feat: support vad for addon.node (#3301)

Co-authored-by: linxiaodong <calm.lin@wukongsch.com>

.devops/main-cuda.Dockerfile

@@ -13,11 +13,10 @@ WORKDIR /app
 ARG CUDA_DOCKER_ARCH=all
 # Set nvcc architecture
 ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
-# Enable cuBLAS
-ENV GGML_CUDA=1
 
 RUN apt-get update && \
     apt-get install -y build-essential libsdl2-dev wget cmake git \
+    && apt-get clean \
     && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
 
 # Ref: https://stackoverflow.com/a/53464012
@@ -25,7 +24,14 @@ ENV CUDA_MAIN_VERSION=12.3
 ENV LD_LIBRARY_PATH /usr/local/cuda-${CUDA_MAIN_VERSION}/compat:$LD_LIBRARY_PATH
 
 COPY .. .
-RUN make base.en
+# Enable cuBLAS
+RUN make base.en CMAKE_ARGS="-DGGML_CUDA=1"
+
+RUN find /app/build -name "*.o" -delete && \
+    find /app/build -name "*.a" -delete && \
+    rm -rf /app/build/CMakeFiles && \
+    rm -rf /app/build/cmake_install.cmake && \
+    rm -rf /app/build/_deps
 
 FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
 ENV CUDA_MAIN_VERSION=12.3
@@ -34,7 +40,11 @@ WORKDIR /app
 
 RUN apt-get update && \
   apt-get install -y curl ffmpeg wget cmake git \
+  && apt-get clean \
   && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
 
 COPY --from=build /app /app
+RUN du -sh /app/*
+RUN find /app -type f -size +100M
+ENV PATH=/app/build/bin:$PATH
 ENTRYPOINT [ "bash", "-c" ]

.devops/main-intel.Dockerfile

@@ -0,0 +1,28 @@
+ARG ONEAPI_VERSION=2025.1.1-0-devel-ubuntu24.04
+
+FROM intel/oneapi-basekit:$ONEAPI_VERSION AS build
+WORKDIR /app
+
+RUN apt-get update && \
+    apt-get install -y build-essential libsdl2-dev wget cmake git \
+    && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
+
+COPY .. .
+# Enable SYCL
+ARG GGML_SYCL_F16=OFF
+RUN if [ "${GGML_SYCL_F16}" = "ON" ]; then \
+        echo "GGML_SYCL_F16 is set" \
+        && export OPT_SYCL_F16="-DGGML_SYCL_F16=ON"; \
+    fi && \
+    make base.en CMAKE_ARGS="-DGGML_SYCL=1 -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx ${OPT_SYCL_F16}"
+
+FROM intel/oneapi-basekit:$ONEAPI_VERSION AS runtime
+WORKDIR /app
+
+RUN apt-get update && \
+  apt-get install -y curl ffmpeg libsdl2-dev wget cmake git \
+  && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
+
+COPY --from=build /app /app
+ENV PATH=/app/build/bin:$PATH
+ENTRYPOINT [ "bash", "-c" ]

.devops/main-musa.Dockerfile

@@ -0,0 +1,40 @@
+ARG UBUNTU_VERSION=22.04
+# This needs to generally match the container host's environment.
+ARG MUSA_VERSION=rc4.0.1
+# Target the MUSA build image
+ARG BASE_MUSA_DEV_CONTAINER=mthreads/musa:${MUSA_VERSION}-mudnn-devel-ubuntu${UBUNTU_VERSION}
+# Target the MUSA runtime image
+ARG BASE_MUSA_RUN_CONTAINER=mthreads/musa:${MUSA_VERSION}-mudnn-runtime-ubuntu${UBUNTU_VERSION}
+
+FROM ${BASE_MUSA_DEV_CONTAINER} AS build
+WORKDIR /app
+
+RUN apt-get update && \
+    apt-get install -y build-essential libsdl2-dev wget cmake git && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/* /tmp/* /var/tmp/*
+
+COPY .. .
+# Enable muBLAS
+RUN make base.en CMAKE_ARGS="-DGGML_MUSA=1"
+
+RUN find /app/build -name "*.o" -delete && \
+    find /app/build -name "*.a" -delete && \
+    rm -rf /app/build/CMakeFiles && \
+    rm -rf /app/build/cmake_install.cmake && \
+    rm -rf /app/build/_deps
+
+FROM ${BASE_MUSA_RUN_CONTAINER} AS runtime
+WORKDIR /app
+
+RUN apt-get update && \
+    apt-get install -y curl ffmpeg wget cmake git && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/* /tmp/* /var/tmp/*
+
+COPY --from=build /app/build/bin /app/build/bin
+COPY --from=build /app/samples /app/samples
+COPY --from=build /app/models /app/models
+
+ENV PATH=/app/build/bin:$PATH
+ENTRYPOINT [ "bash", "-c" ]

.devops/main.Dockerfile

@@ -16,4 +16,5 @@ RUN apt-get update && \
   && rm -rf /var/lib/apt/lists/* /var/cache/apt/archives/*
 
 COPY --from=build /app /app
+ENV PATH=/app/build/bin:$PATH
 ENTRYPOINT [ "bash", "-c" ]

.dockerignore

@@ -0,0 +1,3 @@
+build*/
+.github/
+.devops/

.github/workflows/bindings-ruby.yml

@@ -1,55 +1,11 @@
 name: Bindings Tests (Ruby)
+
 on:
   push:
-    paths:
-      - bindings/ruby/**
-      - src/**/*.c
-      - src/**/*.cpp
-      - src/**/*.h
-      - src/**/*.m
-      - src/**/*.metal
-      - include/**/*.c
-      - include/**/*.cpp
-      - include/**/*.h
-      - include/**/*.m
-      - include/**/*.metal
-      - ggml/**/*.c
-      - ggml/**/*.cpp
-      - ggml/**/*.h
-      - ggml/**/*.m
-      - ggml/**/*.metal
-      - scripts/get-flags.mk
-      - examples/common.h
-      - examples/common.cpp
-      - examples/common-whisper.h
-      - examples/common-whisper.cpp
-      - examples/stb_vorbis.c
-      - examples/miniaudio.h
+    branches:
+      - master
   pull_request:
-    paths:
-      - bindings/ruby/**
-      - src/**/*.c
-      - src/**/*.cpp
-      - src/**/*.h
-      - src/**/*.m
-      - src/**/*.metal
-      - include/**/*.c
-      - include/**/*.cpp
-      - include/**/*.h
-      - include/**/*.m
-      - include/**/*.metal
-      - ggml/**/*.c
-      - ggml/**/*.cpp
-      - ggml/**/*.h
-      - ggml/**/*.m
-      - ggml/**/*.metal
-      - scripts/get-flags.mk
-      - examples/common.h
-      - examples/common.cpp
-      - examples/common-whisper.h
-      - examples/common-whisper.cpp
-      - examples/stb_vorbis.c
-      - examples/miniaudio.h
+    types: [opened, synchronize, reopened]
 
 jobs:
   ubuntu-22:
@@ -60,6 +16,6 @@ jobs:
     steps:
       - uses: ruby/setup-ruby@v1
         with:
-          ruby-version: '3.1'
+          ruby-version: '3.2'
       - uses: actions/checkout@v4
       - run: rake test

.github/workflows/build.yml

@@ -4,6 +4,8 @@ on:
   push:
     branches:
       - master
+    tags:
+      - 'v*'
   pull_request:
     types: [opened, synchronize, reopened]
   workflow_dispatch:
@@ -41,6 +43,7 @@ jobs:
     runs-on: ubuntu-latest
     outputs:
       tag_name: ${{ steps.tag.outputs.name }}
+      should_release: ${{ steps.tag.outputs.should_release }}
 
     steps:
       - name: Checkout with full history
@@ -55,6 +58,7 @@ jobs:
           BUILD_NUMBER=$(git rev-list --count HEAD)
           SHORT_HASH=$(git rev-parse --short=7 HEAD)
           CUSTOM_TAG="${{ github.event.inputs.pre_release_tag }}"
+          SHOULD_RELEASE="false"
 
           echo "Raw values:"
           echo "BUILD_NUMBER: $BUILD_NUMBER"
@@ -62,21 +66,34 @@ jobs:
           echo "BRANCH_NAME: ${{ env.BRANCH_NAME }}"
           echo "CUSTOM_TAG: $CUSTOM_TAG"
 
-          # Use custom tag if provided
-          if [[ -n "$CUSTOM_TAG" ]]; then
+          if [[ "${{ github.ref_type }}" == "tag" ]]; then
+            echo "Using pushed tag name"
+            TAG_NAME="${{ github.ref_name }}"
+            SHOULD_RELEASE="true"
+          elif [[ -n "$CUSTOM_TAG" ]]; then
             echo "Using custom tag"
             TAG_NAME="${CUSTOM_TAG}"
+            SHOULD_RELEASE="true"
+          elif [[ "${{ github.event.inputs.create_release }}" == "true" ]]; then
+            echo "Manual release requested"
+            SHOULD_RELEASE="true"
+            TAG_NAME="b${BUILD_NUMBER}"
           elif [[ "${{ env.BRANCH_NAME }}" == "master" ]]; then
             echo "Using master branch format"
             TAG_NAME="b${BUILD_NUMBER}"
+            SHOULD_RELEASE="false"
           else
             echo "Using non-master branch format"
             SAFE_NAME=$(echo "${{ env.BRANCH_NAME }}" | tr '/' '-')
             TAG_NAME="${SAFE_NAME}-b${BUILD_NUMBER}-${SHORT_HASH}"
+            SHOULD_RELEASE="false"
           fi
 
           echo "Final tag name: $TAG_NAME"
+          echo "Should release: $SHOULD_RELEASE"
           echo "name=$TAG_NAME" >> $GITHUB_OUTPUT
+          echo "should_release=$SHOULD_RELEASE" >> $GITHUB_OUTPUT
+
 
   ubuntu-22:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
@@ -101,6 +118,10 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential libsdl2-dev cmake git
             cmake -B build
@@ -129,6 +150,14 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
+            apt-get update
+            apt-get install -y ca-certificates
+            sed -i "s|http://ports.ubuntu.com|https://mirror.kumi.systems|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential libsdl2-dev cmake git
             cmake -B build -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=armv8-a
@@ -157,6 +186,14 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
+            apt-get update
+            apt-get install -y ca-certificates
+            sed -i "s|http://ports.ubuntu.com|https://mirror.kumi.systems|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential libsdl2-dev cmake git
             cmake -B build -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=armv7-a+fp
@@ -200,23 +237,23 @@ jobs:
           cmake --build build --config Release -j $(sysctl -n hw.logicalcpu)
 
 
-  freeBSD-latest:
-    runs-on: macos-13
-
-    steps:
-      - name: Clone
-        uses: actions/checkout@v4
-
-      - name: Build
-        uses: cross-platform-actions/action@v0.27.0
-        with:
-          operating_system: freebsd
-          version: '14.2'
-          run: |
-            sudo pkg update
-            sudo pkg install -y gmake sdl2 cmake git
-            cmake -B build
-            cmake --build build --config Release
+#  freeBSD-latest:
+#    runs-on: macos-13
+#
+#    steps:
+#      - name: Clone
+#        uses: actions/checkout@v4
+#
+#      - name: Build
+#        uses: cross-platform-actions/action@v0.27.0
+#        with:
+#          operating_system: freebsd
+#          version: '14.2'
+#          run: |
+#            sudo pkg update
+#            sudo pkg install -y gmake sdl2 cmake git
+#            cmake -B build
+#            cmake --build build --config Release
 
   ubuntu-22-gcc:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
@@ -242,6 +279,10 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential cmake libsdl2-dev git
             cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }}
@@ -272,6 +313,14 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
+            apt-get update
+            apt-get install -y ca-certificates
+            sed -i "s|http://ports.ubuntu.com|https://mirror.kumi.systems|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential cmake libsdl2-dev git
             cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=armv8-a
@@ -302,6 +351,14 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
+            apt-get update
+            apt-get install -y ca-certificates
+            sed -i "s|http://ports.ubuntu.com|https://mirror.kumi.systems|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential cmake libsdl2-dev git
             cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DGGML_NATIVE=OFF -DGGML_CPU_ARM_ARCH=armv7-a+fp
@@ -335,6 +392,14 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
+            apt-get update
+            apt-get install -y ca-certificates
+            sed -i "s|http://ports.ubuntu.com|https://mirror.kumi.systems|g" /etc/apt/sources.list
+
             apt update
             apt install -y clang build-essential cmake libsdl2-dev git
             cmake . -DWHISPER_SDL2=ON -DCMAKE_BUILD_TYPE=${{ matrix.build }} -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_COMPILER=clang
@@ -365,6 +430,10 @@ jobs:
             -v ${{ github.workspace }}:/workspace \
             -w /workspace ${{ env.ubuntu_image }} /bin/sh -c '
             set -e
+            export DEBIAN_FRONTEND=noninteractive
+            sed -i "s|archive.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+            sed -i "s|security.ubuntu.com|mirrors.kernel.org|g" /etc/apt/sources.list
+
             apt update
             apt install -y build-essential cmake git
             cmake . -DCMAKE_BUILD_TYPE=Debug \
@@ -527,6 +596,7 @@ jobs:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
             github.event.inputs.run_type == 'full-ci' }}
     runs-on: windows-latest
+    needs: determine-tag
 
     strategy:
       matrix:
@@ -561,6 +631,7 @@ jobs:
         run: >
           cmake -S . -B ./build -A ${{ matrix.arch }}
           -DCMAKE_BUILD_TYPE=${{ matrix.build }}
+          -DBUILD_SHARED_LIBS=ON
           -DWHISPER_SDL2=${{ matrix.sdl2 }}
 
       - name: Build
@@ -572,18 +643,48 @@ jobs:
         if: matrix.sdl2 == 'ON'
         run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
 
-      - name: Upload dll
-        uses: actions/upload-artifact@v4
-        with:
-          name: ${{ matrix.jnaPath }}_whisper.dll
-          path: build/bin/${{ matrix.build }}/whisper.dll
-
-      - name: Upload binaries
+      - name: Upload SDL2.dll
         if: matrix.sdl2 == 'ON'
         uses: actions/upload-artifact@v4
         with:
-          name: whisper-bin-${{ matrix.arch }}
-          path: build/bin/${{ matrix.build }}
+          name: ${{ matrix.s2arc }}_SDL2.dll
+          path: build/bin/${{ matrix.build }}/SDL2.dll
+
+      - name: Upload whisper dll
+        uses: actions/upload-artifact@v4
+        with:
+          name: whisper_${{ matrix.arch }}.dll
+          path: build/bin/${{ matrix.build }}/whisper.dll
+
+      - name: Upload ggml dll
+        uses: actions/upload-artifact@v4
+        with:
+          name: ggml_${{ matrix.arch }}.dll
+          path: build/bin/${{ matrix.build }}/ggml.dll
+
+      - name: Upload ggml base dll
+        uses: actions/upload-artifact@v4
+        with:
+          name: ggml_base_${{ matrix.arch }}.dll
+          path: build/bin/${{ matrix.build }}/ggml-base.dll
+
+      - name: Upload ggml cpu dll
+        uses: actions/upload-artifact@v4
+        with:
+          name: ggml_cpu_${{ matrix.arch }}.dll
+          path: build/bin/${{ matrix.build }}/ggml-cpu.dll
+
+      - name: Pack bin artifacts
+        shell: pwsh
+        run: |
+              Compress-Archive -Path "build/bin/${{ matrix.build }}" -DestinationPath "whisper-bin-${{ matrix.arch }}.zip"
+
+      - name: Upload binaries
+        if: matrix.sdl2 == 'ON' && ${{ needs.determine-tag.outputs.should_release }}
+        uses: actions/upload-artifact@v4
+        with:
+          name: whisper-bin-${{ matrix.arch }}.zip
+          path: whisper-bin-${{ matrix.arch }}.zip
 
   windows-blas:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
@@ -596,11 +697,14 @@ jobs:
         arch: [Win32, x64]
         blas: [ON]
         sdl2: [ON]
+        blasver: [0.3.29]
         include:
           - arch: Win32
             s2arc: x86
+            blasfile: x86
           - arch: x64
             s2arc: x64
+            blasfile: x64_64
           - sdl2: ON
             s2ver: 2.28.5
 
@@ -621,7 +725,8 @@ jobs:
       - name: Install OpenBLAS and pkgconfiglite
         if: matrix.blas == 'ON'
         run: |
-          vcpkg install --triplet=${{ matrix.s2arc }}-windows openblas
+          Invoke-WebRequest "https://github.com/OpenMathLib/OpenBLAS/releases/download/v${{matrix.blasver}}/OpenBLAS-${{matrix.blasver}}_${{matrix.blasfile}}.zip" -OutFile "OpenBLAS-${{matrix.blasver}}.zip"
+          Expand-Archive "OpenBLAS-${{matrix.blasver}}.zip" -DestinationPath "OpenBLAS-${{matrix.blasver}}"
           choco install pkgconfiglite
 
       - name: Fetch SDL2 and set SDL2_DIR
@@ -638,6 +743,8 @@ jobs:
           -DCMAKE_BUILD_TYPE=${{ matrix.build }}
           -DGGML_BLAS=${{ matrix.blas }}
           -DGGML_BLAS_VENDOR=OpenBLAS
+          -DBLAS_LIBRARIES="$env:GITHUB_WORKSPACE/OpenBLAS-${{matrix.blasver}}/lib/libopenblas.lib"
+          -DBLAS_INCLUDE_DIRS="$env:GITHUB_WORKSPACE/OpenBLAS-${{matrix.blasver}}/include"
           -DWHISPER_SDL2=${{ matrix.sdl2 }}
 
       - name: Build
@@ -647,30 +754,37 @@ jobs:
 
       - name: Copy openblas.dll
         if: matrix.blas == 'ON'
-        run: copy "C:/vcpkg/packages/openblas_${{ matrix.s2arc }}-windows/bin/openblas.dll" build/bin/${{ matrix.build }}
+        run: copy "$env:GITHUB_WORKSPACE/OpenBLAS-${{matrix.blasver}}/bin/libopenblas.dll" build/bin/${{ matrix.build }}
 
       - name: Copy SDL2.dll
         if: matrix.sdl2 == 'ON'
         run: copy "$env:SDL2_DIR/../lib/${{ matrix.s2arc }}/SDL2.dll" build/bin/${{ matrix.build }}
 
+      - name: Pack bin artifacts
+        shell: pwsh
+        run: |
+              Compress-Archive -Path "build/bin/${{ matrix.build }}" -DestinationPath "whisper-blas-bin-${{ matrix.arch }}.zip"
+
       - name: Upload binaries
-        if: matrix.blas == 'ON' && matrix.sdl2 == 'ON'
+        if: matrix.blas == 'ON' && matrix.sdl2 == 'ON' && ${{ needs.determine-tag.outputs.should_release }}
         uses: actions/upload-artifact@v4
         with:
-          name: whisper-blas-bin-${{ matrix.arch }}
-          path: build/bin/${{ matrix.build }}
+          name: whisper-blas-bin-${{ matrix.arch }}.zip
+          path: whisper-blas-bin-${{ matrix.arch }}.zip
 
   windows-cublas:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
             github.event.inputs.run_type == 'full-ci' }}
-    runs-on: windows-2019
+    runs-on: windows-2022
+    needs: determine-tag
     strategy:
+      fail-fast: false
       matrix:
         build: [Release]
         arch: [x64]
         cublas: [ON]
         sdl2: [ON]
-        cuda-toolkit: [12.2.0, 11.8.0]
+        cuda-toolkit: [12.4.0, 11.8.0]
         include:
           - arch: x64
             sdl2: ON
@@ -738,7 +852,7 @@ jobs:
           xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
 
           # Visual Studio integration
-          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\MSBuild\Microsoft\VC\v160\BuildCustomizations" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\MSBuild\Microsoft\VC\v170\BuildCustomizations" /E /I /H /Y
 
           # Set environment variables
           echo "$CUDA_TOOLKIT_DIR\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
@@ -746,23 +860,23 @@ jobs:
           echo "CUDA_PATH=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
           echo "CUDA_PATH_V11_8=$CUDA_TOOLKIT_DIR" | Out-File -FilePath $env:GITHUB_ENV -Append -Encoding utf8
         
-      - name: Install Cuda Toolkit 12.2.0
-        if: ${{ matrix.cuda-toolkit == '12.2.0' }}
+      - name: Install Cuda Toolkit 12.4.0
+        if: ${{ matrix.cuda-toolkit == '12.4.0' }}
         run: |
           $CUDA_VERSION = ${{ matrix.cuda-toolkit }}
           $CUDA_TOOLKIT_DIR = "C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v$CUDA_VERSION"
           $CUDA_DOWNLOAD = "https://developer.download.nvidia.com/compute/cuda/redist"
 
           # Components versions
-          $CUDART_VER   = "12.2.140"
-          $NVCC_VER     = "12.2.140"
-          $NVRTC_VER    = "12.2.140"
-          $CUBLAS_VER   = "12.2.5.6"
-          $NVTX_VER     = "12.2.140"
-          $PROFILER_VER = "12.2.140"
-          $VS_VER       = "12.2.140"
-          $NVPROF_VER   = "12.2.142"
-          $CCCL_VER     = "12.2.140"
+          $CUDART_VER   = "12.4.127"
+          $NVCC_VER     = "12.4.131"
+          $NVRTC_VER    = "12.4.127"
+          $CUBLAS_VER   = "12.4.5.8"
+          $NVTX_VER     = "12.4.127"
+          $PROFILER_VER = "12.4.127"
+          $VS_VER       = "12.4.127"
+          $NVPROF_VER   = "12.4.128"
+          $CCCL_VER     = "12.4.127"
 
           # Create the directory where the CUDA Toolkit will be installed
           mkdir -p $CUDA_TOOLKIT_DIR
@@ -796,7 +910,7 @@ jobs:
           xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\*" "$CUDA_TOOLKIT_DIR" /E /I /H /Y
 
           # Visual Studio integration
-          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\MSBuild\Microsoft\VC\v160\BuildCustomizations" /E /I /H /Y
+          xcopy "$CUDA_TOOLKIT_DIR\visual_studio_integration-windows-x86_64-${VS_VER}-archive\visual_studio_integration\MSBuildExtensions\*" "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\MSBuild\Microsoft\VC\v170\BuildCustomizations" /E /I /H /Y
 
           # Set environment variables
           echo "$CUDA_TOOLKIT_DIR\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
@@ -824,14 +938,21 @@ jobs:
       - name: Build Project
         shell: cmd
         run: |
-          call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvars64.bat"
+          call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat"
           cmake --version
           where cmake
+          if "${{ matrix.cuda-toolkit }}" == "11.8.0" (
+            set CUDA_FLAGS=-allow-unsupported-compiler -D_ALLOW_COMPILER_AND_STL_VERSION_MISMATCH -D_DISABLE_CONSTEXPR_MUTEX_CONSTRUCTOR
+          ) else (
+            set CUDA_FLAGS=
+          )
           cmake -S . -B build -G "Ninja Multi-Config" ^
             -DCMAKE_BUILD_TYPE=${{ matrix.build }} ^
             -DGGML_CUDA=${{ matrix.cublas }} ^
             -DWHISPER_SDL2=${{ matrix.sdl2 }} ^
-            -DSDL2_DIR="%SDL2_DIR%"
+            -DSDL2_DIR="%SDL2_DIR%" ^
+            -DCMAKE_POLICY_VERSION_MINIMUM=3.5 ^
+            -DCMAKE_CUDA_FLAGS="%CUDA_FLAGS%"
           set /A NINJA_JOBS=%NUMBER_OF_PROCESSORS%-1
           cmake --build build --config ${{ matrix.build }} -j %NUMBER_OF_PROCESSORS%
 
@@ -848,11 +969,17 @@ jobs:
         if: matrix.sdl2 == 'ON'
         run: copy "$env:SDL2_DIR/../lib/${{ matrix.arch }}/SDL2.dll" build/bin/${{ matrix.build }}
 
+      - name: Pack bin artifacts
+        shell: pwsh
+        run: |
+              Compress-Archive -Path "build/bin/${{ matrix.build }}" -DestinationPath "whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}.zip"
+
       - name: Upload binaries
+        if: ${{ needs.determine-tag.outputs.should_release }}
         uses: actions/upload-artifact@v4
         with:
-          name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}
-          path: build/bin/${{ matrix.build }}
+          name: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}.zip
+          path: whisper-cublas-${{ matrix.cuda-toolkit }}-bin-${{ matrix.arch }}.zip
 
   emscripten:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
@@ -925,20 +1052,15 @@ jobs:
 
       - name: Pack artifacts
         id: pack_artifacts
-        if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
-                github.event.inputs.create_release == 'true' ||
-                github.event.inputs.pre_release_tag != '' }}
         run: |
           zip --symlinks -r whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework.zip build-apple/whisper.xcframework
 
       - name: Upload artifacts
-        if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
-                github.event.inputs.create_release == 'true' ||
-                github.event.inputs.pre_release_tag != '' }}
+        if: ${{ needs.determine-tag.outputs.should_release }}
         uses: actions/upload-artifact@v4
         with:
           path: whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework.zip
-          name: whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework
+          name: whisper-${{ needs.determine-tag.outputs.tag_name }}-xcframework.zip
 
   android:
     if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
@@ -996,38 +1118,93 @@ jobs:
           chmod +x ./gradlew
           ./gradlew assembleRelease
 
-# TODO: disabled because of following fail: https://github.com/ggerganov/whisper.cpp/actions/runs/9686220096/job/26735899598
-#  java:
-#    needs: [ 'windows' ]
-#    runs-on: windows-latest
-#    steps:
-#      - uses: actions/checkout@v4
-#
-#      - name: Install Java
-#        uses: actions/setup-java@v4
-#        with:
-#          distribution: zulu
-#          java-version: 20
-#
-#      - name: Download Windows lib
-#        uses: actions/download-artifact@v4
-#        with:
-#          name: win32-x86-64_whisper.dll
-#          path: bindings/java/build/generated/resources/main/win32-x86-64
-#
-#      - name: Build
-#        run: |
-#          models\download-ggml-model.cmd tiny.en
-#          cd bindings/java
-#          chmod +x ./gradlew
-#          ./gradlew build
-#
-#      - name: Upload jar
-#        uses: actions/upload-artifact@v4
-#        with:
-#          name: whispercpp.jar
-#          path: bindings/java/build/libs/whispercpp-*.jar
-#
+  bindings-java:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
+    needs: ['windows']
+    runs-on: windows-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install Java
+        uses: actions/setup-java@v4
+        with:
+          distribution: zulu
+          java-version: 20
+
+      - name: Download Whisper Windows lib
+        uses: actions/download-artifact@v4
+        with:
+          name: whisper_x64.dll
+
+      - name: Download GGML Windows lib
+        uses: actions/download-artifact@v4
+        with:
+          name: ggml_x64.dll
+
+      - name: Download GGML Base Windows lib
+        uses: actions/download-artifact@v4
+        with:
+          name: ggml_base_x64.dll
+
+      - name: Download GGML CPU Windows lib
+        uses: actions/download-artifact@v4
+        with:
+          name: ggml_cpu_x64.dll
+
+      - name: Download SDL2.dll
+        uses: actions/download-artifact@v4
+        with:
+          name: x64_SDL2.dll
+
+      - name: List downloaded files
+        shell: pwsh
+        run: |
+          Get-ChildItem -Path "." -Recurse -Filter "*.dll"
+
+      - name: Move DLL to correct location
+        shell: pwsh
+        run: |
+          New-Item -Path "build\bin\Release" -ItemType Directory -Force
+
+          Copy-Item -Path "whisper.dll" -Destination "build\bin\Release\whisper.dll" -Force
+          Write-Host "Copied whisper.dll to build\bin\Release\whisper.dll directory"
+
+          Copy-Item -Path "ggml.dll" -Destination "build\bin\Release\ggml.dll" -Force
+          Write-Host "Copied ggml.dll to build\bin\Release\ggml.dll directory"
+
+          Copy-Item -Path "ggml-base.dll" -Destination "build\bin\Release\ggml-base.dll" -Force
+          Write-Host "Copied ggml-base.dll to build\bin\Release\ggml-base.dll directory"
+
+          Copy-Item -Path "ggml-cpu.dll" -Destination "build\bin\Release\ggml-cpu.dll" -Force
+          Write-Host "Copied ggml-cpu.dll to build\bin\Release\ggml-cpu.dll directory"
+
+          Copy-Item -Path "SDL2.dll" -Destination "build\bin\Release\SDL2.dll" -Force
+          Write-Host "Copied SDL2.dll to build\bin\Release\SDL2.dll directory"
+
+      - name: List build release files
+        shell: pwsh
+        run: |
+          Get-ChildItem -Path "build\Release" -Recurse -Filter "*.dll"
+
+      - name: Build
+        run: |
+          models\download-ggml-model.cmd tiny.en models/
+          cd bindings/java
+          chmod +x ./gradlew
+          ./gradlew build --info
+
+      - name: Pack jar artifacts
+        shell: pwsh
+        run: |
+              Compress-Archive -Path "bindings/java/build/libs/whispercpp-*.jar" -DestinationPath "whispercpp.jar.zip"
+
+      - name: Upload jar
+        uses: actions/upload-artifact@v4
+        with:
+          name: whispercpp.jar.zip
+          path: whispercpp.jar.zip
+
 #      - name: Publish package
 #        if: ${{ github.ref == 'refs/heads/master' }}
 #        uses: gradle/gradle-build-action@v2.4.2
@@ -1057,13 +1234,16 @@ jobs:
           ./build/bin/quantize models/ggml-tiny.en.bin models/ggml-tiny.en-q4_0.bin q4_0
 
   release:
-    if: ${{ github.event.inputs.create_release == 'true' || github.event.inputs.pre_release_tag != '' }}
+    if: ${{ github.event.inputs.create_release == 'true' || github.event.inputs.pre_release_tag != '' || startsWith(github.ref, 'refs/tags/v') }}
 
     runs-on: ubuntu-latest
 
     needs:
       - determine-tag
       - ios-xcode-build
+      - windows
+      - windows-blas
+      - windows-cublas
 
     steps:
       - name: Clone
@@ -1097,6 +1277,7 @@ jobs:
         with:
           tag_name: ${{ needs.determine-tag.outputs.tag_name }}
           prerelease: ${{ github.event.inputs.pre_release_tag != '' }}
+          draft: true
 
       - name: Upload release
         id: upload_release
@@ -1123,7 +1304,8 @@ jobs:
   coreml-base-en:
     if: ${{ (github.event_name == 'push' && github.ref == 'refs/heads/master') ||
             github.event.inputs.create_release == 'true' ||
-            github.event.inputs.pre_release_tag != '' }}
+            github.event.inputs.pre_release_tag != '' ||
+            startsWith(github.ref, 'refs/tags/v') }}
     runs-on: macos-latest
     needs: determine-tag
 
@@ -1147,3 +1329,23 @@ jobs:
           source venv/bin/activate
           pip install ane_transformers openai-whisper coremltools
           ./models/generate-coreml-model.sh ${{ env.MODEL_NAME }}
+
+  vad:
+    if: ${{ github.event_name == 'push' || github.event_name == 'pull_request' ||
+            github.event.inputs.run_type == 'full-ci' }}
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Build
+        shell: bash
+        run: |
+          cmake -B build
+          cmake --build build --config Release
+
+      - name: Test
+        shell: bash
+        run: |
+          ctest -R ^test-vad$ --test-dir build --output-on-failure -VV

.github/workflows/docker.yml

@@ -15,12 +15,13 @@ jobs:
     env:
       COMMIT_SHA: ${{ github.sha }}
     strategy:
+      fail-fast: false
       matrix:
         config:
           - { tag: "main", dockerfile: ".devops/main.Dockerfile", platform: "linux/amd64" }
-          #TODO: the cuda image keeps failing - disable for now
-          #      https://github.com/ggerganov/whisper.cpp/actions/runs/11019444428/job/30602020339
-          #- { tag: "main-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platform: "linux/amd64" }
+          - { tag: "main-musa", dockerfile: ".devops/main-musa.Dockerfile", platform: "linux/amd64" }
+          - { tag: "main-intel", dockerfile: ".devops/main-intel.Dockerfile", platform: "linux/amd64" }
+          - { tag: "main-cuda", dockerfile: ".devops/main-cuda.Dockerfile", platform: "linux/amd64" }
 
     steps:
       - name: Check out the repo
@@ -41,21 +42,35 @@ jobs:
           username: ${{ github.repository_owner }}
           password: ${{ secrets.GITHUB_TOKEN }}
 
-      - name: Build and push Docker image (versioned)
-        if: github.event_name == 'push'
-        uses: docker/build-push-action@v5
-        with:
-          context: .
-          push: true
-          platforms: ${{ matrix.config.platform }}
-          tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}-${{ env.COMMIT_SHA }}"
-          file: ${{ matrix.config.dockerfile }}
+      - name: Free up disk space
+        run: |
+          sudo apt-get remove -y '^dotnet-.*' '^llvm-.*' '^mysql-.*' '^postgresql-.*'
+          sudo apt-get autoremove -y
+          sudo apt-get autoclean
+
+          sudo rm -rf /usr/share/dotnet
+          sudo rm -rf /usr/local/lib/android
+          sudo rm -rf /opt/ghc
+          sudo rm -rf /opt/hostedtoolcache/CodeQL
+
+          docker system prune -af
+
+          df -h
+
+      - name: Generate tags
+        id: tags
+        run: |
+          TAGS="ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}"
+          if [ "${{ github.event_name }}" == "push" ]; then
+            TAGS="$TAGS,ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}-${{ env.COMMIT_SHA }}"
+          fi
+          echo "tags=$TAGS" >> $GITHUB_OUTPUT
 
       - name: Build and push Docker image (tagged)
-        uses: docker/build-push-action@v4
+        uses: docker/build-push-action@v5
         with:
           context: .
           push: ${{ github.event_name == 'push' }}
           platforms: ${{ matrix.config.platform }}
-          tags: "ghcr.io/${{ github.repository }}:${{ matrix.config.tag }}"
+          tags: ${{ steps.tags.outputs.tags }}
           file: ${{ matrix.config.dockerfile }}

.gitignore

@@ -14,6 +14,7 @@
 
 build/
 build-*/
+build_*/
 
 # SPM
 .build/
@@ -49,6 +50,8 @@ extra/bench-gg.txt
 models/*.mlmodel
 models/*.mlmodelc
 models/*.mlpackage
+models/*-encoder-openvino.xml
+models/*-encoder-openvino-cache/
 bindings/java/.gradle/
 bindings/java/.idea/
 .idea/

CMakeLists.txt

@@ -1,6 +1,6 @@
 cmake_minimum_required(VERSION 3.5) # for add_link_options and implicit target directories.
 project("whisper.cpp" C CXX)
-project("whisper.cpp" VERSION 1.7.4)
+project("whisper.cpp" VERSION 1.7.6)
 include(CheckIncludeFileCXX)
 
 set(SOVERSION 1)
@@ -59,9 +59,6 @@ option(BUILD_SHARED_LIBS "build shared libraries" ${BUILD_SHARED_LIBS_DEFAULT})
 # option list
 #
 
-# general
-option(WHISPER_CCACHE "whisper: use ccache if available" ON)
-
 # debug
 option(WHISPER_ALL_WARNINGS           "whisper: enable all compiler warnings"                   ON)
 option(WHISPER_ALL_WARNINGS_3RD_PARTY "whisper: enable all compiler warnings in 3rd party libs" OFF)
@@ -96,7 +93,6 @@ option(WHISPER_OPENVINO              "whisper: support for OpenVINO"      OFF)
 include(${CMAKE_CURRENT_SOURCE_DIR}/cmake/build-info.cmake)
 
 # override ggml options
-set(GGML_CCACHE             ${WHISPER_CCACHE})
 set(GGML_SANITIZE_THREAD    ${WHISPER_SANITIZE_THREAD})
 set(GGML_SANITIZE_ADDRESS   ${WHISPER_SANITIZE_ADDRESS})
 set(GGML_SANITIZE_UNDEFINED ${WHISPER_SANITIZE_UNDEFINED})
@@ -121,6 +117,12 @@ whisper_option_depr(WARNING     WHISPER_OPENMP              GGML_OPENMP)
 whisper_option_depr(WARNING     WHISPER_RPC                 GGML_RPC)
 whisper_option_depr(WARNING     WHISPER_SYCL                GGML_SYCL)
 whisper_option_depr(WARNING     WHISPER_SYCL_F16            GGML_SYCL_F16)
+whisper_option_depr(WARNING     WHISPER_CCACHE              GGML_CCACHE)
+
+if (GGML_CUDA AND NOT MSVC)
+    #GGML_CUDA enabled, add the necessary compile options -Wno-deprecated-gpu-targets
+    add_compile_options(-Wno-deprecated-gpu-targets)
+endif()
 
 #
 # build the library
@@ -135,6 +137,22 @@ if (NOT TARGET ggml)
         add_library(ggml ALIAS ggml::ggml)
     else()
         add_subdirectory(ggml)
+        if(WIN32)
+            # The following adds a _DISABLE_CONSTEXPR_MUTEX_CONSTRUCTOR macro and is a workaround for
+            # the Windows C++ standard library which does not support constexpr mutexes.
+            # From the release notes://github.com/microsoft/STL/wiki/Changelog
+            #  Disable constexpr mutex constructor on Windows
+            #  Fixed mutex's constructor to be constexpr. #3824 #4000 #4339
+            #  Note: Programs that aren't following the documented restrictions on binary compatibility may encounter
+            #  null dereferences in mutex machinery. You must follow this rule:
+            #  When you mix binaries built by different supported versions of the toolset, the Redistributable version
+            #  must be at least as new as the latest toolset used by any app component.
+            #  You can define _DISABLE_CONSTEXPR_MUTEX_CONSTRUCTOR as an escape hatch.
+            #
+            # Specifically to whisper.cpp this would cause a crash when using the Java bindings.
+            # resulting in a Invalid memory access error.
+            target_compile_definitions(ggml-base PRIVATE _DISABLE_CONSTEXPR_MUTEX_CONSTRUCTOR)
+        endif()
     endif()
     # ... otherwise assume ggml is added by a parent CMakeLists.txt
 endif()
@@ -160,6 +178,10 @@ get_directory_property(WHISPER_TRANSIENT_DEFINES COMPILE_DEFINITIONS)
 set_target_properties(whisper PROPERTIES PUBLIC_HEADER ${CMAKE_CURRENT_SOURCE_DIR}/include/whisper.h)
 install(TARGETS whisper LIBRARY PUBLIC_HEADER)
 
+target_compile_definitions(whisper PRIVATE
+    WHISPER_VERSION="${PROJECT_VERSION}"
+)
+
 configure_package_config_file(
         ${CMAKE_CURRENT_SOURCE_DIR}/cmake/whisper-config.cmake.in
         ${CMAKE_CURRENT_BINARY_DIR}/whisper-config.cmake
@@ -197,3 +219,37 @@ endif ()
 if (WHISPER_BUILD_EXAMPLES)
     add_subdirectory(examples)
 endif()
+
+if (MSVC)
+    set(MSVC_WARNING_FLAGS
+        /wd4101  # Unreferenced local variable
+        /wd4005  # Macro redefinition
+        /wd4065  # switch statement contains 'default' but no 'case' labels
+        /wd4267  # Conversion from 'size_t' to a smaller type, possible loss of data
+        /wd4244  # Conversion from one type to another type, possible loss of ata
+        /wd4805  # Unsafe mix of type
+        /wd4305  # Truncation from 'type1' to 'type2' (often double to float)
+        /wd4996  # Function or variable may be unsafe/deprecated
+    )
+    function(disable_msvc_warnings target_name)
+        if(TARGET ${target_name})
+            target_compile_options(${target_name} PRIVATE ${MSVC_WARNING_FLAGS})
+        endif()
+    endfunction()
+
+    if (WHISPER_BUILD_EXAMPLES)
+        disable_msvc_warnings(whisper)
+        disable_msvc_warnings(common)
+        disable_msvc_warnings(common-sdl)
+        disable_msvc_warnings(lsp)
+        disable_msvc_warnings(wchess-core)
+        disable_msvc_warnings(whisper-command)
+        disable_msvc_warnings(whisper-cli)
+        disable_msvc_warnings(whisper-server)
+        disable_msvc_warnings(whisper-stream)
+        disable_msvc_warnings(whisper-talk-llama)
+        disable_msvc_warnings(whisper-bench)
+        disable_msvc_warnings(quantize)
+        disable_msvc_warnings(vad-speech-segments)
+    endif()
+endif()

Makefile

@@ -4,7 +4,7 @@
 
 .PHONY: build
 build:
-	cmake -B build
+	cmake -B build $(CMAKE_ARGS)
 	cmake --build build --config Release
 
 # download a few audio samples into folder "./samples":
@@ -41,17 +41,17 @@ samples:
 
 tiny.en tiny base.en base small.en small medium.en medium large-v1 large-v2 large-v3 large-v3-turbo:
 	bash ./models/download-ggml-model.sh $@
-	cmake -B build
+	cmake -B build $(CMAKE_ARGS)
 	cmake --build build --config Release
 	@echo ""
 	@echo "==============================================="
 	@echo "Running $@ on all samples in ./samples ..."
 	@echo "==============================================="
 	@echo ""
-	@for f in samples/*$(.flac .mp3 .ogg .wav); do \
+	@for f in samples/*.{flac,mp3,ogg,wav}; do \
 		echo "----------------------------------------------" ; \
 		echo "[+] Running $@ on $$f ... (run 'ffplay $$f' to listen)" ; \
-	    echo "----------------------------------------------" ; \
+		echo "----------------------------------------------" ; \
 		echo "" ; \
 		./build/bin/whisper-cli -m models/ggml-$@.bin -f $$f ; \
 		echo "" ; \

README.md

@@ -2,15 +2,12 @@
 
 ![whisper.cpp](https://user-images.githubusercontent.com/1991296/235238348-05d0f6a4-da44-4900-a1de-d0707e75b763.jpeg)
 
-[![Actions Status](https://github.com/ggerganov/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggerganov/whisper.cpp/actions)
+[![Actions Status](https://github.com/ggml-org/whisper.cpp/workflows/CI/badge.svg)](https://github.com/ggml-org/whisper.cpp/actions)
 [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
 [![Conan Center](https://shields.io/conan/v/whisper-cpp)](https://conan.io/center/whisper-cpp)
 [![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
 
-> [!NOTE]
-> New maintenance roadmap: https://github.com/ggerganov/whisper.cpp/discussions/2788
-
-Stable: [v1.7.4](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.7.4) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
+Stable: [v1.7.6](https://github.com/ggml-org/whisper.cpp/releases/tag/v1.7.6) / [Roadmap](https://github.com/orgs/ggml-org/projects/4/)
 
 High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
 
@@ -26,7 +23,9 @@ High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisp
 - [Efficient GPU support for NVIDIA](#nvidia-gpu-support)
 - [OpenVINO Support](#openvino-support)
 - [Ascend NPU Support](#ascend-npu-support)
-- [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/include/whisper.h)
+- [Moore Threads GPU Support](#moore-threads-gpu-support)
+- [C-style API](https://github.com/ggml-org/whisper.cpp/blob/master/include/whisper.h)
+- [Voice Activity Detection (VAD)](#voice-activity-detection-vad)
 
 Supported platforms:
 
@@ -34,14 +33,14 @@ Supported platforms:
 - [x] [iOS](examples/whisper.objc)
 - [x] [Android](examples/whisper.android)
 - [x] [Java](bindings/java/README.md)
-- [x] Linux / [FreeBSD](https://github.com/ggerganov/whisper.cpp/issues/56#issuecomment-1350920264)
+- [x] Linux / [FreeBSD](https://github.com/ggml-org/whisper.cpp/issues/56#issuecomment-1350920264)
 - [x] [WebAssembly](examples/whisper.wasm)
-- [x] Windows ([MSVC](https://github.com/ggerganov/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggerganov/whisper.cpp/issues/168)]
-- [x] [Raspberry Pi](https://github.com/ggerganov/whisper.cpp/discussions/166)
-- [x] [Docker](https://github.com/ggerganov/whisper.cpp/pkgs/container/whisper.cpp)
+- [x] Windows ([MSVC](https://github.com/ggml-org/whisper.cpp/blob/master/.github/workflows/build.yml#L117-L144) and [MinGW](https://github.com/ggml-org/whisper.cpp/issues/168))
+- [x] [Raspberry Pi](https://github.com/ggml-org/whisper.cpp/discussions/166)
+- [x] [Docker](https://github.com/ggml-org/whisper.cpp/pkgs/container/whisper.cpp)
 
 The entire high-level implementation of the model is contained in [whisper.h](include/whisper.h) and [whisper.cpp](src/whisper.cpp).
-The rest of the code is part of the [`ggml`](https://github.com/ggerganov/ggml) machine learning library.
+The rest of the code is part of the [`ggml`](https://github.com/ggml-org/ggml) machine learning library.
 
 Having such a lightweight implementation of the model allows to easily integrate it in different platforms and applications.
 As an example, here is a video of running the model on an iPhone 13 device - fully offline, on-device: [whisper.objc](examples/whisper.objc)
@@ -54,14 +53,14 @@ https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a
 
 On Apple Silicon, the inference runs fully on the GPU via Metal:
 
-https://github.com/ggerganov/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
+https://github.com/ggml-org/whisper.cpp/assets/1991296/c82e8f86-60dc-49f2-b048-d2fdbd6b5225
 
 ## Quick start
 
 First clone the repository:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 ```
 
 Navigate into the directory:
@@ -81,7 +80,7 @@ Now build the [whisper-cli](examples/cli) example and transcribe an audio file l
 ```bash
 # build the project
 cmake -B build
-cmake --build build --config Release
+cmake --build build -j --config Release
 
 # transcribe an audio file
 ./build/bin/whisper-cli -f samples/jfk.wav
@@ -150,8 +149,9 @@ standard cmake setup with:
 ```bash
 # build with GGML_BLAS defined
 cmake -B build -DGGML_BLAS=1
-cmake --build build --config Release
+cmake --build build -j --config Release
 ./build/bin/whisper-cli [ .. etc .. ]
+```
 
 ## Quantization
 
@@ -163,7 +163,7 @@ Here are the steps for creating and using a quantized model:
 ```bash
 # quantize a model with Q5_0 method
 cmake -B build
-cmake --build build --config Release
+cmake --build build -j --config Release
 ./build/bin/quantize models/ggml-base.en.bin models/ggml-base.en-q5_0.bin q5_0
 
 # run the examples as usual, specifying the quantized model file
@@ -225,7 +225,7 @@ speed-up - more than x3 faster compared with CPU-only execution. Here are the in
   The first run on a device is slow, since the ANE service compiles the Core ML model to some device-specific format.
   Next runs are faster.
 
-For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggerganov/whisper.cpp/pull/566).
+For more information about the Core ML implementation please refer to PR [#566](https://github.com/ggml-org/whisper.cpp/pull/566).
 
 ## OpenVINO support
 
@@ -267,7 +267,7 @@ This can result in significant speedup in encoder performance. Here are the inst
 
 - Build `whisper.cpp` with OpenVINO support:
 
-  Download OpenVINO package from [release page](https://github.com/openvinotoolkit/openvino/releases). The recommended version to use is [2023.0.0](https://github.com/openvinotoolkit/openvino/releases/tag/2023.0.0).
+  Download OpenVINO package from [release page](https://github.com/openvinotoolkit/openvino/releases). The recommended version to use is [2024.6.0](https://github.com/openvinotoolkit/openvino/releases/tag/2024.6.0). Ready to use Binaries of the required libraries can be found in the [OpenVino Archives](https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.6/)
 
   After downloading & extracting package onto your development system, set up required environment by sourcing setupvars script. For example:
 
@@ -310,7 +310,7 @@ This can result in significant speedup in encoder performance. Here are the inst
   The first time run on an OpenVINO device is slow, since the OpenVINO framework will compile the IR (Intermediate Representation) model to a device-specific 'blob'. This device-specific blob will get
   cached for the next run.
 
-For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggerganov/whisper.cpp/pull/1037).
+For more information about the OpenVINO implementation please refer to PR [#1037](https://github.com/ggml-org/whisper.cpp/pull/1037).
 
 ## NVIDIA GPU support
 
@@ -324,6 +324,12 @@ cmake -B build -DGGML_CUDA=1
 cmake --build build -j --config Release
 ```
 
+or for newer NVIDIA GPU's (RTX 5000 series):
+```
+cmake -B build -DGGML_CUDA=1 -DCMAKE_CUDA_ARCHITECTURES="86"
+cmake --build build -j --config Release
+```
+
 ## Vulkan GPU support
 Cross-vendor solution which allows you to accelerate workload on your GPU.
 First, make sure your graphics card driver provides support for Vulkan API.
@@ -377,6 +383,56 @@ Run the inference examples as usual, for example:
 - If you have trouble with Ascend NPU device, please create a issue with **[CANN]** prefix/tag.
 - If you run successfully with your Ascend NPU device, please help update the table `Verified devices`.
 
+## Moore Threads GPU support
+
+With Moore Threads cards the processing of the models is done efficiently on the GPU via muBLAS and custom MUSA kernels.
+First, make sure you have installed `MUSA SDK rc4.0.1`: https://developer.mthreads.com/sdk/download/musa?equipment=&os=&driverVersion=&version=4.0.1
+
+Now build `whisper.cpp` with MUSA support:
+
+```
+cmake -B build -DGGML_MUSA=1
+cmake --build build -j --config Release
+```
+
+or specify the architecture for your Moore Threads GPU. For example, if you have a MTT S80 GPU, you can specify the architecture as follows:
+
+```
+cmake -B build -DGGML_MUSA=1 -DMUSA_ARCHITECTURES="21"
+cmake --build build -j --config Release
+```
+
+## FFmpeg support (Linux only)
+
+If you want to support more audio formats (such as Opus and AAC), you can turn on the `WHISPER_FFMPEG` build flag to enable FFmpeg integration.
+
+First, you need to install required libraries:
+
+```bash
+# Debian/Ubuntu
+sudo apt install libavcodec-dev libavformat-dev libavutil-dev
+
+# RHEL/Fedora
+sudo dnf install libavcodec-free-devel libavformat-free-devel libavutil-free-devel
+```
+
+Then you can build the project as follows:
+
+```bash
+cmake -B build -D WHISPER_FFMPEG=yes
+cmake --build build
+```
+
+Run the following example to confirm it's working:
+
+```bash
+# Convert an audio file to Opus format
+ffmpeg -i samples/jfk.wav jfk.opus
+
+# Transcribe the audio file
+./build/bin/whisper-cli --model models/ggml-base.en.bin --file jfk.opus
+```
+
 ## Docker
 
 ### Prerequisites
@@ -388,8 +444,9 @@ Run the inference examples as usual, for example:
 
 We have two Docker images available for this project:
 
-1. `ghcr.io/ggerganov/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
-2. `ghcr.io/ggerganov/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
+1. `ghcr.io/ggml-org/whisper.cpp:main`: This image includes the main executable file as well as `curl` and `ffmpeg`. (platforms: `linux/amd64`, `linux/arm64`)
+2. `ghcr.io/ggml-org/whisper.cpp:main-cuda`: Same as `main` but compiled with CUDA support. (platforms: `linux/amd64`)
+3. `ghcr.io/ggml-org/whisper.cpp:main-musa`: Same as `main` but compiled with MUSA support. (platforms: `linux/amd64`)
 
 ### Usage
 
@@ -402,11 +459,11 @@ docker run -it --rm \
 docker run -it --rm \
   -v path/to/models:/models \
   -v path/to/audios:/audios \
-  whisper.cpp:main "./main -m /models/ggml-base.bin -f /audios/jfk.wav"
+  whisper.cpp:main "whisper-cli -m /models/ggml-base.bin -f /audios/jfk.wav"
 # transcribe an audio file in samples folder
 docker run -it --rm \
   -v path/to/models:/models \
-  whisper.cpp:main "./main -m /models/ggml-base.bin -f ./samples/jfk.wav"
+  whisper.cpp:main "whisper-cli -m /models/ggml-base.bin -f ./samples/jfk.wav"
 ```
 
 ## Installing with Conan
@@ -427,12 +484,12 @@ For detailed instructions on how to use Conan, please refer to the [Conan docume
 
 This is a naive example of performing real-time inference on audio from your microphone.
 The [stream](examples/stream) tool samples the audio every half a second and runs the transcription continuously.
-More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10). 
-You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly. 
+More info is available in [issue #10](https://github.com/ggml-org/whisper.cpp/issues/10).
+You will need to have [sdl2](https://wiki.libsdl.org/SDL2/Installation) installed for it to work properly.
 
 ```bash
 cmake -B build -DWHISPER_SDL2=ON
-cmake --build build --config Release
+cmake --build build -j --config Release
 ./build/bin/whisper-stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
 ```
 
@@ -516,7 +573,7 @@ main: processing './samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 pr
 
 ## Speaker segmentation via tinydiarize (experimental)
 
-More information about this approach is available here: https://github.com/ggerganov/whisper.cpp/pull/1058
+More information about this approach is available here: https://github.com/ggml-org/whisper.cpp/pull/1058
 
 Sample usage:
 
@@ -543,7 +600,7 @@ main: processing './samples/a13.wav' (480000 samples, 30.0 sec), 4 threads, 1 pr
 ## Karaoke-style movie generation (experimental)
 
 The [whisper-cli](examples/cli) example provides support for output of karaoke-style movies, where the
-currently pronounced word is highlighted. Use the `-wts` argument and run the generated bash script.
+currently pronounced word is highlighted. Use the `-owts` argument and run the generated bash script.
 This requires to have `ffmpeg` installed.
 
 Here are a few _"typical"_ examples:
@@ -580,7 +637,7 @@ https://user-images.githubusercontent.com/1991296/199337538-b7b0c7a3-2753-4a88-a
 
 ## Video comparison of different models
 
-Use the [scripts/bench-wts.sh](https://github.com/ggerganov/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
+Use the [scripts/bench-wts.sh](https://github.com/ggml-org/whisper.cpp/blob/master/scripts/bench-wts.sh) script to generate a video in the following format:
 
 ```bash
 ./scripts/bench-wts.sh samples/jfk.wav
@@ -597,7 +654,7 @@ In order to have an objective comparison of the performance of the inference acr
 use the [whisper-bench](examples/bench) tool. The tool simply runs the Encoder part of the model and prints how much time it
 took to execute it. The results are summarized in the following Github issue:
 
-[Benchmark results](https://github.com/ggerganov/whisper.cpp/issues/89)
+[Benchmark results](https://github.com/ggml-org/whisper.cpp/issues/89)
 
 Additionally a script to run whisper.cpp with different models and audio files is provided [bench.py](scripts/bench.py).
 
@@ -624,25 +681,24 @@ You can download the converted models using the [models/download-ggml-model.sh](
 or manually from here:
 
 - https://huggingface.co/ggerganov/whisper.cpp
-- https://ggml.ggerganov.com
 
 For more details, see the conversion script [models/convert-pt-to-ggml.py](models/convert-pt-to-ggml.py) or [models/README.md](models/README.md).
 
-## [Bindings](https://github.com/ggerganov/whisper.cpp/discussions/categories/bindings)
+## [Bindings](https://github.com/ggml-org/whisper.cpp/discussions/categories/bindings)
 
-- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggerganov/whisper.cpp/discussions/310)
-- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggerganov/whisper.cpp/discussions/309)
+- [x] Rust: [tazz4843/whisper-rs](https://github.com/tazz4843/whisper-rs) | [#310](https://github.com/ggml-org/whisper.cpp/discussions/310)
+- [x] JavaScript: [bindings/javascript](bindings/javascript) | [#309](https://github.com/ggml-org/whisper.cpp/discussions/309)
   - React Native (iOS / Android): [whisper.rn](https://github.com/mybigday/whisper.rn)
-- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggerganov/whisper.cpp/discussions/312)
+- [x] Go: [bindings/go](bindings/go) | [#312](https://github.com/ggml-org/whisper.cpp/discussions/312)
 - [x] Java:
   - [GiviMAD/whisper-jni](https://github.com/GiviMAD/whisper-jni)
-- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggerganov/whisper.cpp/discussions/507)
-- [x] Objective-C / Swift: [ggerganov/whisper.spm](https://github.com/ggerganov/whisper.spm) | [#313](https://github.com/ggerganov/whisper.cpp/discussions/313)
+- [x] Ruby: [bindings/ruby](bindings/ruby) | [#507](https://github.com/ggml-org/whisper.cpp/discussions/507)
+- [x] Objective-C / Swift: [ggml-org/whisper.spm](https://github.com/ggml-org/whisper.spm) | [#313](https://github.com/ggml-org/whisper.cpp/discussions/313)
   - [exPHAT/SwiftWhisper](https://github.com/exPHAT/SwiftWhisper)
-- [x] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
+- [x] .NET: | [#422](https://github.com/ggml-org/whisper.cpp/discussions/422)
   - [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
   - [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
-- [x] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
+- [x] Python: | [#9](https://github.com/ggml-org/whisper.cpp/issues/9)
   - [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
   - [AIWintermuteAI/whispercpp](https://github.com/AIWintermuteAI/whispercpp) (Updated fork of aarnphm/whispercpp)
   - [aarnphm/whispercpp](https://github.com/aarnphm/whispercpp) (Pybind11)
@@ -650,6 +706,118 @@ For more details, see the conversion script [models/convert-pt-to-ggml.py](model
 - [x] R: [bnosac/audio.whisper](https://github.com/bnosac/audio.whisper)
 - [x] Unity: [macoron/whisper.unity](https://github.com/Macoron/whisper.unity)
 
+## XCFramework
+The XCFramework is a precompiled version of the library for iOS, visionOS, tvOS,
+and macOS. It can be used in Swift projects without the need to compile the
+library from source. For example, the v1.7.5 version of the XCFramework can be
+used as follows:
+
+```swift
+// swift-tools-version: 5.10
+// The swift-tools-version declares the minimum version of Swift required to build this package.
+
+import PackageDescription
+
+let package = Package(
+    name: "Whisper",
+    targets: [
+        .executableTarget(
+            name: "Whisper",
+            dependencies: [
+                "WhisperFramework"
+            ]),
+        .binaryTarget(
+            name: "WhisperFramework",
+            url: "https://github.com/ggml-org/whisper.cpp/releases/download/v1.7.5/whisper-v1.7.5-xcframework.zip",
+            checksum: "c7faeb328620d6012e130f3d705c51a6ea6c995605f2df50f6e1ad68c59c6c4a"
+        )
+    ]
+)
+```
+
+## Voice Activity Detection (VAD)
+Support for Voice Activity Detection (VAD) can be enabled using the `--vad`
+argument to `whisper-cli`. In addition to this option a VAD model is also
+required.
+
+The way this works is that first the audio samples are passed through
+the VAD model which will detect speech segments. Using this information the
+only the speech segments that are detected are extracted from the original audio
+input and passed to whisper for processing. This reduces the amount of audio
+data that needs to be processed by whisper and can significantly speed up the
+transcription process.
+
+The following VAD models are currently supported:
+
+### Silero-VAD
+[Silero-vad](https://github.com/snakers4/silero-vad) is a lightweight VAD model
+written in Python that is fast and accurate.
+
+Models can be downloaded by running the following command on Linux or MacOS:
+```console
+$ ./models/download-vad-model.sh silero-v5.1.2
+Downloading ggml model silero-v5.1.2 from 'https://huggingface.co/ggml-org/whisper-vad' ...
+ggml-silero-v5.1.2.bin        100%[==============================================>] 864.35K  --.-KB/s    in 0.04s
+Done! Model 'silero-v5.1.2' saved in '/path/models/ggml-silero-v5.1.2.bin'
+You can now use it like this:
+
+  $ ./build/bin/whisper-cli -vm /path/models/ggml-silero-v5.1.2.bin --vad -f samples/jfk.wav -m models/ggml-base.en.bin
+
+```
+And the following command on Windows:
+```console
+> .\models\download-vad-model.cmd silero-v5.1.2
+Downloading vad model silero-v5.1.2...
+Done! Model silero-v5.1.2 saved in C:\Users\danie\work\ai\whisper.cpp\ggml-silero-v5.1.2.bin
+You can now use it like this:
+
+C:\path\build\bin\Release\whisper-cli.exe -vm C:\path\ggml-silero-v5.1.2.bin --vad -m models/ggml-base.en.bin -f samples\jfk.wav
+
+```
+
+To see a list of all available models, run the above commands without any
+arguments.
+
+This model can be also be converted manually to ggml using the following command:
+```console
+$ python3 -m venv venv && source venv/bin/activate
+$ (venv) pip install silero-vad
+$ (venv) $ python models/convert-silero-vad-to-ggml.py --output models/silero.bin
+Saving GGML Silero-VAD model to models/silero-v5.1.2-ggml.bin
+```
+And it can then be used with whisper as follows:
+```console
+$ ./build/bin/whisper-cli \
+   --file ./samples/jfk.wav \
+   --model ./models/ggml-base.en.bin \
+   --vad \
+   --vad-model ./models/silero-v5.1.2-ggml.bin
+```
+
+### VAD Options
+
+* --vad-threshold: Threshold probability for speech detection. A probability
+for a speech segment/frame above this threshold will be considered as speech.
+
+* --vad-min-speech-duration-ms: Minimum speech duration in milliseconds. Speech
+segments shorter than this value will be discarded to filter out brief noise or
+false positives.
+
+* --vad-min-silence-duration-ms: Minimum silence duration in milliseconds. Silence
+periods must be at least this long to end a speech segment. Shorter silence
+periods will be ignored and included as part of the speech.
+
+* --vad-max-speech-duration-s: Maximum speech duration in seconds. Speech segments
+longer than this will be automatically split into multiple segments at silence
+points exceeding 98ms to prevent excessively long segments.
+
+* --vad-speech-pad-ms: Speech padding in milliseconds. Adds this amount of padding
+before and after each detected speech segment to avoid cutting off speech edges.
+
+* --vad-samples-overlap: Amount of audio to extend from each speech segment into
+the next one, in seconds (e.g., 0.10 = 100ms overlap). This ensures speech isn't
+cut off abruptly between segments when they're concatenated together.
+
 ## Examples
 
 There are various examples of using the library for different projects in the [examples](examples) folder.
@@ -668,13 +836,13 @@ Some of the examples are even ported to run in the browser using WebAssembly. Ch
 | [whisper.android](examples/whisper.android)         |                                       | Android mobile application using whisper.cpp                                                                                    |
 | [whisper.nvim](examples/whisper.nvim)               |                                       | Speech-to-text plugin for Neovim                                                                                                |
 | [generate-karaoke.sh](examples/generate-karaoke.sh) |                                       | Helper script to easily [generate a karaoke video](https://youtu.be/uj7hVta4blM) of raw audio capture                           |
-| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggerganov/whisper.cpp/issues/185)                                           |
+| [livestream.sh](examples/livestream.sh)             |                                       | [Livestream audio transcription](https://github.com/ggml-org/whisper.cpp/issues/185)                                            |
 | [yt-wsp.sh](examples/yt-wsp.sh)                     |                                       | Download + transcribe and/or translate any VOD [(original)](https://gist.github.com/DaniruKun/96f763ec1a037cc92fe1a059b643b818) |
 | [wchess](examples/wchess)                           | [wchess.wasm](examples/wchess)        | Voice-controlled chess                                                                                                          |
 
-## [Discussions](https://github.com/ggerganov/whisper.cpp/discussions)
+## [Discussions](https://github.com/ggml-org/whisper.cpp/discussions)
 
 If you have any kind of feedback about this project feel free to use the Discussions section and open a new topic.
-You can use the [Show and tell](https://github.com/ggerganov/whisper.cpp/discussions/categories/show-and-tell) category
+You can use the [Show and tell](https://github.com/ggml-org/whisper.cpp/discussions/categories/show-and-tell) category
 to share your own projects that use `whisper.cpp`. If you have a question, make sure to check the
-[Frequently asked questions (#126)](https://github.com/ggerganov/whisper.cpp/discussions/126) discussion.
+[Frequently asked questions (#126)](https://github.com/ggml-org/whisper.cpp/discussions/126) discussion.

README_sycl.md

@@ -1,249 +1,249 @@
-# whisper.cpp for SYCL
-
-[Background](#background)
-
-[OS](#os)
-
-[Intel GPU](#intel-gpu)
-
-[Linux](#linux)
-
-[Environment Variable](#environment-variable)
-
-[Known Issue](#known-issue)
-
-[Todo](#todo)
-
-## Background
-
-SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators<EFBFBD>such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
-
-oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
-
-Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
-
-To avoid  re-inventing the wheel, this code refers other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel<EFBFBD> DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
-
-The whisper.cpp for SYCL is used to support Intel GPUs.
-
-For Intel CPU, recommend to use whisper.cpp for X86 (Intel MKL build).
-
-## OS
-
-|OS|Status|Verified|
-|-|-|-|
-|Linux|Support|Ubuntu 22.04|
-|Windows|Ongoing| |
-
-
-## Intel GPU
-
-|Intel GPU| Status | Verified Model|
-|-|-|-|
-|Intel Data Center Max Series| Support| Max 1550|
-|Intel Data Center Flex Series| Support| Flex 170|
-|Intel Arc Series| Support| Arc 770|
-|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
-|Intel iGPU| Support| iGPU in i5-1250P, i7-1165G7|
-
-
-## Linux
-
-### Setup Environment
-
-1. Install Intel GPU driver.
-
-a. Please install Intel GPU driver by official guide: [Install GPU Drivers](https://dgpu-docs.intel.com/driver/installation.html).
-
-Note: for iGPU, please install the client GPU driver.
-
-b. Add user to group: video, render.
-
-```
-sudo usermod -aG render username
-sudo usermod -aG video username
-```
-
-Note: re-login to enable it.
-
-c. Check
-
-```
-sudo apt install clinfo
-sudo clinfo -l
-```
-
-Output (example):
-
-```
-Platform #0: Intel(R) OpenCL Graphics
- `-- Device #0: Intel(R) Arc(TM) A770 Graphics
-
-
-Platform #0: Intel(R) OpenCL HD Graphics
- `-- Device #0: Intel(R) Iris(R) Xe Graphics [0x9a49]
-```
-
-2. Install Intel<EFBFBD> oneAPI Base toolkit.
-
-
-a. Please follow the procedure in [Get the Intel<EFBFBD> oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
-
-Recommend to install to default folder: **/opt/intel/oneapi**.
-
-Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
-
-b. Check
-
-```
-source /opt/intel/oneapi/setvars.sh
-
-sycl-ls
-```
-
-There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
-
-Output (example):
-```
-[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2  [2023.16.10.0.17_160000]
-[opencl:cpu:1] Intel(R) OpenCL, 13th Gen Intel(R) Core(TM) i7-13700K OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
-[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics OpenCL 3.0 NEO  [23.30.26918.50]
-[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26918]
-
-```
-
-2. Build locally:
-
-```
-mkdir -p build
-cd build
-source /opt/intel/oneapi/setvars.sh
-
-#for FP16
-#cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DWHISPER_SYCL_F16=ON 
-
-#for FP32
-cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
-
-#build example/main only
-#cmake --build . --config Release --target main
-
-#build all binary
-cmake --build . --config Release -v
-
-```
-
-or
-
-```
-./examples/sycl/build.sh
-```
-
-Note:
-
-- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
-
-### Run
-
-1. Put model file to folder **models**
-
-2. Enable oneAPI running environment
-
-```
-source /opt/intel/oneapi/setvars.sh
-```
-
-3. List device ID
-
-Run without parameter:
-
-```
-./build/bin/ls-sycl-device
-
-or
-
-./build/bin/main
-```
-
-Check the ID in startup log, like:
-
-```
-found 4 SYCL devices:
-  Device 0: Intel(R) Arc(TM) A770 Graphics,	compute capability 1.3,
-    max compute_units 512,	max work group size 1024,	max sub group size 32,	global mem size 16225243136
-  Device 1: Intel(R) FPGA Emulation Device,	compute capability 1.2,
-    max compute_units 24,	max work group size 67108864,	max sub group size 64,	global mem size 67065057280
-  Device 2: 13th Gen Intel(R) Core(TM) i7-13700K,	compute capability 3.0,
-    max compute_units 24,	max work group size 8192,	max sub group size 64,	global mem size 67065057280
-  Device 3: Intel(R) Arc(TM) A770 Graphics,	compute capability 3.0,
-    max compute_units 512,	max work group size 1024,	max sub group size 32,	global mem size 16225243136
-
-```
-
-|Attribute|Note|
-|-|-|
-|compute capability 1.3|Level-zero running time, recommended |
-|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
-
-4. Set device ID and execute whisper.cpp
-
-Set device ID = 0 by **GGML_SYCL_DEVICE=0**
-
-```
-GGML_SYCL_DEVICE=0 ./build/bin/main -m models/ggml-base.en.bin -f samples/jfk.wav
-```
-or run by script:
-
-```
-./examples/sycl/run_whisper.sh
-```
-
-
-
-5. Check the device ID in output
-
-Like:
-```
-Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
-```
-
-
-## Environment Variable
-
-#### Build
-
-|Name|Value|Function|
-|-|-|-|
-|WHISPER_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, WHISPER_SYCL=ON is mandatory.|
-|WHISPER_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path.For FP32, do not set it.|
-|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
-|CMAKE_CXX_COMPILER|icpx|use icpx for SYCL code path|
-
-#### Running
-
-
-|Name|Value|Function|
-|-|-|-|
-|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
-|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
-
-## Known Issue
-
-- Error:  `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
-
-  Miss to enable oneAPI running environment.
-
-  Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
-
-
-- Hang during startup
-
-  llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
-
-  Solution: add **--no-mmap**.
-
-## Todo
-
-- Support to build in Windows.
-
-- Support multiple cards.
+# whisper.cpp for SYCL
+
+[Background](#background)
+
+[OS](#os)
+
+[Intel GPU](#intel-gpu)
+
+[Linux](#linux)
+
+[Environment Variable](#environment-variable)
+
+[Known Issue](#known-issue)
+
+[Todo](#todo)
+
+## Background
+
+SYCL is a higher-level programming model to improve programming productivity on various hardware accelerators—such as CPUs, GPUs, and FPGAs. It is a single-source embedded domain-specific language based on pure C++17.
+
+oneAPI is a specification that is open and standards-based, supporting multiple architecture types including but not limited to GPU, CPU, and FPGA. The spec has both direct programming and API-based programming paradigms.
+
+Intel uses the SYCL as direct programming language to support CPU, GPUs and FPGAs.
+
+To avoid  re-inventing the wheel, this code refers other code paths in llama.cpp (like OpenBLAS, cuBLAS, CLBlast). We use a open-source tool [SYCLomatic](https://github.com/oneapi-src/SYCLomatic) (Commercial release [Intel® DPC++ Compatibility Tool](https://www.intel.com/content/www/us/en/developer/tools/oneapi/dpc-compatibility-tool.html)) migrate to SYCL.
+
+The whisper.cpp for SYCL is used to support Intel GPUs.
+
+For Intel CPU, recommend to use whisper.cpp for X86 (Intel MKL build).
+
+## OS
+
+|OS|Status|Verified|
+|-|-|-|
+|Linux|Support|Ubuntu 22.04|
+|Windows|Ongoing| |
+
+
+## Intel GPU
+
+|Intel GPU| Status | Verified Model|
+|-|-|-|
+|Intel Data Center Max Series| Support| Max 1550|
+|Intel Data Center Flex Series| Support| Flex 170|
+|Intel Arc Series| Support| Arc 770|
+|Intel built-in Arc GPU| Support| built-in Arc GPU in Meteor Lake|
+|Intel iGPU| Support| iGPU in i5-1250P, i7-1165G7|
+
+
+## Linux
+
+### Setup Environment
+
+1. Install Intel GPU driver.
+
+a. Please install Intel GPU driver by official guide: [Install GPU Drivers](https://dgpu-docs.intel.com/driver/installation.html).
+
+Note: for iGPU, please install the client GPU driver.
+
+b. Add user to group: video, render.
+
+```
+sudo usermod -aG render username
+sudo usermod -aG video username
+```
+
+Note: re-login to enable it.
+
+c. Check
+
+```
+sudo apt install clinfo
+sudo clinfo -l
+```
+
+Output (example):
+
+```
+Platform #0: Intel(R) OpenCL Graphics
+ `-- Device #0: Intel(R) Arc(TM) A770 Graphics
+
+
+Platform #0: Intel(R) OpenCL HD Graphics
+ `-- Device #0: Intel(R) Iris(R) Xe Graphics [0x9a49]
+```
+
+2. Install Intel® oneAPI Base toolkit.
+
+
+a. Please follow the procedure in [Get the Intel® oneAPI Base Toolkit ](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html).
+
+Recommend to install to default folder: **/opt/intel/oneapi**.
+
+Following guide use the default folder as example. If you use other folder, please modify the following guide info with your folder.
+
+b. Check
+
+```
+source /opt/intel/oneapi/setvars.sh
+
+sycl-ls
+```
+
+There should be one or more level-zero devices. Like **[ext_oneapi_level_zero:gpu:0]**.
+
+Output (example):
+```
+[opencl:acc:0] Intel(R) FPGA Emulation Platform for OpenCL(TM), Intel(R) FPGA Emulation Device OpenCL 1.2  [2023.16.10.0.17_160000]
+[opencl:cpu:1] Intel(R) OpenCL, 13th Gen Intel(R) Core(TM) i7-13700K OpenCL 3.0 (Build 0) [2023.16.10.0.17_160000]
+[opencl:gpu:2] Intel(R) OpenCL Graphics, Intel(R) Arc(TM) A770 Graphics OpenCL 3.0 NEO  [23.30.26918.50]
+[ext_oneapi_level_zero:gpu:0] Intel(R) Level-Zero, Intel(R) Arc(TM) A770 Graphics 1.3 [1.3.26918]
+
+```
+
+2. Build locally:
+
+```
+mkdir -p build
+cd build
+source /opt/intel/oneapi/setvars.sh
+
+#for FP16
+#cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DWHISPER_SYCL_F16=ON 
+
+#for FP32
+cmake .. -DWHISPER_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
+
+#build example/main only
+#cmake --build . --config Release --target main
+
+#build all binary
+cmake --build . --config Release -v
+
+```
+
+or
+
+```
+./examples/sycl/build.sh
+```
+
+Note:
+
+- By default, it will build for all binary files. It will take more time. To reduce the time, we recommend to build for **example/main** only.
+
+### Run
+
+1. Put model file to folder **models**
+
+2. Enable oneAPI running environment
+
+```
+source /opt/intel/oneapi/setvars.sh
+```
+
+3. List device ID
+
+Run without parameter:
+
+```
+./build/bin/ls-sycl-device
+
+or
+
+./build/bin/main
+```
+
+Check the ID in startup log, like:
+
+```
+found 4 SYCL devices:
+  Device 0: Intel(R) Arc(TM) A770 Graphics,	compute capability 1.3,
+    max compute_units 512,	max work group size 1024,	max sub group size 32,	global mem size 16225243136
+  Device 1: Intel(R) FPGA Emulation Device,	compute capability 1.2,
+    max compute_units 24,	max work group size 67108864,	max sub group size 64,	global mem size 67065057280
+  Device 2: 13th Gen Intel(R) Core(TM) i7-13700K,	compute capability 3.0,
+    max compute_units 24,	max work group size 8192,	max sub group size 64,	global mem size 67065057280
+  Device 3: Intel(R) Arc(TM) A770 Graphics,	compute capability 3.0,
+    max compute_units 512,	max work group size 1024,	max sub group size 32,	global mem size 16225243136
+
+```
+
+|Attribute|Note|
+|-|-|
+|compute capability 1.3|Level-zero running time, recommended |
+|compute capability 3.0|OpenCL running time, slower than level-zero in most cases|
+
+4. Set device ID and execute whisper.cpp
+
+Set device ID = 0 by **GGML_SYCL_DEVICE=0**
+
+```
+GGML_SYCL_DEVICE=0 ./build/bin/main -m models/ggml-base.en.bin -f samples/jfk.wav
+```
+or run by script:
+
+```
+./examples/sycl/run_whisper.sh
+```
+
+
+
+5. Check the device ID in output
+
+Like:
+```
+Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
+```
+
+
+## Environment Variable
+
+#### Build
+
+|Name|Value|Function|
+|-|-|-|
+|WHISPER_SYCL|ON (mandatory)|Enable build with SYCL code path. <br>For FP32/FP16, WHISPER_SYCL=ON is mandatory.|
+|WHISPER_SYCL_F16|ON (optional)|Enable FP16 build with SYCL code path.For FP32, do not set it.|
+|CMAKE_C_COMPILER|icx|Use icx compiler for SYCL code path|
+|CMAKE_CXX_COMPILER|icpx|use icpx for SYCL code path|
+
+#### Running
+
+
+|Name|Value|Function|
+|-|-|-|
+|GGML_SYCL_DEVICE|0 (default) or 1|Set the device id used. Check the device ids by default running output|
+|GGML_SYCL_DEBUG|0 (default) or 1|Enable log function by macro: GGML_SYCL_DEBUG|
+
+## Known Issue
+
+- Error:  `error while loading shared libraries: libsycl.so.7: cannot open shared object file: No such file or directory`.
+
+  Miss to enable oneAPI running environment.
+
+  Install oneAPI base toolkit and enable it by: `source /opt/intel/oneapi/setvars.sh`.
+
+
+- Hang during startup
+
+  llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
+
+  Solution: add **--no-mmap**.
+
+## Todo
+
+- Support to build in Windows.
+
+- Support multiple cards.

bindings/go/README.md

@@ -51,7 +51,7 @@ func main() {
 In order to build, you need to have the Go compiler installed. You can get it from [here](https://golang.org/dl/). Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/go
 make test
 ```
@@ -98,7 +98,7 @@ The API Documentation:
 
 Getting help:
 
-  * Follow the discussion for the go bindings [here](https://github.com/ggerganov/whisper.cpp/discussions/312)
+  * Follow the discussion for the go bindings [here](https://github.com/ggml-org/whisper.cpp/discussions/312)
 
 ## License
 

bindings/go/doc.go

@@ -1,5 +1,5 @@
 /*
-github.com/ggerganov/whisper.cpp/bindings/go
+github.com/ggml-org/whisper.cpp/bindings/go
 provides a speech-to-text service bindings for the Go programming language.
 */
 package whisper

bindings/java/README.md

@@ -23,26 +23,42 @@ import io.github.ggerganov.whispercpp.WhisperCpp;
 public class Example {
 
     public static void main(String[] args) {
+        
         WhisperCpp whisper = new WhisperCpp();
-        // By default, models are loaded from ~/.cache/whisper/ and are usually named "ggml-${name}.bin"
-        // or you can provide the absolute path to the model file.
-        long context = whisper.initContext("base.en");
         try {
-            var whisperParams = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
-            // custom configuration if required
-            whisperParams.temperature_inc = 0f;
+            // By default, models are loaded from ~/.cache/whisper/ and are usually named "ggml-${name}.bin"
+            // or you can provide the absolute path to the model file.
+            whisper.initContext("../ggml-base.en.bin"); 
+            WhisperFullParams.ByValue whisperParams = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH); 
             
-            var samples = readAudio(); // divide each value by 32767.0f
-            whisper.fullTranscribe(whisperParams, samples);
+            // custom configuration if required      
+            //whisperParams.n_threads = 8;
+            whisperParams.temperature = 0.0f;
+            whisperParams.temperature_inc = 0.2f;
+            //whisperParams.language = "en";
+                            
+            float[] samples = readAudio(); // divide each value by 32767.0f
+            List<WhisperSegment> whisperSegmentList = whisper.fullTranscribeWithTime(whisperParams, samples);
             
-            int segmentCount = whisper.getTextSegmentCount(context);
-            for (int i = 0; i < segmentCount; i++) {
-                String text = whisper.getTextSegment(context, i);
-                System.out.println(segment.getText());
+            for (WhisperSegment whisperSegment : whisperSegmentList) {
+
+                long start = whisperSegment.getStart();
+                long end = whisperSegment.getEnd();
+
+                String text = whisperSegment.getSentence();
+                    
+                System.out.println("start: "+start);
+                System.out.println("end: "+end);
+                System.out.println("text: "+text);
+                
             }
+    
+        } catch (IOException e) {
+            e.printStackTrace();
         } finally {
-             whisper.freeContext(context);
+            whisper.close();
         }
+        
      }
 }
 ```
@@ -52,7 +68,7 @@ public class Example {
 In order to build, you need to have the JDK 8 or higher installed. Run the tests with:
 
 ```bash
-git clone https://github.com/ggerganov/whisper.cpp.git
+git clone https://github.com/ggml-org/whisper.cpp.git
 cd whisper.cpp/bindings/java
 
 ./gradlew build

bindings/java/build.gradle

@@ -27,23 +27,41 @@ sourceSets {
 tasks.register('copyLibwhisperDynlib', Copy) {
     from '../../build/src'
     include 'libwhisper.dylib'
-    into 'build/generated/resources/main/darwin'
+    into 'build/generated/resources/main'
 }
 
 tasks.register('copyLibwhisperSo', Copy) {
     from '../../build/src'
     include 'libwhisper.so'
-    into 'build/generated/resources/main/linux-x86-64'
+    into 'build/generated/resources/main'
 }
 
-tasks.register('copyWhisperDll', Copy) {
-    from '../../build/Release'
+tasks.register('copyWhisperDLL', Copy) {
+    from '../../build/bin/Release'
     include 'whisper.dll'
-    into 'build/generated/resources/main/windows-x86-64'
+    into 'build/generated/resources/main'
+}
+
+tasks.register('copyGGML_BASE_DLL', Copy) {
+    from '../../build/bin/Release'
+    include 'ggml-base.dll'
+    into 'build/generated/resources/main'
+}
+
+tasks.register('copyGGML_DLL', Copy) {
+    from '../../build/bin/Release'
+    include 'ggml.dll'
+    into 'build/generated/resources/main'
+}
+
+tasks.register('copyGGML_CPU_DLL', Copy) {
+    from '../../build/bin/Release'
+    include 'ggml-cpu.dll'
+    into 'build/generated/resources/main'
 }
 
 tasks.register('copyLibs') {
-    dependsOn copyLibwhisperDynlib, copyLibwhisperSo, copyWhisperDll
+    dependsOn copyLibwhisperDynlib, copyLibwhisperSo, copyWhisperDLL, copyGGML_BASE_DLL, copyGGML_DLL, copyGGML_CPU_DLL
 }
 
 test {

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperCpp.java

@@ -168,23 +168,26 @@ public class WhisperCpp implements AutoCloseable {
         return str.toString().trim();
     }
 
-    public List<WhisperSegment> fullTranscribeWithTime(WhisperFullParams whisperParams, float[] audioData) throws IOException {
+    /**
+     * Full transcribe with time list.
+     *
+     * @param whisperParams the whisper params
+     * @param audioData     the audio data
+     * @return the list
+     * @throws IOException the io exception
+     */
+    public List<WhisperSegment> fullTranscribeWithTime(WhisperFullParams.ByValue whisperParams, float[] audioData) throws IOException {
         if (ctx == null) {
             throw new IllegalStateException("Model not initialised");
         }
 
-        WhisperFullParams.ByValue valueParams = new WhisperFullParams.ByValue(
-            lib.whisper_full_default_params_by_ref(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH.ordinal()));
-        valueParams.read();
-
-        if (lib.whisper_full(ctx, valueParams, audioData, audioData.length) != 0) {
+        if (lib.whisper_full(ctx, whisperParams, audioData, audioData.length) != 0) {
             throw new IOException("Failed to process audio");
         }
 
         int nSegments = lib.whisper_full_n_segments(ctx);
         List<WhisperSegment> segments= new ArrayList<>(nSegments);
 
-
         for (int i = 0; i < nSegments; i++) {
             long t0 = lib.whisper_full_get_segment_t0(ctx, i);
             String text = lib.whisper_full_get_segment_text(ctx, i);

bindings/java/src/main/java/io/github/ggerganov/whispercpp/WhisperCppJnaLibrary.java

@@ -9,6 +9,7 @@ import io.github.ggerganov.whispercpp.params.WhisperContextParams;
 import io.github.ggerganov.whispercpp.params.WhisperFullParams;
 
 public interface WhisperCppJnaLibrary extends Library {
+
     WhisperCppJnaLibrary instance = Native.load("whisper", WhisperCppJnaLibrary.class);
 
     String whisper_print_system_info();

bindings/java/src/test/java/io/github/ggerganov/whispercpp/WhisperCppTest.java

@@ -118,7 +118,7 @@ class WhisperCppTest {
         float[] floats = new float[b.length / 2];
 
         //WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_GREEDY);
-        WhisperFullParams params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
+        WhisperFullParams.ByValue params = whisper.getFullDefaultParams(WhisperSamplingStrategy.WHISPER_SAMPLING_BEAM_SEARCH);
         params.setProgressCallback((ctx, state, progress, user_data) -> System.out.println("progress: " + progress));
         params.print_progress = CBool.FALSE;
         //params.initial_prompt = "and so my fellow Americans um, like";

bindings/javascript/package.json

@@ -1,6 +1,6 @@
 {
   "name": "whisper.cpp",
-  "version": "1.7.4",
+  "version": "1.7.6",
   "description": "Whisper speech recognition",
   "main": "whisper.js",
   "scripts": {

bindings/ruby/.gitignore

@@ -1,3 +1,9 @@
 LICENSE
 pkg/
 lib/whisper.*
+ext/examples/
+ext/ggml/
+ext/include/
+ext/scripts/
+ext/src/
+test/fixtures/

bindings/ruby/README.md

@@ -16,6 +16,32 @@ If bundler is not being used to manage dependencies, install the gem by executin
 
     $ gem install whispercpp
 
+You can pass build options for whisper.cpp, for instance:
+
+    $ bundle config build.whispercpp --enable-ggml-cuda
+
+or,
+
+    $ gem install whispercpp -- --enable-ggml-cuda
+
+See whisper.cpp's [README](https://github.com/ggml-org/whisper.cpp/blob/master/README.md) for available options. You need convert options present the README to Ruby-style options, for example:
+
+Boolean options:
+
+* `-DGGML_BLAS=1` -> `--enable-ggml-blas`
+* `-DWHISER_COREML=OFF` -> `--disable-whisper-coreml`
+
+Argument options:
+
+* `-DGGML_CUDA_COMPRESSION_MODE=size` -> `--ggml-cuda-compression-mode=size`
+
+Combination:
+
+* `-DGGML_CUDA=1 -DCMAKE_CUDA_ARCHITECTURES="86"` -> `--enable-ggml-cuda --cmake_cuda-architectures="86"`
+
+For boolean options like `GGML_CUDA`, the README says `-DGGML_CUDA=1`. You need strip `-D`, prepend `--enable-` for `1` or `ON` (`--disable-` for `0` or `OFF`) and make it kebab-case: `--enable-ggml-cuda`.  
+For options which require arguments like `CMAKE_CUDA_ARCHITECTURES`, the README says `-DCMAKE_CUDA_ARCHITECTURES="86"`. You need strip `-D`, prepend `--`, make it kebab-case, append `=` and append argument: `--cmake-cuda-architectures="86"`.
+
 Usage
 -----
 
@@ -44,17 +70,6 @@ end
 
 Some models are prepared up-front:
 
-```ruby
-base_en = Whisper::Model.pre_converted_models["base.en"]
-whisper = Whisper::Context.new(base_en)
-```
-
-At first time you use a model, it is downloaded automatically. After that, downloaded cached file is used. To clear cache, call `#clear_cache`:
-
-```ruby
-Whisper::Model.pre_converted_models["base"].clear_cache
-```
-
 You also can use shorthand for pre-converted models:
 
 ```ruby
@@ -79,6 +94,19 @@ puts Whisper::Model.pre_converted_models.keys
 #   :
 ```
 
+You can also retrieve each model:
+
+```ruby
+base_en = Whisper::Model.pre_converted_models["base.en"]
+whisper = Whisper::Context.new(base_en)
+```
+
+At first time you use a model, it is downloaded automatically. After that, downloaded cached file is used. To clear cache, call `#clear_cache`:
+
+```ruby
+Whisper::Model.pre_converted_models["base"].clear_cache
+```
+
 You can also use local model files you prepared:
 
 ```ruby
@@ -99,9 +127,80 @@ See [models][] page for details.
 
 Currently, whisper.cpp accepts only 16-bit WAV files.
 
+### Voice Activity Detection (VAD) ###
+
+Support for Voice Activity Detection (VAD) can be enabled by setting `Whisper::Params`'s `vad` argument to `true` and specifying VAD model:
+
+```ruby
+Whisper::Params.new(
+  vad: true,
+  vad_model_path: "silero-v5.1.2",
+  # other arguments...
+)
+```
+
+When you pass the model name (`"silero-v5.1.2"`) or URI (`https://huggingface.co/ggml-org/whisper-vad/resolve/main/ggml-silero-v5.1.2.bin`), it will be downloaded automatically.
+Currently, "silero-v5.1.2" is registered as pre-converted model like ASR models. You also specify file path or URI of model.
+
+If you need configure VAD behavior, pass params for that:
+
+```ruby
+Whisper::Params.new(
+  vad: true,
+  vad_model_path: "silero-v5.1.2",
+  vad_params: Whisper::VAD::Params.new(
+    threshold: 1.0, # defaults to 0.5
+    min_speech_duration_ms: 500, # defaults to 250
+    min_silence_duration_ms: 200, # defaults to 100
+    max_speech_duration_s: 30000, # default is FLT_MAX,
+    speech_pad_ms: 50, # defaults to 30
+    samples_overlap: 0.5 # defaults to 0.1
+  ),
+  # other arguments...
+)
+```
+
+For details on VAD, see [whisper.cpp's README](https://github.com/ggml-org/whisper.cpp?tab=readme-ov-file#voice-activity-detection-vad).
+
+### Output ###
+
+whispercpp supports SRT and WebVTT output:
+
+```ruby
+puts whisper.transcribe("path/to/audio.wav", Whisper::Params.new).to_webvtt
+# =>
+WEBVTT
+
+1
+00:00:00.000 --> 00:00:03.860
+ My thought I have nobody by a beauty and will as you poured.
+
+2
+00:00:03.860 --> 00:00:09.840
+ Mr. Rochester is sub in that so-don't find simplest, and devoted about, to let might in
+
+3
+00:00:09.840 --> 00:00:09.940
+ a
+
+```
+
+You may call `#to_srt`, too
+
+
 API
 ---
 
+### Transcription ###
+
+By default, `Whisper::Context#transcribe` works in a single thread. You can make it work in parallel by passing `n_processors` option:
+
+```ruby
+whisper.transcribe("path/to/audio.wav", params, n_processors: Etc.nprocessors)
+```
+
+Note that transcription occasionally might be low accuracy when it works in parallel.
+
 ### Segments ###
 
 Once `Whisper::Context#transcribe` called, you can retrieve segments by `#each_segment`:
@@ -123,7 +222,7 @@ whisper
       ed: format_time(segment.end_time),
       text: segment.text
     }
-    line << " (speaker turned)" if segment.speaker_next_turn?
+    line << " (speaker turned)" if segment.speaker_turn_next?
     puts line
   end
 
@@ -139,7 +238,7 @@ params.on_new_segment do |segment|
     ed: format_time(segment.end_time),
     text: segment.text
   }
-  line << " (speaker turned)" if segment.speaker_next_turn?
+  line << " (speaker turned)" if segment.speaker_turn_next?
   puts line
 end
 
@@ -228,7 +327,7 @@ The second argument `samples` may be an array, an object with `length` and `each
 Development
 -----------
 
-    % git clone https://github.com/ggerganov/whisper.cpp.git
+    % git clone https://github.com/ggml-org/whisper.cpp.git
     % cd whisper.cpp/bindings/ruby
     % rake test
 
@@ -236,10 +335,15 @@ First call of `rake test` builds an extension and downloads a model for testing.
 
 If something seems wrong on build, running `rake clean` solves some cases.
 
+### Need help ###
+
+* Windows support
+* Refinement of C/C++ code, especially memory management
+
 License
 -------
 
 The same to [whisper.cpp][].
 
-[whisper.cpp]: https://github.com/ggerganov/whisper.cpp
-[models]: https://github.com/ggerganov/whisper.cpp/tree/master/models
+[whisper.cpp]: https://github.com/ggml-org/whisper.cpp
+[models]: https://github.com/ggml-org/whisper.cpp/tree/master/models

bindings/ruby/Rakefile

@@ -3,11 +3,15 @@ require "bundler/gem_tasks"
 require "rake/testtask"
 require_relative "extsources"
 
+SOURCES_DIR = "ext/sources"
+
 SOURCES = FileList[]
 
 EXTSOURCES.each do |src|
   basename = src.pathmap("%f")
-  dest = basename == "LICENSE" ? basename : src.pathmap("%{../..,ext}p")
+  dest = basename == "LICENSE" ? basename
+                               : src.pathmap("%{\\.\\./\\.\\.,#{SOURCES_DIR}}p")
+                                    .pathmap("%{\\.\\./javascript,#{SOURCES_DIR}/bindings/javascript}p")
   dir = dest.pathmap("%d")
   file src
   directory dir
@@ -18,7 +22,6 @@ EXTSOURCES.each do |src|
 end
 
 CLEAN.include SOURCES
-CLEAN.include FileList["ext/**/*.o", "ext/**/*.metal", "ext/**/*.tmp", "ext/whisper.{so,bundle,dll}"]
 
 SRC = FileList["ext/*.{c,cpp,h}"]
 
@@ -36,6 +39,20 @@ file "ext/Makefile" => SRC + ["ext/extconf.rb"] + SOURCES do |t|
     ruby "extconf.rb"
   end
 end
+if File.exist? "ext/Makefile"
+  task :make_clean do
+    cd "ext" do
+      sh "make", "clean"
+    end
+  end
+  task clean: :make_clean
+  task :make_distclean do
+    cd "ext" do
+      sh "make", "distclean"
+    end
+  end
+  task clobber: :make_distclean
+end
 
 file SO_FILE => "ext/Makefile" do |t|
   chdir "ext" do
@@ -50,17 +67,30 @@ file LIB_FILE => [SO_FILE, "lib"] do |t|
 end
 CLEAN.include LIB_FILE
 
-Rake::TestTask.new do |t|
-  t.test_files = FileList["tests/test_*.rb"]
+Rake::TestTask.new
+
+TEST_FIXTURE_AUDIO = "test/fixtures/jfk.wav"
+TEST_FIXTURE_AUDIO_SRC = File.expand_path(File.join(__dir__, "..", "..", "samples", "jfk.wav"))
+TEST_FIXTURE_AUDIO_DIR = TEST_FIXTURE_AUDIO.pathmap("%d")
+directory TEST_FIXTURE_AUDIO_DIR
+if File.exist? TEST_FIXTURE_AUDIO_SRC
+  file TEST_FIXTURE_AUDIO => [TEST_FIXTURE_AUDIO_SRC, TEST_FIXTURE_AUDIO_DIR] do |t|
+    symlink t.source, t.name
+  end
+else
+  require "open-uri"
+  file TEST_FIXTURE_AUDIO => TEST_FIXTURE_AUDIO_DIR do |t|
+    File.write t.name, URI("https://github.com/ggml-org/whisper.cpp/raw/refs/heads/master/samples/jfk.wav").read
+  end
 end
 
-TEST_MEMORY_VIEW = "tests/jfk_reader/jfk_reader.#{RbConfig::CONFIG['DLEXT']}"
-file TEST_MEMORY_VIEW => "tests/jfk_reader/jfk_reader.c" do |t|
-  chdir "tests/jfk_reader" do
+TEST_MEMORY_VIEW = "test/jfk_reader/jfk_reader.#{RbConfig::CONFIG['DLEXT']}"
+file TEST_MEMORY_VIEW => "test/jfk_reader/jfk_reader.c" do |t|
+  chdir "test/jfk_reader" do
     ruby "extconf.rb"
     sh "make"
   end
 end
-CLEAN.include "tests/jfk_reader/jfk_reader.{o,#{RbConfig::CONFIG['DLEXT']}}"
+CLEAN.include TEST_MEMORY_VIEW
 
-task test: [LIB_FILE, TEST_MEMORY_VIEW]
+task test: [LIB_FILE, TEST_MEMORY_VIEW, TEST_FIXTURE_AUDIO]

bindings/ruby/ext/.gitignore

@@ -2,10 +2,8 @@ Makefile
 whisper.so
 whisper.bundle
 whisper.dll
-scripts/get-flags.mk
 *.o
-/*/**/*.c
-/*/**/*.cpp
-/*/**/*.h
-/*/**/*.m
-/*/**/*.metal
+*.a
+sources/*
+!sources/CMakeGraphVizOptions.cmake
+mkmf.log

bindings/ruby/ext/cpu.mk

@@ -1,13 +0,0 @@
-ggml/src/ggml-cpu/ggml-cpu-cpp.o: \
-	ggml/src/ggml-cpu/ggml-cpu.cpp \
-	ggml/src/ggml-cpu/unary-ops.cpp \
-	ggml/src/ggml-cpu/binary-ops.cpp \
-	ggml/src/ggml-cpu/vec.cpp \
-	ggml/src/ggml-cpu/ops.cpp \
-	ggml/include/ggml-backend.h \
-	ggml/include/ggml.h \
-	ggml/include/ggml-alloc.h \
-	ggml/src/ggml-backend-impl.h \
-	ggml/include/ggml-cpu.h \
-	ggml/src/ggml-impl.h
-	$(CXX) $(CXXFLAGS)   -c $< -o $@

bindings/ruby/ext/dependencies.rb

@@ -0,0 +1,73 @@
+require "tsort"
+
+class Dependencies
+  include TSort
+
+  def initialize(cmake, options)
+    @cmake = cmake
+    @options = options
+    @static_lib_shape = nil
+    @nodes = {}
+    @graph = Hash.new {|h, k| h[k] = []}
+
+    generate_dot
+    parse_dot
+  end
+
+  def libs
+    tsort.filter_map {|node|
+      label, shape = @nodes[node]
+      if shape == @static_lib_shape
+        label.gsub(/\\n\([^)]+\)/, '')
+      else
+        nil
+      end
+    }.reverse.collect {|lib| "lib#{lib}.a"}
+  end
+
+  def to_s
+    libs.join(" ")
+  end
+
+  private
+
+  def dot_path
+    File.join(__dir__, "build", "whisper.cpp.dot")
+  end
+
+  def generate_dot
+    args = ["-S", "sources", "-B", "build", "--graphviz", dot_path, "-D", "BUILD_SHARED_LIBS=OFF"]
+    args << @options.to_s unless @options.to_s.empty?
+    system @cmake, *args, exception: true
+  end
+
+  def parse_dot
+    File.open(dot_path).each_line do |line|
+      case line
+      when /\[\s*label\s*=\s*"Static Library"\s*,\s*shape\s*=\s*(?<shape>\w+)\s*\]/
+        @static_lib_shape = $~[:shape]
+      when /\A\s*"(?<node>\w+)"\s*\[\s*label\s*=\s*"(?<label>\S+)"\s*,\s*shape\s*=\s*(?<shape>\w+)\s*\]\s*;\s*\z/
+        node = $~[:node]
+        label = $~[:label]
+        shape = $~[:shape]
+        @nodes[node] = [label, shape]
+      when /\A\s*"(?<depender>\w+)"\s*->\s*"(?<dependee>\w+)"/
+        depender = $~[:depender]
+        dependee = $~[:dependee]
+        @graph[depender] << dependee
+      end
+    end
+  end
+
+  def tsort_each_node
+    @nodes.each_key do |node|
+      yield node
+    end
+  end
+
+  def tsort_each_child(node)
+    @graph[node].each do |child|
+      yield child
+    end
+  end
+end

bindings/ruby/ext/extconf.rb

@@ -1,212 +1,22 @@
-require 'mkmf'
+require "mkmf"
+require_relative "options"
+require_relative "dependencies"
 
-# need to use c++ compiler flags
-$CXXFLAGS << ' -std=c++17'
+cmake = find_executable("cmake") || abort
+options = Options.new(cmake)
+have_library("gomp") rescue nil
+libs = Dependencies.new(cmake, options)
 
-$LDFLAGS << ' -lstdc++'
+$INCFLAGS << " -Isources/include -Isources/ggml/include -Isources/examples"
+$LOCAL_LIBS << " #{libs}"
+$cleanfiles << " build #{libs}"
 
-# Set to true when building binary gems
-if enable_config('static-stdlib', false)
-  $LDFLAGS << ' -static-libgcc -static-libstdc++'
-end
-
-if enable_config('march-tune-native', false)
-  $CFLAGS << ' -march=native -mtune=native'
-  $CXXFLAGS << ' -march=native -mtune=native'
-end
-
-if ENV['WHISPER_METAL']
-  $GGML_METAL ||= true
-  $DEPRECATE_WARNING ||= true
-end
-
-$UNAME_S = `uname -s`.chomp
-$UNAME_P = `uname -p`.chomp
-$UNAME_M = `uname -m`.chomp
-
-if $UNAME_S == 'Darwin'
-  unless ENV['GGML_NO_METAL']
-    $GGML_METAL ||= true
-  end
-  $GGML_NO_OPENMP ||= true
-end
-
-if $GGML_METAL
-  $GGML_METAL_EMBED_LIBRARY = true
-end
-
-$MK_CPPFLAGS = '-Iggml/include -Iggml/src -Iggml/src/ggml-cpu -Iinclude -Isrc -Iexamples -DGGML_USE_CPU'
-$MK_CFLAGS   = '-std=c11   -fPIC'
-$MK_CXXFLAGS = '-std=c++17 -fPIC'
-$MK_NVCCFLAGS = '-std=c++17'
-$MK_LDFLAGS = ''
-
-$OBJ_GGML = []
-$OBJ_WHISPER = []
-$OBJ_COMMON = []
-$OBJ_SDL = []
-
-$MK_CPPFLAGS << ' -D_XOPEN_SOURCE=600'
-
-if $UNAME_S == 'Linux'
-  $MK_CPPFLAGS << ' -D_GNU_SOURCE'
-end
-
-if $UNAME_S == 'Darwin'
-  $MK_CPPFLAGS << ' -D_DARWIN_C_SOURCE'
-end
-
-if ENV['WHISPER_DEBUG']
-  $MK_CFLAGS    << ' -O0 -g'
-  $MK_CXXFLAGS  << ' -O0 -g'
-  $MK_LDFLAGS   << ' -g'
-  $MK_NVCCFLAGS << ' -O0 -g'
-else
-  $MK_CPPFLAGS   << ' -DNDEBUG'
-  $MK_CFLAGS     << ' -O3'
-  $MK_CXXFLAGS   << ' -O3'
-  $MK_NVCCFLAGS  << ' -O3'
-end
-
-$WARN_FLAGS =
-  ' -Wall' <<
-  ' -Wextra' <<
-  ' -Wpedantic' <<
-  ' -Wcast-qual' <<
-  ' -Wno-unused-function'
-
-$MK_CFLAGS <<
-  $WARN_FLAGS <<
-  ' -Wshadow' <<
-  ' -Wstrict-prototypes' <<
-  ' -Wpointer-arith' <<
-  ' -Wmissing-prototypes' <<
-  ' -Werror=implicit-int' <<
-  ' -Werror=implicit-function-declaration'
-
-$MK_CXXFLAGS <<
-  $WARN_FLAGS <<
-  ' -Wmissing-declarations' <<
-  ' -Wmissing-noreturn'
-
-unless `#{cc_command} #{$LDFLAGS} -Wl,-v 2>&1`.chomp.include? 'dyld-1015.7'
-  $MK_CPPFLAGS << ' -DHAVE_BUGGY_APPLE_LINKER'
-end
-
-if %w[Linux Darwin FreeBSD NetBSD OpenBSD Haiku].include? $UNAME_S
-  $MK_CFLAGS   << ' -pthread'
-  $MK_CXXFLAGS << ' -pthread'
-end
-
-unless $_WIN32
-  $DSO_EXT = '.so'
-else
-  $DSO_EXT = '.dll'
-end
-
-unless ENV['RISCV']
-  if %w[x86_64 i686 amd64].include? $UNAME_M
-    $HOST_CXXFLAGS ||= ''
-
-    $MK_CFLAGS     << ' -march=native -mtune=native'
-    $HOST_CXXFLAGS << ' -march=native -mtune=native'
-  end
-else
-  $MK_CFLAGS   << ' -march=rv64gcv -mabi=lp64d'
-  $MK_CXXFLAGS << ' -march=rv64gcv -mabi=lp64d'
-end
-
-unless ENV['GGML_NO_ACCELERATE']
-  if $UNAME_S == 'Darwin'
-    $MK_CPPFLAGS << ' -DGGML_USE_ACCELERATE -DGGML_USE_BLAS -DGGML_BLAS_USE_ACCELERATE'
-    $MK_CPPFLAGS << ' -DACCELERATE_NEW_LAPACK'
-    $MK_CPPFLAGS << ' -DACCELERATE_LAPACK_ILP64'
-    $MK_LDFLAGS  << ' -framework Accelerate'
-    $OBJ_GGML    << 'ggml/src/ggml-blas/ggml-blas.o'
-  end
-end
-
-if ENV['GGML_OPENBLAS']
-  $MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas`.chomp}"
-  $MK_CFLAGS   << " #{`pkg-config --cflags-only-other openblas)`.chomp}"
-  $MK_LDFLAGS  << " #{`pkg-config --libs openblas`}"
-  $OBJ_GGML    << 'ggml/src/ggml-blas/ggml-blas.o'
-end
-
-if ENV['GGML_OPENBLAS64']
-  $MK_CPPFLAGS << " -DGGML_USE_BLAS #{`pkg-config --cflags-only-I openblas64`.chomp}"
-  $MK_CFLAGS   << " #{`pkg-config --cflags-only-other openblas64)`.chomp}"
-  $MK_LDFLAGS  << " #{`pkg-config --libs openblas64`}"
-  $OBJ_GGML    << 'ggml/src/ggml-blas/ggml-blas.o'
-end
-
-if $GGML_METAL
-  $MK_CPPFLAGS << ' -DGGML_USE_METAL'
-  $MK_LDFLAGS  << ' -framework Foundation -framework Metal -framework MetalKit'
-  $OBJ_GGML    << 'ggml/src/ggml-metal/ggml-metal.o'
-
-  if ENV['GGML_METAL_NDEBUG']
-    $MK_CPPFLAGS << ' -DGGML_METAL_NDEBUG'
-  end
-
-  if $GGML_METAL_EMBED_LIBRARY
-    $MK_CPPFLAGS << ' -DGGML_METAL_EMBED_LIBRARY'
-    $OBJ_GGML    << 'ggml/src/ggml-metal/ggml-metal-embed.o'
-  end
-end
-
-$OBJ_GGML <<
-  'ggml/src/ggml.o' <<
-  'ggml/src/ggml-alloc.o' <<
-  'ggml/src/ggml-backend.o' <<
-  'ggml/src/ggml-backend-reg.o' <<
-  'ggml/src/ggml-opt.o' <<
-  'ggml/src/ggml-quants.o' <<
-  'ggml/src/ggml-threading.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-cpp.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-aarch64.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-hbm.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-quants.o' <<
-  'ggml/src/ggml-cpu/ggml-cpu-traits.o' <<
-  'ggml/src/ggml-cpu/unary-ops.o' <<
-  'ggml/src/ggml-cpu/binary-ops.o' <<
-  'ggml/src/ggml-cpu/vec.o' <<
-  'ggml/src/ggml-cpu/ops.o'
-
-$OBJ_WHISPER <<
-  'src/whisper.o' <<
-  'examples/common.o' <<
-  'examples/common-whisper.o'
-
-$objs = $OBJ_GGML + $OBJ_WHISPER + $OBJ_COMMON + $OBJ_SDL
-$objs <<
-  "ruby_whisper.o" <<
-  "ruby_whisper_context.o" <<
-  "ruby_whisper_transcribe.o" <<
-  "ruby_whisper_params.o" <<
-  "ruby_whisper_error.o" <<
-  "ruby_whisper_segment.o" <<
-  "ruby_whisper_model.o"
-
-$CPPFLAGS  = "#{$MK_CPPFLAGS} #{$CPPFLAGS}"
-$CFLAGS    = "#{$CPPFLAGS} #{$MK_CFLAGS} #{$GF_CFLAGS} #{$CFLAGS}"
-$BASE_CXXFLAGS = "#{$MK_CXXFLAGS} #{$CXXFLAGS}"
-$CXXFLAGS  = "#{$BASE_CXXFLAGS} #{$HOST_CXXFLAGS} #{$GF_CXXFLAGS} #{$CPPFLAGS}"
-$NVCCFLAGS = "#{$MK_NVCCFLAGS} #{$NVCCFLAGS}"
-$LDFLAGS   = "#{$MK_LDFLAGS} #{$LDFLAGS}"
-
-create_makefile('whisper')
-
-File.open 'Makefile', 'a' do |file|
-  file.puts 'include scripts/get-flags.mk'
-  file.puts 'include cpu.mk'
-
-  if $GGML_METAL
-    file.puts 'include metal.mk'
-
-    if $GGML_METAL_EMBED_LIBRARY
-      file.puts 'include metal-embed.mk'
-    end
-  end
+create_makefile "whisper" do |conf|
+  conf << <<~EOF
+    $(TARGET_SO): #{libs}
+    #{libs}: cmake-targets
+    cmake-targets:
+    #{"\t"}#{cmake} -S sources -B build -D BUILD_SHARED_LIBS=OFF -D CMAKE_ARCHIVE_OUTPUT_DIRECTORY=#{__dir__} -D CMAKE_POSITION_INDEPENDENT_CODE=ON #{options}
+    #{"\t"}#{cmake} --build build --config Release --target common whisper
+  EOF
 end

bindings/ruby/ext/metal-embed.mk

@@ -1,17 +0,0 @@
-ggml/src/ggml-metal/ggml-metal-embed.o: \
-	ggml/src/ggml-metal/ggml-metal.metal \
-	ggml/src/ggml-metal/ggml-metal-impl.h \
-	ggml/src/ggml-common.h
-	@echo "Embedding Metal library"
-	@sed -e '/__embed_ggml-common.h__/r      ggml/src/ggml-common.h'                -e '/__embed_ggml-common.h__/d'      < ggml/src/ggml-metal/ggml-metal.metal           > ggml/src/ggml-metal/ggml-metal-embed.metal.tmp
-	@sed -e '/#include "ggml-metal-impl.h"/r ggml/src/ggml-metal/ggml-metal-impl.h' -e '/#include "ggml-metal-impl.h"/d' < ggml/src/ggml-metal/ggml-metal-embed.metal.tmp > ggml/src/ggml-metal/ggml-metal-embed.metal
-	$(eval TEMP_ASSEMBLY=$(shell mktemp -d))
-	@echo ".section __DATA, __ggml_metallib"                       >  $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	@echo ".globl _ggml_metallib_start"                            >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	@echo "_ggml_metallib_start:"                                  >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	@echo ".incbin \"ggml/src/ggml-metal/ggml-metal-embed.metal\"" >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	@echo ".globl _ggml_metallib_end"                              >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	@echo "_ggml_metallib_end:"                                    >> $(TEMP_ASSEMBLY)/ggml-metal-embed.s
-	$(CC) $(CFLAGS) -c $(TEMP_ASSEMBLY)/ggml-metal-embed.s -o $@
-	@rm -f ${TEMP_ASSEMBLY}/ggml-metal-embed.s
-	@rmdir ${TEMP_ASSEMBLY}

bindings/ruby/ext/metal.mk

@@ -1,6 +0,0 @@
-ggml/src/ggml-metal/ggml-metal.o: \
-	ggml/src/ggml-metal/ggml-metal.m \
-	ggml/src/ggml-metal/ggml-metal-impl.h \
-	ggml/include/ggml-metal.h \
-	ggml/include/ggml.h
-	$(CC) $(CFLAGS) -c $< -o $@

bindings/ruby/ext/options.rb

@@ -0,0 +1,85 @@
+class Options
+  def initialize(cmake="cmake")
+    @cmake = cmake
+    @options = {}
+
+    configure
+  end
+
+  def to_s
+    @options
+      .reject {|name, (type, value)| value.nil?}
+      .collect {|name, (type, value)| "-D #{name}=#{value == true ? "ON" : value == false ? "OFF" : value.shellescape}"}
+      .join(" ")
+  end
+
+  def cmake_options
+    return @cmake_options if @cmake_options
+
+    output = nil
+    Dir.chdir __dir__ do
+      output = `#{@cmake.shellescape} -S sources -B build -L`
+    end
+    @cmake_options = output.lines.drop_while {|line| line.chomp != "-- Cache values"}.drop(1)
+                       .filter_map {|line|
+                         option, value = line.chomp.split("=", 2)
+                         name, type = option.split(":", 2)
+                         [
+                           name,
+                           [
+                             type,
+                             type == "BOOL" ? value == "ON" : value
+                           ]
+                         ]
+                       }.to_h
+  end
+
+  private
+
+  def configure
+    cmake_options.each_pair do |name, (type, default_value)|
+      option = option_name(name)
+      value = type == "BOOL" ? enable_config(option) : arg_config("--#{option}")
+      @options[name] = [type, value]
+    end
+
+    configure_accelerate
+    configure_metal
+    configure_coreml
+  end
+
+  # See ggml/src/ggml-cpu/CMakeLists.txt
+  def configure_accelerate
+    if RUBY_PLATFORM.match?(/darwin/) && enabled?("GGML_ACCELERATE")
+      $LDFLAGS << " -framework Accelerate"
+    end
+  end
+
+  # See ggml/src/ggml-metal/CMakeLists.txt
+  def configure_metal
+    $LDFLAGS << " -framework Foundation -framework Metal -framework MetalKit" if enabled?("GGML_METAL")
+  end
+
+  # See src/CmakeLists.txt
+  def configure_coreml
+    if enabled?("WHISPER_COREML")
+      $LDFLAGS << " -framework Foundation -framework CoreML"
+      $defs << "-DRUBY_WHISPER_USE_COREML"
+    end
+  end
+
+  def option_name(name)
+    name.downcase.gsub("_", "-")
+  end
+
+  def enabled?(option)
+    op = @options[option]
+    raise "Option not exist: #{option}" unless op
+    raise "Option not boolean: #{option}(#{op[0]})" unless op[0] == "BOOL"
+    if op[1].nil?
+      cmake_options[option][1]
+    else
+      op[1]
+    end
+  end
+end

bindings/ruby/ext/ruby_whisper.c

@@ -3,8 +3,10 @@
 #include "ruby_whisper.h"
 
 VALUE mWhisper;
+VALUE mVAD;
 VALUE cContext;
 VALUE cParams;
+VALUE cVADParams;
 VALUE eError;
 
 VALUE cSegment;
@@ -20,6 +22,9 @@ ID id_new;
 ID id_to_path;
 ID id_URI;
 ID id_pre_converted_models;
+ID id_coreml_compiled_models;
+ID id_cache;
+ID id_n_processors;
 
 static bool is_log_callback_finalized = false;
 
@@ -31,6 +36,7 @@ extern void init_ruby_whisper_params(VALUE *mWhisper);
 extern void init_ruby_whisper_error(VALUE *mWhisper);
 extern void init_ruby_whisper_segment(VALUE *mWhisper, VALUE *cSegment);
 extern void init_ruby_whisper_model(VALUE *mWhisper);
+extern void init_ruby_whisper_vad_params(VALUE *mVAD);
 extern void register_callbacks(ruby_whisper_params *rwp, VALUE *context);
 
 /*
@@ -80,6 +86,14 @@ static VALUE ruby_whisper_s_lang_str_full(VALUE self, VALUE id) {
   return rb_str_new2(str_full);
 }
 
+/*
+ * call-seq:
+ *   system_info_str -> String
+ */
+static VALUE ruby_whisper_s_system_info_str(VALUE self) {
+  return rb_str_new2(whisper_print_system_info());
+}
+
 static VALUE ruby_whisper_s_finalize_log_callback(VALUE self, VALUE id) {
   is_log_callback_finalized = true;
   return Qnil;
@@ -116,16 +130,6 @@ static VALUE ruby_whisper_s_log_set(VALUE self, VALUE log_callback, VALUE user_d
   return Qnil;
 }
 
-static void rb_whisper_model_mark(ruby_whisper_model *rwm) {
-  rb_gc_mark(rwm->context);
-}
-
-static VALUE ruby_whisper_model_allocate(VALUE klass) {
-  ruby_whisper_model *rwm;
-  rwm = ALLOC(ruby_whisper_model);
-  return Data_Wrap_Struct(klass, rb_whisper_model_mark, RUBY_DEFAULT_FREE, rwm);
-}
-
 void Init_whisper() {
   id_to_s = rb_intern("to_s");
   id_call = rb_intern("call");
@@ -137,9 +141,14 @@ void Init_whisper() {
   id_to_path = rb_intern("to_path");
   id_URI = rb_intern("URI");
   id_pre_converted_models = rb_intern("pre_converted_models");
+  id_coreml_compiled_models = rb_intern("coreml_compiled_models");
+  id_cache = rb_intern("cache");
+  id_n_processors = rb_intern("n_processors");
 
   mWhisper = rb_define_module("Whisper");
+  mVAD = rb_define_module_under(mWhisper, "VAD");
 
+  rb_define_const(mWhisper, "VERSION", rb_str_new2(whisper_version()));
   rb_define_const(mWhisper, "LOG_LEVEL_NONE", INT2NUM(GGML_LOG_LEVEL_NONE));
   rb_define_const(mWhisper, "LOG_LEVEL_INFO", INT2NUM(GGML_LOG_LEVEL_INFO));
   rb_define_const(mWhisper, "LOG_LEVEL_WARN", INT2NUM(GGML_LOG_LEVEL_WARN));
@@ -151,6 +160,7 @@ void Init_whisper() {
   rb_define_singleton_method(mWhisper, "lang_id", ruby_whisper_s_lang_id, 1);
   rb_define_singleton_method(mWhisper, "lang_str", ruby_whisper_s_lang_str, 1);
   rb_define_singleton_method(mWhisper, "lang_str_full", ruby_whisper_s_lang_str_full, 1);
+  rb_define_singleton_method(mWhisper, "system_info_str", ruby_whisper_s_system_info_str, 0);
   rb_define_singleton_method(mWhisper, "log_set", ruby_whisper_s_log_set, 2);
   rb_define_private_method(rb_singleton_class(mWhisper), "finalize_log_callback", ruby_whisper_s_finalize_log_callback, 1);
 
@@ -159,6 +169,9 @@ void Init_whisper() {
   init_ruby_whisper_error(&mWhisper);
   init_ruby_whisper_segment(&mWhisper, &cContext);
   init_ruby_whisper_model(&mWhisper);
+  init_ruby_whisper_vad_params(&mVAD);
 
+  rb_require("whisper/context");
+  rb_require("whisper/segment");
   rb_require("whisper/model/uri");
 }

bindings/ruby/ext/ruby_whisper.h

@@ -19,9 +19,15 @@ typedef struct {
   bool diarize;
   ruby_whisper_callback_container *new_segment_callback_container;
   ruby_whisper_callback_container *progress_callback_container;
+  ruby_whisper_callback_container *encoder_begin_callback_container;
   ruby_whisper_callback_container *abort_callback_container;
+  VALUE vad_params;
 } ruby_whisper_params;
 
+typedef struct {
+  struct whisper_vad_params params;
+} ruby_whisper_vad_params;
+
 typedef struct {
   VALUE context;
   int index;

bindings/ruby/ext/ruby_whisper_context.c

@@ -11,15 +11,21 @@ extern ID id_new;
 extern ID id_to_path;
 extern ID id_URI;
 extern ID id_pre_converted_models;
+extern ID id_coreml_compiled_models;
+extern ID id_cache;
+extern ID id_n_processors;
 
 extern VALUE cContext;
 extern VALUE eError;
 extern VALUE cModel;
 
+extern const rb_data_type_t ruby_whisper_params_type;
 extern VALUE ruby_whisper_transcribe(int argc, VALUE *argv, VALUE self);
-extern VALUE rb_whisper_model_initialize(VALUE context);
-extern VALUE rb_whisper_segment_initialize(VALUE context, int index);
-extern void register_callbacks(ruby_whisper_params *rwp, VALUE *context);
+extern VALUE rb_whisper_model_s_new(VALUE context);
+extern VALUE rb_whisper_segment_s_new(VALUE context, int index);
+extern void prepare_transcription(ruby_whisper_params *rwp, VALUE *context);
+
+ID transcribe_option_names[1];
 
 static void
 ruby_whisper_free(ruby_whisper *rw)
@@ -37,19 +43,74 @@ rb_whisper_mark(ruby_whisper *rw)
 }
 
 void
-rb_whisper_free(ruby_whisper *rw)
+rb_whisper_free(void *p)
 {
+  ruby_whisper *rw = (ruby_whisper *)p;
   ruby_whisper_free(rw);
   free(rw);
 }
 
+static size_t
+ruby_whisper_memsize(const void *p)
+{
+  const ruby_whisper *rw = (const ruby_whisper *)p;
+  size_t size = sizeof(rw);
+  if (!rw) {
+    return 0;
+  }
+  if (rw->context) {
+    size += sizeof(rw->context);
+  }
+  return size;
+}
+
+const rb_data_type_t ruby_whisper_type = {
+  "ruby_whisper",
+  {0, rb_whisper_free, ruby_whisper_memsize,},
+  0, 0,
+  0
+};
+
 static VALUE
 ruby_whisper_allocate(VALUE klass)
 {
   ruby_whisper *rw;
-  rw = ALLOC(ruby_whisper);
+  VALUE obj = TypedData_Make_Struct(klass, ruby_whisper, &ruby_whisper_type, rw);
   rw->context = NULL;
-  return Data_Wrap_Struct(klass, rb_whisper_mark, rb_whisper_free, rw);
+  return obj;
+}
+
+VALUE
+ruby_whisper_normalize_model_path(VALUE model_path)
+{
+  VALUE pre_converted_models = rb_funcall(cModel, id_pre_converted_models, 0);
+  VALUE pre_converted_model = rb_hash_aref(pre_converted_models, model_path);
+  if (!NIL_P(pre_converted_model)) {
+    model_path = pre_converted_model;
+#ifdef RUBY_WHISPER_USE_COREML
+    VALUE coreml_converted_models = rb_funcall(cModel, id_coreml_compiled_models, 0);
+    VALUE coreml_converted_model = rb_hash_aref(coreml_converted_models, pre_converted_model);
+    if (!NIL_P(coreml_converted_model)) {
+      rb_funcall(coreml_converted_model, id_cache, 0);
+    }
+#endif
+  }
+  else if (TYPE(model_path) == T_STRING) {
+    const char * model_path_str = StringValueCStr(model_path);
+    if (strncmp("http://", model_path_str, 7) == 0 || strncmp("https://", model_path_str, 8) == 0) {
+      VALUE uri_class = rb_const_get(cModel, id_URI);
+      model_path = rb_class_new_instance(1, &model_path, uri_class);
+    }
+  }
+  else if (rb_obj_is_kind_of(model_path, rb_path2class("URI::HTTP"))) {
+    VALUE uri_class = rb_const_get(cModel, id_URI);
+    model_path = rb_class_new_instance(1, &model_path, uri_class);
+  }
+  if (rb_respond_to(model_path, id_to_path)) {
+    model_path = rb_funcall(model_path, id_to_path, 0);
+  }
+
+  return model_path;
 }
 
 /*
@@ -66,27 +127,9 @@ ruby_whisper_initialize(int argc, VALUE *argv, VALUE self)
 
   // TODO: we can support init from buffer here too maybe another ruby object to expose
   rb_scan_args(argc, argv, "01", &whisper_model_file_path);
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
 
-  VALUE pre_converted_models = rb_funcall(cModel, id_pre_converted_models, 0);
-  VALUE pre_converted_model = rb_hash_aref(pre_converted_models, whisper_model_file_path);
-  if (!NIL_P(pre_converted_model)) {
-    whisper_model_file_path = pre_converted_model;
-  }
-  if (TYPE(whisper_model_file_path) == T_STRING) {
-    const char * whisper_model_file_path_str = StringValueCStr(whisper_model_file_path);
-    if (strncmp("http://", whisper_model_file_path_str, 7) == 0 || strncmp("https://", whisper_model_file_path_str, 8) == 0) {
-      VALUE uri_class = rb_const_get(cModel, id_URI);
-      whisper_model_file_path = rb_class_new_instance(1, &whisper_model_file_path, uri_class);
-    }
-  }
-  if (rb_obj_is_kind_of(whisper_model_file_path, rb_path2class("URI::HTTP"))) {
-    VALUE uri_class = rb_const_get(cModel, id_URI);
-    whisper_model_file_path = rb_class_new_instance(1, &whisper_model_file_path, uri_class);
-  }
-  if (rb_respond_to(whisper_model_file_path, id_to_path)) {
-    whisper_model_file_path = rb_funcall(whisper_model_file_path, id_to_path, 0);
-  }
+  whisper_model_file_path = ruby_whisper_normalize_model_path(whisper_model_file_path);
   if (!rb_respond_to(whisper_model_file_path, id_to_s)) {
     rb_raise(rb_eRuntimeError, "Expected file path to model to initialize Whisper::Context");
   }
@@ -104,7 +147,7 @@ ruby_whisper_initialize(int argc, VALUE *argv, VALUE self)
 VALUE ruby_whisper_model_n_vocab(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_vocab(rw->context));
 }
 
@@ -115,7 +158,7 @@ VALUE ruby_whisper_model_n_vocab(VALUE self)
 VALUE ruby_whisper_model_n_audio_ctx(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_ctx(rw->context));
 }
 
@@ -126,7 +169,7 @@ VALUE ruby_whisper_model_n_audio_ctx(VALUE self)
 VALUE ruby_whisper_model_n_audio_state(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_state(rw->context));
 }
 
@@ -137,7 +180,7 @@ VALUE ruby_whisper_model_n_audio_state(VALUE self)
 VALUE ruby_whisper_model_n_audio_head(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_head(rw->context));
 }
 
@@ -148,7 +191,7 @@ VALUE ruby_whisper_model_n_audio_head(VALUE self)
 VALUE ruby_whisper_model_n_audio_layer(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_layer(rw->context));
 }
 
@@ -159,7 +202,7 @@ VALUE ruby_whisper_model_n_audio_layer(VALUE self)
 VALUE ruby_whisper_model_n_text_ctx(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_ctx(rw->context));
 }
 
@@ -170,7 +213,7 @@ VALUE ruby_whisper_model_n_text_ctx(VALUE self)
 VALUE ruby_whisper_model_n_text_state(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_state(rw->context));
 }
 
@@ -181,7 +224,7 @@ VALUE ruby_whisper_model_n_text_state(VALUE self)
 VALUE ruby_whisper_model_n_text_head(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_head(rw->context));
 }
 
@@ -192,7 +235,7 @@ VALUE ruby_whisper_model_n_text_head(VALUE self)
 VALUE ruby_whisper_model_n_text_layer(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_layer(rw->context));
 }
 
@@ -203,7 +246,7 @@ VALUE ruby_whisper_model_n_text_layer(VALUE self)
 VALUE ruby_whisper_model_n_mels(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_mels(rw->context));
 }
 
@@ -214,7 +257,7 @@ VALUE ruby_whisper_model_n_mels(VALUE self)
 VALUE ruby_whisper_model_ftype(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_ftype(rw->context));
 }
 
@@ -225,7 +268,7 @@ VALUE ruby_whisper_model_ftype(VALUE self)
 VALUE ruby_whisper_model_type(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return rb_str_new2(whisper_model_type_readable(rw->context));
 }
 
@@ -248,9 +291,9 @@ VALUE ruby_whisper_full(int argc, VALUE *argv, VALUE self)
 
   ruby_whisper *rw;
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   VALUE params = argv[0];
-  Data_Get_Struct(params, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(params, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   VALUE samples = argv[1];
   int n_samples;
   rb_memory_view_t view;
@@ -265,13 +308,20 @@ VALUE ruby_whisper_full(int argc, VALUE *argv, VALUE self)
     // Should check when samples.respond_to?(:length)?
   } else {
     if (TYPE(samples) == T_ARRAY) {
-      n_samples = RARRAY_LEN(samples);
+      if (RARRAY_LEN(samples) > INT_MAX) {
+        rb_raise(rb_eArgError, "samples are too long");
+      }
+      n_samples = (int)RARRAY_LEN(samples);
     } else if (memory_view_available_p) {
       if (!rb_memory_view_get(samples, &view, RUBY_MEMORY_VIEW_SIMPLE)) {
         view.obj = Qnil;
         rb_raise(rb_eArgError, "unable to get a memory view");
       }
-      n_samples = view.byte_size / view.item_size;
+      ssize_t n_samples_size = view.byte_size / view.item_size;
+      if (n_samples_size > INT_MAX) {
+        rb_raise(rb_eArgError, "samples are too long");
+      }
+      n_samples = (int)n_samples_size;
     } else if (rb_respond_to(samples, id_length)) {
       n_samples = NUM2INT(rb_funcall(samples, id_length, 0));
     } else {
@@ -296,7 +346,7 @@ VALUE ruby_whisper_full(int argc, VALUE *argv, VALUE self)
       }
     }
   }
-  register_callbacks(rwp, &self);
+  prepare_transcription(rwp, &self);
   const int result = whisper_full(rw->context, rwp->params, c_samples, n_samples);
   if (0 == result) {
     return self;
@@ -327,9 +377,9 @@ ruby_whisper_full_parallel(int argc, VALUE *argv,VALUE self)
 
   ruby_whisper *rw;
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   VALUE params = argv[0];
-  Data_Get_Struct(params, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(params, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   VALUE samples = argv[1];
   int n_samples;
   int n_processors;
@@ -359,10 +409,17 @@ ruby_whisper_full_parallel(int argc, VALUE *argv,VALUE self)
       view.obj = Qnil;
       rb_raise(rb_eArgError, "unable to get a memory view");
     }
-    n_samples = view.byte_size / view.item_size;
+    ssize_t n_samples_size = view.byte_size / view.item_size;
+    if (n_samples_size > INT_MAX) {
+      rb_raise(rb_eArgError, "samples are too long");
+    }
+    n_samples = (int)n_samples_size;
   } else {
     if (TYPE(samples) == T_ARRAY) {
-      n_samples = RARRAY_LEN(samples);
+      if (RARRAY_LEN(samples) > INT_MAX) {
+        rb_raise(rb_eArgError, "samples are too long");
+      }
+      n_samples = (int)RARRAY_LEN(samples);
     } else if (rb_respond_to(samples, id_length)) {
       n_samples = NUM2INT(rb_funcall(samples, id_length, 0));
     } else {
@@ -387,7 +444,7 @@ ruby_whisper_full_parallel(int argc, VALUE *argv,VALUE self)
       }
     }
   }
-  register_callbacks(rwp, &self);
+  prepare_transcription(rwp, &self);
   const int result = whisper_full_parallel(rw->context, rwp->params, c_samples, n_samples, n_processors);
   if (0 == result) {
     return self;
@@ -406,7 +463,7 @@ static VALUE
 ruby_whisper_full_n_segments(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_full_n_segments(rw->context));
 }
 
@@ -420,7 +477,7 @@ static VALUE
 ruby_whisper_full_lang_id(VALUE self)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_full_lang_id(rw->context));
 }
 
@@ -445,10 +502,10 @@ static VALUE
 ruby_whisper_full_get_segment_t0(VALUE self, VALUE i_segment)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   const int c_i_segment = ruby_whisper_full_check_segment_index(rw, i_segment);
   const int64_t t0 = whisper_full_get_segment_t0(rw->context, c_i_segment);
-  return INT2NUM(t0);
+  return LONG2NUM(t0);
 }
 
 /*
@@ -463,10 +520,10 @@ static VALUE
 ruby_whisper_full_get_segment_t1(VALUE self, VALUE i_segment)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   const int c_i_segment = ruby_whisper_full_check_segment_index(rw, i_segment);
   const int64_t t1 = whisper_full_get_segment_t1(rw->context, c_i_segment);
-  return INT2NUM(t1);
+  return LONG2NUM(t1);
 }
 
 /*
@@ -481,7 +538,7 @@ static VALUE
 ruby_whisper_full_get_segment_speaker_turn_next(VALUE self, VALUE i_segment)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   const int c_i_segment = ruby_whisper_full_check_segment_index(rw, i_segment);
   const bool speaker_turn_next = whisper_full_get_segment_speaker_turn_next(rw->context, c_i_segment);
   return speaker_turn_next ? Qtrue : Qfalse;
@@ -499,7 +556,7 @@ static VALUE
 ruby_whisper_full_get_segment_text(VALUE self, VALUE i_segment)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   const int c_i_segment = ruby_whisper_full_check_segment_index(rw, i_segment);
   const char * text = whisper_full_get_segment_text(rw->context, c_i_segment);
   return rb_str_new2(text);
@@ -513,7 +570,7 @@ static VALUE
 ruby_whisper_full_get_segment_no_speech_prob(VALUE self, VALUE i_segment)
 {
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
   const int c_i_segment = ruby_whisper_full_check_segment_index(rw, i_segment);
   const float no_speech_prob = whisper_full_get_segment_no_speech_prob(rw->context, c_i_segment);
   return DBL2NUM(no_speech_prob);
@@ -524,7 +581,7 @@ ruby_whisper_full_get_segment_no_speech_prob(VALUE self, VALUE i_segment)
 static VALUE
 ruby_whisper_full_get_segment(VALUE self, VALUE i_segment)
 {
-  return rb_whisper_segment_initialize(self, NUM2INT(i_segment));
+  return rb_whisper_segment_s_new(self, NUM2INT(i_segment));
 }
 
 /*
@@ -554,11 +611,11 @@ ruby_whisper_each_segment(VALUE self)
   }
 
   ruby_whisper *rw;
-  Data_Get_Struct(self, ruby_whisper, rw);
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
 
   const int n_segments = whisper_full_n_segments(rw->context);
   for (int i = 0; i < n_segments; ++i) {
-    rb_yield(rb_whisper_segment_initialize(self, i));
+    rb_yield(rb_whisper_segment_s_new(self, i));
   }
 
   return self;
@@ -571,7 +628,7 @@ ruby_whisper_each_segment(VALUE self)
 static VALUE
 ruby_whisper_get_model(VALUE self)
 {
-  return rb_whisper_model_initialize(self);
+  return rb_whisper_model_s_new(self);
 }
 
 void
@@ -579,6 +636,8 @@ init_ruby_whisper_context(VALUE *mWhisper)
 {
   cContext = rb_define_class_under(*mWhisper, "Context", rb_cObject);
 
+  transcribe_option_names[0] = id_n_processors;
+
   rb_define_alloc_func(cContext, ruby_whisper_allocate);
   rb_define_method(cContext, "initialize", ruby_whisper_initialize, -1);
 
@@ -605,7 +664,7 @@ init_ruby_whisper_context(VALUE *mWhisper)
   rb_define_method(cContext, "full", ruby_whisper_full, -1);
   rb_define_method(cContext, "full_parallel", ruby_whisper_full_parallel, -1);
 
-  // High leve
+  // High level
   rb_define_method(cContext, "full_get_segment", ruby_whisper_full_get_segment, 1);
   rb_define_method(cContext, "each_segment", ruby_whisper_each_segment, 0);
 

bindings/ruby/ext/ruby_whisper_model.c

@@ -1,22 +1,44 @@
 #include <ruby.h>
 #include "ruby_whisper.h"
 
+extern const rb_data_type_t ruby_whisper_type;
+
 extern VALUE cModel;
 
-static void rb_whisper_model_mark(ruby_whisper_model *rwm) {
-  rb_gc_mark(rwm->context);
+static void rb_whisper_model_mark(void *p) {
+  ruby_whisper_model *rwm = (ruby_whisper_model *)p;
+  if (rwm->context) {
+    rb_gc_mark(rwm->context);
+  }
 }
 
+static size_t
+ruby_whisper_model_memsize(const void *p)
+{
+  const ruby_whisper_model *rwm = (const ruby_whisper_model *)p;
+  size_t size = sizeof(rwm);
+  if (!rwm) {
+    return 0;
+  }
+  return size;
+}
+
+static const rb_data_type_t rb_whisper_model_type = {
+  "ruby_whisper_model",
+  {rb_whisper_model_mark, RUBY_DEFAULT_FREE, ruby_whisper_model_memsize,},
+  0, 0,
+  0
+};
+
 static VALUE ruby_whisper_model_allocate(VALUE klass) {
   ruby_whisper_model *rwm;
-  rwm = ALLOC(ruby_whisper_model);
-  return Data_Wrap_Struct(klass, rb_whisper_model_mark, RUBY_DEFAULT_FREE, rwm);
+  return TypedData_Make_Struct(klass, ruby_whisper_model, &rb_whisper_model_type, rwm);
 }
 
-VALUE rb_whisper_model_initialize(VALUE context) {
+VALUE rb_whisper_model_s_new(VALUE context) {
   ruby_whisper_model *rwm;
   const VALUE model = ruby_whisper_model_allocate(cModel);
-  Data_Get_Struct(model, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(model, ruby_whisper_model, &rb_whisper_model_type, rwm);
   rwm->context = context;
   return model;
 };
@@ -29,9 +51,9 @@ static VALUE
 ruby_whisper_model_n_vocab(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_vocab(rw->context));
 }
 
@@ -43,9 +65,9 @@ static VALUE
 ruby_whisper_model_n_audio_ctx(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_ctx(rw->context));
 }
 
@@ -57,9 +79,9 @@ static VALUE
 ruby_whisper_model_n_audio_state(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_state(rw->context));
 }
 
@@ -71,9 +93,9 @@ static VALUE
 ruby_whisper_model_n_audio_head(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_head(rw->context));
 }
 
@@ -85,9 +107,9 @@ static VALUE
 ruby_whisper_model_n_audio_layer(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_audio_layer(rw->context));
 }
 
@@ -99,9 +121,9 @@ static VALUE
 ruby_whisper_model_n_text_ctx(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_ctx(rw->context));
 }
 
@@ -113,9 +135,9 @@ static VALUE
 ruby_whisper_model_n_text_state(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_state(rw->context));
 }
 
@@ -127,9 +149,9 @@ static VALUE
 ruby_whisper_model_n_text_head(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_head(rw->context));
 }
 
@@ -141,9 +163,9 @@ static VALUE
 ruby_whisper_model_n_text_layer(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_text_layer(rw->context));
 }
 
@@ -155,9 +177,9 @@ static VALUE
 ruby_whisper_model_n_mels(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_n_mels(rw->context));
 }
 
@@ -169,9 +191,9 @@ static VALUE
 ruby_whisper_model_ftype(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return INT2NUM(whisper_model_ftype(rw->context));
 }
 
@@ -183,9 +205,9 @@ static VALUE
 ruby_whisper_model_type(VALUE self)
 {
   ruby_whisper_model *rwm;
-  Data_Get_Struct(self, ruby_whisper_model, rwm);
+  TypedData_Get_Struct(self, ruby_whisper_model, &rb_whisper_model_type, rwm);
   ruby_whisper *rw;
-  Data_Get_Struct(rwm->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rwm->context, ruby_whisper, &ruby_whisper_type, rw);
   return rb_str_new2(whisper_model_type_readable(rw->context));
 }
 

bindings/ruby/ext/ruby_whisper_params.c

@@ -3,7 +3,7 @@
 
 #define BOOL_PARAMS_SETTER(self, prop, value) \
   ruby_whisper_params *rwp; \
-  Data_Get_Struct(self, ruby_whisper_params, rwp); \
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp); \
   if (value == Qfalse || value == Qnil) { \
     rwp->params.prop = false; \
   } else { \
@@ -13,7 +13,7 @@
 
 #define BOOL_PARAMS_GETTER(self,  prop) \
   ruby_whisper_params *rwp; \
-  Data_Get_Struct(self, ruby_whisper_params, rwp); \
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp); \
   if (rwp->params.prop) { \
     return Qtrue; \
   } else { \
@@ -26,13 +26,16 @@
   rb_define_method(cParams, #param_name, ruby_whisper_params_get_ ## param_name, 0); \
   rb_define_method(cParams, #param_name "=", ruby_whisper_params_set_ ## param_name, 1);
 
-#define RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT 30
+#define RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT 35
 
 extern VALUE cParams;
+extern VALUE cVADParams;
 
 extern ID id_call;
 
-extern VALUE rb_whisper_segment_initialize(VALUE context, int index);
+extern VALUE ruby_whisper_normalize_model_path(VALUE model_path);
+extern VALUE rb_whisper_segment_s_new(VALUE context, int index);
+extern const rb_data_type_t ruby_whisper_vad_params_type;
 
 static ID param_names[RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT];
 static ID id_language;
@@ -63,12 +66,19 @@ static ID id_new_segment_callback;
 static ID id_new_segment_callback_user_data;
 static ID id_progress_callback;
 static ID id_progress_callback_user_data;
+static ID id_encoder_begin_callback;
+static ID id_encoder_begin_callback_user_data;
 static ID id_abort_callback;
 static ID id_abort_callback_user_data;
+static ID id_vad;
+static ID id_vad_model_path;
+static ID id_vad_params;
 
 static void
 rb_whisper_callbcack_container_mark(ruby_whisper_callback_container *rwc)
 {
+  if (rwc == NULL) return;
+
   rb_gc_mark(rwc->user_data);
   rb_gc_mark(rwc->callback);
   rb_gc_mark(rwc->callbacks);
@@ -100,7 +110,7 @@ static void new_segment_callback(struct whisper_context *ctx, struct whisper_sta
   const int n_segments = whisper_full_n_segments_from_state(state);
   for (int i = n_new; i > 0; i--) {
     int i_segment = n_segments - i;
-    VALUE segment = rb_whisper_segment_initialize(*container->context, i_segment);
+    VALUE segment = rb_whisper_segment_s_new(*container->context, i_segment);
     for (int j = 0; j < callbacks_len; j++) {
       VALUE cb = rb_ary_entry(container->callbacks, j);
       rb_funcall(cb, id_call, 1, segment);
@@ -126,6 +136,33 @@ static void progress_callback(struct whisper_context *ctx, struct whisper_state
   }
 }
 
+static bool encoder_begin_callback(struct whisper_context *ctx, struct whisper_state *state, void *user_data) {
+  const ruby_whisper_callback_container *container = (ruby_whisper_callback_container *)user_data;
+  bool is_aborted = false;
+  VALUE result;
+
+  // Currently, doesn't support state because
+  // those require to resolve GC-related problems.
+  if (!NIL_P(container->callback)) {
+    result = rb_funcall(container->callback, id_call, 3, *container->context, Qnil, container->user_data);
+    if (result == Qfalse) {
+      is_aborted = true;
+    }
+  }
+  const long callbacks_len = RARRAY_LEN(container->callbacks);
+  if (0 == callbacks_len) {
+    return !is_aborted;
+  }
+  for (int j = 0; j < callbacks_len; j++) {
+    VALUE cb = rb_ary_entry(container->callbacks, j);
+    result = rb_funcall(cb, id_call, 0);
+    if (result == Qfalse) {
+      is_aborted = true;
+    }
+  }
+  return !is_aborted;
+}
+
 static bool abort_callback(void * user_data) {
   const ruby_whisper_callback_container *container = (ruby_whisper_callback_container *)user_data;
   if (!NIL_P(container->callback)) {
@@ -148,7 +185,7 @@ static bool abort_callback(void * user_data) {
   return false;
 }
 
-void register_callbacks(ruby_whisper_params * rwp, VALUE * context) {
+static void register_callbacks(ruby_whisper_params * rwp, VALUE * context) {
   if (!NIL_P(rwp->new_segment_callback_container->callback) || 0 != RARRAY_LEN(rwp->new_segment_callback_container->callbacks)) {
     rwp->new_segment_callback_container->context = context;
     rwp->params.new_segment_callback = new_segment_callback;
@@ -161,6 +198,12 @@ void register_callbacks(ruby_whisper_params * rwp, VALUE * context) {
     rwp->params.progress_callback_user_data = rwp->progress_callback_container;
   }
 
+  if (!NIL_P(rwp->encoder_begin_callback_container->callback) || 0 != RARRAY_LEN(rwp->encoder_begin_callback_container->callbacks)) {
+    rwp->encoder_begin_callback_container->context = context;
+    rwp->params.encoder_begin_callback = encoder_begin_callback;
+    rwp->params.encoder_begin_callback_user_data = rwp->encoder_begin_callback_container;
+  }
+
   if (!NIL_P(rwp->abort_callback_container->callback) || 0 != RARRAY_LEN(rwp->abort_callback_container->callbacks)) {
     rwp->abort_callback_container->context = context;
     rwp->params.abort_callback = abort_callback;
@@ -168,12 +211,29 @@ void register_callbacks(ruby_whisper_params * rwp, VALUE * context) {
   }
 }
 
-void
-rb_whisper_params_mark(ruby_whisper_params *rwp)
+static void set_vad_params(ruby_whisper_params *rwp)
 {
+  ruby_whisper_vad_params * rwvp;
+  TypedData_Get_Struct(rwp->vad_params, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwp->params.vad_params = rwvp->params;
+}
+
+void
+prepare_transcription(ruby_whisper_params *rwp, VALUE *context)
+{
+  register_callbacks(rwp, context);
+  set_vad_params(rwp);
+}
+
+void
+rb_whisper_params_mark(void *p)
+{
+  ruby_whisper_params *rwp = (ruby_whisper_params *)p;
   rb_whisper_callbcack_container_mark(rwp->new_segment_callback_container);
   rb_whisper_callbcack_container_mark(rwp->progress_callback_container);
+  rb_whisper_callbcack_container_mark(rwp->encoder_begin_callback_container);
   rb_whisper_callbcack_container_mark(rwp->abort_callback_container);
+  rb_gc_mark(rwp->vad_params);
 }
 
 void
@@ -182,24 +242,46 @@ ruby_whisper_params_free(ruby_whisper_params *rwp)
 }
 
 void
-rb_whisper_params_free(ruby_whisper_params *rwp)
+rb_whisper_params_free(void *p)
 {
+  ruby_whisper_params *rwp = (ruby_whisper_params *)p;
   // How to free user_data and callback only when not referred to by others?
   ruby_whisper_params_free(rwp);
   free(rwp);
 }
 
+static size_t
+ruby_whisper_params_memsize(const void *p)
+{
+  const ruby_whisper_params *rwp = (const ruby_whisper_params *)p;
+
+  return sizeof(ruby_whisper_params) + sizeof(rwp->params) + sizeof(rwp->vad_params);
+}
+
+const rb_data_type_t ruby_whisper_params_type = {
+  "ruby_whisper_params",
+  {
+    rb_whisper_params_mark,
+    rb_whisper_params_free,
+    ruby_whisper_params_memsize,
+  },
+  0, 0,
+  0
+};
+
 static VALUE
 ruby_whisper_params_allocate(VALUE klass)
 {
   ruby_whisper_params *rwp;
-  rwp = ALLOC(ruby_whisper_params);
+  VALUE obj = TypedData_Make_Struct(klass, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
   rwp->diarize = false;
+  rwp->vad_params = TypedData_Wrap_Struct(cVADParams, &ruby_whisper_vad_params_type, (void *)&rwp->params.vad_params);
   rwp->new_segment_callback_container = rb_whisper_callback_container_allocate();
   rwp->progress_callback_container = rb_whisper_callback_container_allocate();
+  rwp->encoder_begin_callback_container = rb_whisper_callback_container_allocate();
   rwp->abort_callback_container = rb_whisper_callback_container_allocate();
-  return Data_Wrap_Struct(klass, rb_whisper_params_mark, rb_whisper_params_free, rwp);
+  return obj;
 }
 
 /*
@@ -212,7 +294,7 @@ static VALUE
 ruby_whisper_params_set_language(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   if (value == Qfalse || value == Qnil) {
     rwp->params.language = "auto";
   } else {
@@ -228,7 +310,7 @@ static VALUE
 ruby_whisper_params_get_language(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   if (rwp->params.language) {
     return rb_str_new2(rwp->params.language);
   } else {
@@ -465,7 +547,7 @@ static VALUE
 ruby_whisper_params_get_initial_prompt(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->params.initial_prompt == NULL ? Qnil : rb_str_new2(rwp->params.initial_prompt);
 }
 /*
@@ -476,7 +558,7 @@ static VALUE
 ruby_whisper_params_set_initial_prompt(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.initial_prompt = StringValueCStr(value);
   return value;
 }
@@ -490,7 +572,7 @@ static VALUE
 ruby_whisper_params_get_diarize(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   if (rwp->diarize) {
     return Qtrue;
   } else {
@@ -505,7 +587,7 @@ static VALUE
 ruby_whisper_params_set_diarize(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   if (value == Qfalse || value == Qnil) {
     rwp->diarize = false;
   } else {
@@ -524,7 +606,7 @@ static VALUE
 ruby_whisper_params_get_offset(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return INT2NUM(rwp->params.offset_ms);
 }
 /*
@@ -535,7 +617,7 @@ static VALUE
 ruby_whisper_params_set_offset(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.offset_ms = NUM2INT(value);
   return value;
 }
@@ -549,7 +631,7 @@ static VALUE
 ruby_whisper_params_get_duration(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return INT2NUM(rwp->params.duration_ms);
 }
 /*
@@ -560,7 +642,7 @@ static VALUE
 ruby_whisper_params_set_duration(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.duration_ms = NUM2INT(value);
   return value;
 }
@@ -575,7 +657,7 @@ static VALUE
 ruby_whisper_params_get_max_text_tokens(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return INT2NUM(rwp->params.n_max_text_ctx);
 }
 /*
@@ -586,7 +668,7 @@ static VALUE
 ruby_whisper_params_set_max_text_tokens(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.n_max_text_ctx = NUM2INT(value);
   return value;
 }
@@ -598,7 +680,7 @@ static VALUE
 ruby_whisper_params_get_temperature(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.temperature);
 }
 /*
@@ -609,7 +691,7 @@ static VALUE
 ruby_whisper_params_set_temperature(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.temperature = RFLOAT_VALUE(value);
   return value;
 }
@@ -623,7 +705,7 @@ static VALUE
 ruby_whisper_params_get_max_initial_ts(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.max_initial_ts);
 }
 /*
@@ -634,7 +716,7 @@ static VALUE
 ruby_whisper_params_set_max_initial_ts(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.max_initial_ts = RFLOAT_VALUE(value);
   return value;
 }
@@ -646,7 +728,7 @@ static VALUE
 ruby_whisper_params_get_length_penalty(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.length_penalty);
 }
 /*
@@ -657,7 +739,7 @@ static VALUE
 ruby_whisper_params_set_length_penalty(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.length_penalty = RFLOAT_VALUE(value);
   return value;
 }
@@ -669,7 +751,7 @@ static VALUE
 ruby_whisper_params_get_temperature_inc(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.temperature_inc);
 }
 /*
@@ -680,7 +762,7 @@ static VALUE
 ruby_whisper_params_set_temperature_inc(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.temperature_inc = RFLOAT_VALUE(value);
   return value;
 }
@@ -694,7 +776,7 @@ static VALUE
 ruby_whisper_params_get_entropy_thold(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.entropy_thold);
 }
 /*
@@ -705,7 +787,7 @@ static VALUE
 ruby_whisper_params_set_entropy_thold(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.entropy_thold = RFLOAT_VALUE(value);
   return value;
 }
@@ -717,7 +799,7 @@ static VALUE
 ruby_whisper_params_get_logprob_thold(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.logprob_thold);
 }
 /*
@@ -728,7 +810,7 @@ static VALUE
 ruby_whisper_params_set_logprob_thold(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.logprob_thold = RFLOAT_VALUE(value);
   return value;
 }
@@ -740,7 +822,7 @@ static VALUE
 ruby_whisper_params_get_no_speech_thold(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return DBL2NUM(rwp->params.no_speech_thold);
 }
 /*
@@ -751,7 +833,7 @@ static VALUE
 ruby_whisper_params_set_no_speech_thold(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->params.no_speech_thold = RFLOAT_VALUE(value);
   return value;
 }
@@ -759,7 +841,7 @@ static VALUE
 ruby_whisper_params_get_new_segment_callback(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->new_segment_callback_container->callback;
 }
 /*
@@ -776,7 +858,7 @@ static VALUE
 ruby_whisper_params_set_new_segment_callback(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->new_segment_callback_container->callback = value;
   return value;
 }
@@ -784,7 +866,7 @@ static VALUE
 ruby_whisper_params_get_new_segment_callback_user_data(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->new_segment_callback_container->user_data;
 }
 /*
@@ -797,7 +879,7 @@ static VALUE
 ruby_whisper_params_set_new_segment_callback_user_data(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->new_segment_callback_container->user_data = value;
   return value;
 }
@@ -805,7 +887,7 @@ static VALUE
 ruby_whisper_params_get_progress_callback(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->progress_callback_container->callback;
 }
 /*
@@ -824,7 +906,7 @@ static VALUE
 ruby_whisper_params_set_progress_callback(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->progress_callback_container->callback = value;
   return value;
 }
@@ -832,7 +914,7 @@ static VALUE
 ruby_whisper_params_get_progress_callback_user_data(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->progress_callback_container->user_data;
 }
 /*
@@ -845,15 +927,66 @@ static VALUE
 ruby_whisper_params_set_progress_callback_user_data(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->progress_callback_container->user_data = value;
   return value;
 }
+
+static VALUE
+ruby_whisper_params_get_encoder_begin_callback(VALUE self)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  return rwp->encoder_begin_callback_container->callback;
+}
+
+/*
+ * Sets encoder begin callback, called when the encoder starts.
+ *
+ *   params.encoder_begin_callback = ->(context, _, user_data) {
+ *     # ...
+ *   }
+ *
+ * call-seq:
+ *   encoder_begin_callback = callback -> callback
+ */
+static VALUE
+ruby_whisper_params_set_encoder_begin_callback(VALUE self, VALUE value)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  rwp->encoder_begin_callback_container->callback = value;
+  return value;
+}
+
+static VALUE
+ruby_whisper_params_get_encoder_begin_callback_user_data(VALUE self)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  return rwp->encoder_begin_callback_container->user_data;
+}
+
+/*
+ * Sets user data passed to the last argument of encoder begin callback.
+ *
+ * call-seq:
+ *   encoder_begin_callback_user_data = user_data -> use_data
+ */
+static VALUE
+ruby_whisper_params_set_encoder_begin_callback_user_data(VALUE self, VALUE value)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  rwp->encoder_begin_callback_container->user_data = value;
+  return value;
+}
+
 static VALUE
 ruby_whisper_params_get_abort_callback(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->abort_callback_container->callback;
 }
 /*
@@ -870,7 +1003,7 @@ static VALUE
 ruby_whisper_params_set_abort_callback(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->abort_callback_container->callback = value;
   return value;
 }
@@ -878,7 +1011,7 @@ static VALUE
 ruby_whisper_params_get_abort_callback_user_data(VALUE self)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   return rwp->abort_callback_container->user_data;
 }
 /*
@@ -891,11 +1024,74 @@ static VALUE
 ruby_whisper_params_set_abort_callback_user_data(VALUE self, VALUE value)
 {
   ruby_whisper_params *rwp;
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   rwp->abort_callback_container->user_data = value;
   return value;
 }
 
+/*
+ * call-seq:
+ *   vad = use_vad -> use_vad
+ */
+static VALUE
+ruby_whisper_params_get_vad(VALUE self)
+{
+  BOOL_PARAMS_GETTER(self, vad)
+}
+
+static VALUE
+ruby_whisper_params_set_vad(VALUE self, VALUE value)
+{
+  BOOL_PARAMS_SETTER(self, vad, value)
+}
+
+/*
+ * call-seq:
+ *   vad_model_path = model_path -> model_path
+ */
+static VALUE
+ruby_whisper_params_set_vad_model_path(VALUE self, VALUE value)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  if (NIL_P(value)) {
+    rwp->params.vad_model_path = NULL;
+    return value;
+  }
+  VALUE path = ruby_whisper_normalize_model_path(value);
+  rwp->params.vad_model_path = StringValueCStr(path);
+  return value;
+}
+
+static VALUE
+ruby_whisper_params_get_vad_model_path(VALUE self)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  return rwp->params.vad_model_path == NULL ? Qnil : rb_str_new2(rwp->params.vad_model_path);
+}
+
+/*
+ * call-seq:
+ *   vad_params = params -> params
+ */
+static VALUE
+ruby_whisper_params_set_vad_params(VALUE self, VALUE value)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  rwp->vad_params = value;
+  return value;
+}
+
+static VALUE
+ruby_whisper_params_get_vad_params(VALUE self)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  return rwp->vad_params;
+}
+
 #define SET_PARAM_IF_SAME(param_name) \
   if (id == id_ ## param_name) { \
     ruby_whisper_params_set_ ## param_name(self, value); \
@@ -905,7 +1101,6 @@ ruby_whisper_params_set_abort_callback_user_data(VALUE self, VALUE value)
 static VALUE
 ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
 {
-
   VALUE kw_hash;
   VALUE values[RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT] = {Qundef};
   VALUE value;
@@ -918,8 +1113,8 @@ ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
     return self;
   }
 
-  rb_get_kwargs(kw_hash, &param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, &values);
-  Data_Get_Struct(self, ruby_whisper_params, rwp);
+  rb_get_kwargs(kw_hash, param_names, 0, RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT, values);
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
 
   for (i = 0; i < RUBY_WHISPER_PARAMS_PARAM_NAMES_COUNT; i++) {
     id = param_names[i];
@@ -958,8 +1153,13 @@ ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
       SET_PARAM_IF_SAME(new_segment_callback_user_data)
       SET_PARAM_IF_SAME(progress_callback)
       SET_PARAM_IF_SAME(progress_callback_user_data)
+      SET_PARAM_IF_SAME(encoder_begin_callback)
+      SET_PARAM_IF_SAME(encoder_begin_callback_user_data)
       SET_PARAM_IF_SAME(abort_callback)
       SET_PARAM_IF_SAME(abort_callback_user_data)
+      SET_PARAM_IF_SAME(vad)
+      SET_PARAM_IF_SAME(vad_model_path)
+      SET_PARAM_IF_SAME(vad_params)
     }
   }
 
@@ -981,10 +1181,10 @@ ruby_whisper_params_initialize(int argc, VALUE *argv, VALUE self)
 static VALUE
 ruby_whisper_params_on_new_segment(VALUE self)
 {
-  ruby_whisper_params *rws;
-  Data_Get_Struct(self, ruby_whisper_params, rws);
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   const VALUE blk = rb_block_proc();
-  rb_ary_push(rws->new_segment_callback_container->callbacks, blk);
+  rb_ary_push(rwp->new_segment_callback_container->callbacks, blk);
   return Qnil;
 }
 
@@ -1001,10 +1201,30 @@ ruby_whisper_params_on_new_segment(VALUE self)
 static VALUE
 ruby_whisper_params_on_progress(VALUE self)
 {
-  ruby_whisper_params *rws;
-  Data_Get_Struct(self, ruby_whisper_params, rws);
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   const VALUE blk = rb_block_proc();
-  rb_ary_push(rws->progress_callback_container->callbacks, blk);
+  rb_ary_push(rwp->progress_callback_container->callbacks, blk);
+  return Qnil;
+}
+
+/*
+ * Hook called when the encoder starts.
+ *
+ *   whisper.on_encoder_begin do
+ *     # ...
+ *   end
+ *
+ * call-seq:
+ *   on_encoder_begin { ... }
+ */
+static VALUE
+ruby_whisper_params_on_encoder_begin(VALUE self)
+{
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
+  const VALUE blk = rb_block_proc();
+  rb_ary_push(rwp->encoder_begin_callback_container->callbacks, blk);
   return Qnil;
 }
 
@@ -1025,10 +1245,10 @@ ruby_whisper_params_on_progress(VALUE self)
 static VALUE
 ruby_whisper_params_abort_on(VALUE self)
 {
-  ruby_whisper_params *rws;
-  Data_Get_Struct(self, ruby_whisper_params, rws);
+  ruby_whisper_params *rwp;
+  TypedData_Get_Struct(self, ruby_whisper_params, &ruby_whisper_params_type, rwp);
   const VALUE blk = rb_block_proc();
-  rb_ary_push(rws->abort_callback_container->callbacks, blk);
+  rb_ary_push(rwp->abort_callback_container->callbacks, blk);
   return Qnil;
 }
 
@@ -1068,10 +1288,16 @@ init_ruby_whisper_params(VALUE *mWhisper)
   DEFINE_PARAM(new_segment_callback_user_data, 25)
   DEFINE_PARAM(progress_callback, 26)
   DEFINE_PARAM(progress_callback_user_data, 27)
-  DEFINE_PARAM(abort_callback, 28)
-  DEFINE_PARAM(abort_callback_user_data, 29)
+  DEFINE_PARAM(encoder_begin_callback, 28)
+  DEFINE_PARAM(encoder_begin_callback_user_data, 29)
+  DEFINE_PARAM(abort_callback, 30)
+  DEFINE_PARAM(abort_callback_user_data, 31)
+  DEFINE_PARAM(vad, 32)
+  DEFINE_PARAM(vad_model_path, 33)
+  DEFINE_PARAM(vad_params, 34)
 
   rb_define_method(cParams, "on_new_segment", ruby_whisper_params_on_new_segment, 0);
   rb_define_method(cParams, "on_progress", ruby_whisper_params_on_progress, 0);
+  rb_define_method(cParams, "on_encoder_begin", ruby_whisper_params_on_encoder_begin, 0);
   rb_define_method(cParams, "abort_on", ruby_whisper_params_abort_on, 0);
 }

bindings/ruby/ext/ruby_whisper_segment.c

@@ -1,28 +1,57 @@
 #include <ruby.h>
 #include "ruby_whisper.h"
 
+#define N_KEY_NAMES 5
+
+static VALUE sym_start_time;
+static VALUE sym_end_time;
+static VALUE sym_text;
+static VALUE sym_no_speech_prob;
+static VALUE sym_speaker_turn_next;
+static VALUE key_names;
+
+extern const rb_data_type_t ruby_whisper_type;
+
 extern VALUE cSegment;
 
 static void
-rb_whisper_segment_mark(ruby_whisper_segment *rws)
+rb_whisper_segment_mark(void *p)
 {
+  ruby_whisper_segment *rws = (ruby_whisper_segment *)p;
   rb_gc_mark(rws->context);
 }
 
+static size_t
+ruby_whisper_segment_memsize(const void *p)
+{
+  const ruby_whisper_segment *rws = (const ruby_whisper_segment *)p;
+  size_t size = sizeof(rws);
+  if (!rws) {
+    return 0;
+  }
+  return size;
+}
+
+static const rb_data_type_t ruby_whisper_segment_type = {
+  "ruby_whisper_segment",
+  {rb_whisper_segment_mark, RUBY_DEFAULT_FREE, ruby_whisper_segment_memsize,},
+  0, 0,
+  0
+};
+
 VALUE
 ruby_whisper_segment_allocate(VALUE klass)
 {
   ruby_whisper_segment *rws;
-  rws = ALLOC(ruby_whisper_segment);
-  return Data_Wrap_Struct(klass, rb_whisper_segment_mark, RUBY_DEFAULT_FREE, rws);
+  return TypedData_Make_Struct(klass, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
 }
 
 VALUE
-rb_whisper_segment_initialize(VALUE context, int index)
+rb_whisper_segment_s_new(VALUE context, int index)
 {
   ruby_whisper_segment *rws;
   const VALUE segment = ruby_whisper_segment_allocate(cSegment);
-  Data_Get_Struct(segment, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(segment, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   rws->context = context;
   rws->index = index;
   return segment;
@@ -38,12 +67,12 @@ static VALUE
 ruby_whisper_segment_get_start_time(VALUE self)
 {
   ruby_whisper_segment *rws;
-  Data_Get_Struct(self, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   ruby_whisper *rw;
-  Data_Get_Struct(rws->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
   const int64_t t0 = whisper_full_get_segment_t0(rw->context, rws->index);
   // able to multiply 10 without overflow because to_timestamp() in whisper.cpp does it
-  return INT2NUM(t0 * 10);
+  return LONG2NUM(t0 * 10);
 }
 
 /*
@@ -56,12 +85,12 @@ static VALUE
 ruby_whisper_segment_get_end_time(VALUE self)
 {
   ruby_whisper_segment *rws;
-  Data_Get_Struct(self, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   ruby_whisper *rw;
-  Data_Get_Struct(rws->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
   const int64_t t1 = whisper_full_get_segment_t1(rw->context, rws->index);
   // able to multiply 10 without overflow because to_timestamp() in whisper.cpp does it
-  return INT2NUM(t1 * 10);
+  return LONG2NUM(t1 * 10);
 }
 
 /*
@@ -74,9 +103,9 @@ static VALUE
 ruby_whisper_segment_get_speaker_turn_next(VALUE self)
 {
   ruby_whisper_segment *rws;
-  Data_Get_Struct(self, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   ruby_whisper *rw;
-  Data_Get_Struct(rws->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
   return whisper_full_get_segment_speaker_turn_next(rw->context, rws->index) ? Qtrue : Qfalse;
 }
 
@@ -88,9 +117,9 @@ static VALUE
 ruby_whisper_segment_get_text(VALUE self)
 {
   ruby_whisper_segment *rws;
-  Data_Get_Struct(self, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   ruby_whisper *rw;
-  Data_Get_Struct(rws->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
   const char * text = whisper_full_get_segment_text(rw->context, rws->index);
   return rb_str_new2(text);
 }
@@ -103,21 +132,89 @@ static VALUE
 ruby_whisper_segment_get_no_speech_prob(VALUE self)
 {
   ruby_whisper_segment *rws;
-  Data_Get_Struct(self, ruby_whisper_segment, rws);
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
   ruby_whisper *rw;
-  Data_Get_Struct(rws->context, ruby_whisper, rw);
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
   return DBL2NUM(whisper_full_get_segment_no_speech_prob(rw->context, rws->index));
 }
 
+/*
+ * call-seq:
+ *   deconstruct_keys(keys) -> hash
+ *
+ *  Possible keys: :start_time, :end_time, :text, :no_speech_prob, :speaker_turn_next
+ *
+ *   whisper.each_segment do |segment|
+ *     segment => {start_time:, end_time:, text:, no_speech_prob:, speaker_turn_next:}
+ *
+ *     puts "[#{start_time} --> #{end_time}] #{text} (no speech prob: #{no_speech_prob}#{speaker_turn_next ? ', speaker turns next' : ''})"
+ *   end
+ */
+static VALUE
+ruby_whisper_segment_deconstruct_keys(VALUE self, VALUE keys)
+{
+  ruby_whisper_segment *rws;
+  TypedData_Get_Struct(self, ruby_whisper_segment, &ruby_whisper_segment_type, rws);
+  ruby_whisper *rw;
+  TypedData_Get_Struct(rws->context, ruby_whisper, &ruby_whisper_type, rw);
+
+  VALUE hash = rb_hash_new();
+  long n_keys;
+  if (NIL_P(keys)) {
+    keys = key_names;
+    n_keys = N_KEY_NAMES;
+  } else {
+    n_keys = RARRAY_LEN(keys);
+    if (n_keys > N_KEY_NAMES) {
+      return hash;
+    }
+  }
+  for (int i = 0; i < n_keys; i++) {
+    VALUE key = rb_ary_entry(keys, i);
+    if (key == sym_start_time) {
+      rb_hash_aset(hash, key, ruby_whisper_segment_get_start_time(self));
+    }
+    if (key == sym_end_time) {
+      rb_hash_aset(hash, key, ruby_whisper_segment_get_end_time(self));
+    }
+    if (key == sym_text) {
+      rb_hash_aset(hash, key, ruby_whisper_segment_get_text(self));
+    }
+    if (key == sym_no_speech_prob) {
+      rb_hash_aset(hash, key, ruby_whisper_segment_get_no_speech_prob(self));
+    }
+    if (key == sym_speaker_turn_next) {
+      rb_hash_aset(hash, key, ruby_whisper_segment_get_speaker_turn_next(self));
+    }
+  }
+
+  return hash;
+}
+
 void
 init_ruby_whisper_segment(VALUE *mWhisper, VALUE *cContext)
 {
   cSegment  = rb_define_class_under(*mWhisper, "Segment", rb_cObject);
 
+  sym_start_time = ID2SYM(rb_intern("start_time"));
+  sym_end_time = ID2SYM(rb_intern("end_time"));
+  sym_text = ID2SYM(rb_intern("text"));
+  sym_no_speech_prob = ID2SYM(rb_intern("no_speech_prob"));
+  sym_speaker_turn_next = ID2SYM(rb_intern("speaker_turn_next"));
+  key_names = rb_ary_new3(
+    N_KEY_NAMES,
+    sym_start_time,
+    sym_end_time,
+    sym_text,
+    sym_no_speech_prob,
+    sym_speaker_turn_next
+  );
+
   rb_define_alloc_func(cSegment, ruby_whisper_segment_allocate);
   rb_define_method(cSegment, "start_time", ruby_whisper_segment_get_start_time, 0);
   rb_define_method(cSegment, "end_time", ruby_whisper_segment_get_end_time, 0);
-  rb_define_method(cSegment, "speaker_next_turn?", ruby_whisper_segment_get_speaker_turn_next, 0);
+  rb_define_method(cSegment, "speaker_turn_next?", ruby_whisper_segment_get_speaker_turn_next, 0);
   rb_define_method(cSegment, "text", ruby_whisper_segment_get_text, 0);
   rb_define_method(cSegment, "no_speech_prob", ruby_whisper_segment_get_no_speech_prob, 0);
+  rb_define_method(cSegment, "deconstruct_keys", ruby_whisper_segment_deconstruct_keys, 1);
 }

bindings/ruby/ext/ruby_whisper_transcribe.cpp

@@ -8,11 +8,15 @@
 extern "C" {
 #endif
 
+extern const rb_data_type_t ruby_whisper_type;
+extern const rb_data_type_t ruby_whisper_params_type;
+
 extern ID id_to_s;
 extern ID id_call;
+extern ID transcribe_option_names[1];
 
 extern void
-register_callbacks(ruby_whisper_params * rwp, VALUE * self);
+prepare_transcription(ruby_whisper_params * rwp, VALUE * self);
 
 /*
  * transcribe a single file
@@ -31,11 +35,16 @@ VALUE
 ruby_whisper_transcribe(int argc, VALUE *argv, VALUE self) {
   ruby_whisper *rw;
   ruby_whisper_params *rwp;
-  VALUE wave_file_path, blk, params;
+  VALUE wave_file_path, blk, params, kws;
+  VALUE opts[1];
 
-  rb_scan_args(argc, argv, "02&", &wave_file_path, &params, &blk);
-  Data_Get_Struct(self, ruby_whisper, rw);
-  Data_Get_Struct(params, ruby_whisper_params, rwp);
+  rb_scan_args_kw(RB_SCAN_ARGS_LAST_HASH_KEYWORDS, argc, argv, "2:&", &wave_file_path, &params, &kws, &blk);
+  rb_get_kwargs(kws, transcribe_option_names, 0, 1, opts);
+
+  int n_processors = opts[0] == Qundef ? 1 : NUM2INT(opts[0]);
+
+  TypedData_Get_Struct(self, ruby_whisper, &ruby_whisper_type, rw);
+  TypedData_Get_Struct(params, ruby_whisper_params, &ruby_whisper_params_type, rwp);
 
   if (!rb_respond_to(wave_file_path, id_to_s)) {
     rb_raise(rb_eRuntimeError, "Expected file path to wave file");
@@ -50,32 +59,33 @@ ruby_whisper_transcribe(int argc, VALUE *argv, VALUE self) {
     fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname_inp.c_str());
     return self;
   }
-  {
-    static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
+  // Commented out because it is work in progress
+  // {
+  //   static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
 
-    rwp->params.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
-      bool is_aborted = *(bool*)user_data;
-      return !is_aborted;
-    };
-    rwp->params.encoder_begin_callback_user_data = &is_aborted;
-  }
+  //   rwp->params.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
+  //     bool is_aborted = *(bool*)user_data;
+  //     return !is_aborted;
+  //   };
+  //   rwp->params.encoder_begin_callback_user_data = &is_aborted;
+  // }
 
-  register_callbacks(rwp, &self);
+  prepare_transcription(rwp, &self);
 
-  if (whisper_full_parallel(rw->context, rwp->params, pcmf32.data(), pcmf32.size(), 1) != 0) {
+  if (whisper_full_parallel(rw->context, rwp->params, pcmf32.data(), pcmf32.size(), n_processors) != 0) {
     fprintf(stderr, "failed to process audio\n");
     return self;
   }
+  if (NIL_P(blk)) {
+    return self;
+  }
   const int n_segments = whisper_full_n_segments(rw->context);
   VALUE output = rb_str_new2("");
   for (int i = 0; i < n_segments; ++i) {
     const char * text = whisper_full_get_segment_text(rw->context, i);
     output = rb_str_concat(output, rb_str_new2(text));
   }
-  VALUE idCall = id_call;
-  if (blk != Qnil) {
-    rb_funcall(blk, idCall, 1, output);
-  }
+  rb_funcall(blk, id_call, 1, output);
   return self;
 }
 #ifdef __cplusplus

bindings/ruby/ext/ruby_whisper_vad_params.c

@@ -0,0 +1,288 @@
+#include <ruby.h>
+#include "ruby_whisper.h"
+
+#define DEFINE_PARAM(param_name, nth) \
+  id_ ## param_name = rb_intern(#param_name); \
+  param_names[nth] = id_ ## param_name; \
+  rb_define_method(cVADParams, #param_name, ruby_whisper_vad_params_get_ ## param_name, 0); \
+  rb_define_method(cVADParams, #param_name "=", ruby_whisper_vad_params_set_ ## param_name, 1);
+
+#define NUM_PARAMS 6
+
+extern VALUE cVADParams;
+
+static size_t
+ruby_whisper_vad_params_memsize(const void *p)
+{
+  const struct ruby_whisper_vad_params *params = p;
+  size_t size = sizeof(params);
+  if (!params) {
+    return 0;
+  }
+  return size;
+}
+
+static ID param_names[NUM_PARAMS];
+static ID id_threshold;
+static ID id_min_speech_duration_ms;
+static ID id_min_silence_duration_ms;
+static ID id_max_speech_duration_s;
+static ID id_speech_pad_ms;
+static ID id_samples_overlap;
+
+const rb_data_type_t ruby_whisper_vad_params_type = {
+  "ruby_whisper_vad_params",
+  {0, 0, ruby_whisper_vad_params_memsize,},
+  0, 0,
+  0
+};
+
+static VALUE
+ruby_whisper_vad_params_s_allocate(VALUE klass)
+{
+  ruby_whisper_vad_params *rwvp;
+  VALUE obj = TypedData_Make_Struct(klass, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params = whisper_vad_default_params();
+  return obj;
+}
+
+/*
+ * Probability threshold to consider as speech.
+ *
+ * call-seq:
+ *   threshold = th -> th
+ */
+static VALUE
+ruby_whisper_vad_params_set_threshold(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.threshold = RFLOAT_VALUE(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_threshold(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return DBL2NUM(rwvp->params.threshold);
+}
+
+/*
+ * Min duration for a valid speech segment.
+ *
+ * call-seq:
+ *   min_speech_duration_ms = duration_ms -> duration_ms
+ */
+static VALUE
+ruby_whisper_vad_params_set_min_speech_duration_ms(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.min_speech_duration_ms = NUM2INT(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_min_speech_duration_ms(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return INT2NUM(rwvp->params.min_speech_duration_ms);
+}
+
+/*
+ * Min silence duration to consider speech as ended.
+ *
+ * call-seq:
+ *   min_silence_duration_ms = duration_ms -> duration_ms
+ */
+static VALUE
+ruby_whisper_vad_params_set_min_silence_duration_ms(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.min_silence_duration_ms = NUM2INT(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_min_silence_duration_ms(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return INT2NUM(rwvp->params.min_silence_duration_ms);
+}
+
+/*
+ * Max duration of a speech segment before forcing a new segment.
+ *
+ * call-seq:
+ *   max_speech_duration_s = duration_s -> duration_s
+ */
+static VALUE
+ruby_whisper_vad_params_set_max_speech_duration_s(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.max_speech_duration_s = RFLOAT_VALUE(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_max_speech_duration_s(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return DBL2NUM(rwvp->params.max_speech_duration_s);
+}
+
+/*
+ * Padding added before and after speech segments.
+ *
+ * call-seq:
+ *   speech_pad_ms = pad_ms -> pad_ms
+ */
+static VALUE
+ruby_whisper_vad_params_set_speech_pad_ms(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.speech_pad_ms = NUM2INT(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_speech_pad_ms(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return INT2NUM(rwvp->params.speech_pad_ms);
+}
+
+/*
+ * Overlap in seconds when copying audio samples from speech segment.
+ *
+ * call-seq:
+ *   samples_overlap = overlap -> overlap
+ */
+static VALUE
+ruby_whisper_vad_params_set_samples_overlap(VALUE self, VALUE value)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  rwvp->params.samples_overlap = RFLOAT_VALUE(value);
+  return value;
+}
+
+static VALUE
+ruby_whisper_vad_params_get_samples_overlap(VALUE self)
+{
+  ruby_whisper_vad_params *rwvp;
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+  return DBL2NUM(rwvp->params.samples_overlap);
+}
+
+static VALUE
+ruby_whisper_vad_params_equal(VALUE self, VALUE other)
+{
+  ruby_whisper_vad_params *rwvp1;
+  ruby_whisper_vad_params *rwvp2;
+
+  if (self == other) {
+    return Qtrue;
+  }
+
+  if (!rb_obj_is_kind_of(other, cVADParams)) {
+    return Qfalse;
+  }
+
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp1);
+  TypedData_Get_Struct(other, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp2);
+
+  if (rwvp1->params.threshold != rwvp2->params.threshold) {
+    return Qfalse;
+  }
+  if (rwvp1->params.min_speech_duration_ms != rwvp2->params.min_speech_duration_ms) {
+    return Qfalse;
+  }
+  if (rwvp1->params.min_silence_duration_ms != rwvp2->params.min_silence_duration_ms) {
+    return Qfalse;
+  }
+  if (rwvp1->params.max_speech_duration_s != rwvp2->params.max_speech_duration_s) {
+    return Qfalse;
+  }
+  if (rwvp1->params.speech_pad_ms != rwvp2->params.speech_pad_ms) {
+    return Qfalse;
+  }
+  if (rwvp1->params.samples_overlap != rwvp2->params.samples_overlap) {
+    return Qfalse;
+  }
+
+  return Qtrue;
+}
+
+#define SET_PARAM_IF_SAME(param_name) \
+  if (id == id_ ## param_name) { \
+    ruby_whisper_vad_params_set_ ## param_name(self, value); \
+    continue; \
+  }
+
+VALUE
+ruby_whisper_vad_params_initialize(int argc, VALUE *argv, VALUE self)
+{
+  VALUE kw_hash;
+  VALUE values[NUM_PARAMS] = {Qundef};
+  VALUE value;
+  ruby_whisper_vad_params *rwvp;
+  ID id;
+  int i;
+
+  TypedData_Get_Struct(self, ruby_whisper_vad_params, &ruby_whisper_vad_params_type, rwvp);
+
+  rb_scan_args_kw(RB_SCAN_ARGS_KEYWORDS, argc, argv, ":", &kw_hash);
+  if (NIL_P(kw_hash)) {
+    return self;
+  }
+
+  rb_get_kwargs(kw_hash, param_names, 0, NUM_PARAMS, values);
+
+  for (i = 0; i < NUM_PARAMS; i++) {
+    id = param_names[i];
+    value = values[i];
+    if (value == Qundef) {
+      continue;
+    }
+    SET_PARAM_IF_SAME(threshold)
+    SET_PARAM_IF_SAME(min_speech_duration_ms)
+    SET_PARAM_IF_SAME(min_silence_duration_ms)
+    SET_PARAM_IF_SAME(max_speech_duration_s)
+    SET_PARAM_IF_SAME(speech_pad_ms)
+    SET_PARAM_IF_SAME(samples_overlap)
+  }
+
+  return self;
+}
+
+#undef SET_PARAM_IF_SAME
+
+void
+init_ruby_whisper_vad_params(VALUE *mVAD)
+{
+  cVADParams = rb_define_class_under(*mVAD, "Params", rb_cObject);
+  rb_define_alloc_func(cVADParams, ruby_whisper_vad_params_s_allocate);
+  rb_define_method(cVADParams, "initialize", ruby_whisper_vad_params_initialize, -1);
+
+  DEFINE_PARAM(threshold, 0)
+  DEFINE_PARAM(min_speech_duration_ms, 1)
+  DEFINE_PARAM(min_silence_duration_ms, 2)
+  DEFINE_PARAM(max_speech_duration_s, 3)
+  DEFINE_PARAM(speech_pad_ms, 4)
+  DEFINE_PARAM(samples_overlap, 5)
+
+  rb_define_method(cVADParams, "==", ruby_whisper_vad_params_equal, 1);
+}
+
+#undef DEFINE_PARAM
+#undef NUM_PARAMS

bindings/ruby/ext/sources/CMakeGraphVizOptions.cmake

@@ -0,0 +1,8 @@
+set(GRAPHVIZ_EXECUTABLES FALSE)
+set(GRAPHVIZ_STATIC_LIBS TRUE)
+set(GRAPHVIZ_SHARED_LIBS FALSE)
+set(GRAPHVIZ_MODULE_LIBS FALSE)
+set(GRAPHVIZ_INTERFACE_LIBS FALSE)
+set(GRAPHVIZ_OBJECT_LIBS FALSE)
+set(GRAPHVIZ_UNKNOWN_LIBS FALSE)
+set(GRAPHVIZ_GENERATE_DEPENDERS FALSE)

bindings/ruby/extsources.rb

@@ -1,6 +1,40 @@
-require "yaml"
+require "pathname"
 
-sources = `git ls-files -z ../..`.split("\x0")
-paths = YAML.load_file("../../.github/workflows/bindings-ruby.yml")[true]["push"]["paths"]
-paths.delete "bindings/ruby/**"
-EXTSOURCES = (Dir.glob(paths, base: "../..").collect {|path| "../../#{path}"} << "../../LICENSE") & sources
+root = Pathname("..")/".."
+ignored_dirs = %w[
+  .devops
+  .github
+  ci
+  examples/wchess/wchess.wasm
+  examples/whisper.android
+  examples/whisper.android.java
+  examples/whisper.objc
+  examples/whisper.swiftui
+  grammars
+  models
+  samples
+  scripts
+].collect {|dir| root/dir}
+ignored_files = %w[
+  AUTHORS
+  Makefile
+  README.md
+  README_sycl.md
+  .gitignore
+  .gitmodules
+  .dockerignore
+  whisper.nvim
+  twitch.sh
+  yt-wsp.sh
+  close-issue.yml
+]
+
+EXTSOURCES =
+  `git ls-files -z #{root}`.split("\x0")
+    .collect {|file| Pathname(file)}
+    .reject {|file|
+      ignored_dirs.any? {|dir| file.descend.any? {|desc| desc == dir}} ||
+        ignored_files.include?(file.basename.to_path) ||
+        (file.descend.to_a[1] != root && file.descend.to_a[1] != Pathname("..")/"javascript")
+    }
+    .collect(&:to_path)

bindings/ruby/lib/whisper/context.rb

@@ -0,0 +1,15 @@
+module Whisper
+  class Context
+    def to_srt
+      each_segment.with_index.reduce("") {|srt, (segment, index)|
+        srt << "#{index + 1}\n#{segment.to_srt_cue}\n"
+      }
+    end
+
+    def to_webvtt
+      each_segment.with_index.reduce("WEBVTT\n\n") {|webvtt, (segment, index)|
+        webvtt << "#{index + 1}\n#{segment.to_webvtt_cue}\n"
+      }
+    end
+  end
+end

bindings/ruby/lib/whisper/model/uri.rb

@@ -34,7 +34,7 @@ module Whisper
                when /darwin/
                  Pathname(Dir.home)/"Library/Caches"
                else
-                 ENV.key?("XDG_CACHE_HOME") ? ENV["XDG_CACHE_HOME"] : Pathname(Dir.home)/".cache"
+                 ENV.key?("XDG_CACHE_HOME") ? Pathname(ENV["XDG_CACHE_HOME"]) : Pathname(Dir.home)/".cache"
                end
         base/"whisper.cpp"
       end
@@ -53,8 +53,10 @@ module Whisper
           http.request request do |response|
             case response
             when Net::HTTPNotModified
-            # noop
+              # noop
             when Net::HTTPOK
+              return if !response.key?("last-modified") && cache_path.exist?
+
               download response
             when Net::HTTPRedirection
               request URI(response["location"]), headers
@@ -68,7 +70,7 @@ module Whisper
       rescue => err
         if cache_path.exist?
           warn err
-        # Use cache file
+          # Use cache file
         else
           raise
         end
@@ -128,6 +130,44 @@ module Whisper
       end
     end
 
+    class ZipURI < URI
+      def cache
+        zip_path = super
+        dest = unzipped_path
+        return if dest.exist? && dest.mtime >= zip_path.mtime
+        escaping dest do
+          system "unzip", "-q", "-d", zip_path.dirname.to_path, zip_path.to_path, exception: true
+        end
+        zip_path
+      end
+
+      def clear_cache
+        super
+        unzipped_path.rmtree if unzipped_path.exist?
+      end
+
+      private
+
+      def unzipped_path
+        cache_path.sub_ext("")
+      end
+
+      def escaping(path)
+        escaped = Pathname("#{path}.removing")
+        if path.exist?
+          escaped.rmtree if escaped.exist?
+          path.rename escaped
+        end
+        yield
+      ensure
+        if path.exist?
+          escaped.rmtree if escaped.exist?
+        else
+          escaped.rename path if escaped.exist?
+        end
+      end
+    end
+
     @pre_converted_models = %w[
       tiny
       tiny.en
@@ -163,8 +203,31 @@ module Whisper
       models[name] = URI.new("https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-#{name}.bin")
     }
 
+    %w[
+      silero-v5.1.2
+    ].each do |name|
+      @pre_converted_models[name] = URI.new("https://huggingface.co/ggml-org/whisper-vad/resolve/main/ggml-#{name}.bin")
+    end
+
+    @coreml_compiled_models = %w[
+      tiny
+      tiny.en
+      base
+      base.en
+      small
+      small.en
+      medium
+      medium.en
+      large-v1
+      large-v2
+      large-v3
+      large-v3-turbo
+    ].each_with_object({}) do |name, models|
+      models[@pre_converted_models[name]] = ZipURI.new("https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-#{name}-encoder.mlmodelc.zip")
+    end
+
     class << self
-      attr_reader :pre_converted_models
+      attr_reader :pre_converted_models, :coreml_compiled_models
     end
   end
 end

bindings/ruby/lib/whisper/segment.rb

@@ -0,0 +1,58 @@
+module Whisper
+  class Segment
+    SRT_ESCAPES = {
+      "&" => "&",
+      "<" => "&lt;",
+      ">" => "&gt;",
+    }
+    SRT_ESCAPES_RE = Regexp.union(SRT_ESCAPES.keys)
+    private_constant :SRT_ESCAPES, :SRT_ESCAPES_RE
+
+    def to_srt_cue
+      "#{srt_start_time} --> #{srt_end_time}\n#{srt_text}\n"
+    end
+
+    def to_webvtt_cue
+      "#{webvtt_start_time} --> #{webvtt_end_time}\n#{webvtt_text}\n"
+    end
+
+    private
+
+    def time_to_a(time)
+      sec, decimal_part = time.divmod(1000)
+      min, sec = sec.divmod(60)
+      hour, min = min.divmod(60)
+      [hour, min, sec, decimal_part]
+    end
+
+    def srt_time(time)
+      "%02d:%02d:%02d,%03d" % time_to_a(time)
+    end
+
+    def srt_start_time
+      srt_time(start_time)
+    end
+
+    def srt_end_time
+      srt_time(end_time)
+    end
+
+    def srt_text
+      text.gsub(SRT_ESCAPES_RE, SRT_ESCAPES)
+    end
+
+    def webvtt_time(time)
+      "%02d:%02d:%02d.%03d" % time_to_a(time)
+    end
+
+    def webvtt_start_time
+      webvtt_time(start_time)
+    end
+
+    def webvtt_end_time
+      webvtt_time(end_time)
+    end
+
+    alias webvtt_text srt_text
+  end
+end

bindings/ruby/sig/whisper.rbs

@@ -7,8 +7,10 @@ module Whisper
   type log_callback = ^(Integer level, String message, Object user_data) -> void
   type new_segment_callback = ^(Whisper::Context, void, Integer n_new, Object user_data) -> void
   type progress_callback = ^(Whisper::Context, void, Integer progress, Object user_data) -> void
+  type encoder_begin_callback = ^(Whisper::Context, void, Object user_data) -> void
   type abort_callback = ^(Whisper::Context, void, Object user_data) -> boolish
 
+  VERSION: String
   LOG_LEVEL_NONE: Integer
   LOG_LEVEL_INFO: Integer
   LOG_LEVEL_WARN: Integer
@@ -21,11 +23,23 @@ module Whisper
   def self.lang_str: (Integer id) -> String
   def self.lang_str_full: (Integer id) -> String
   def self.log_set: (log_callback, Object? user_data) -> log_callback
+  def self.system_info_str: () -> String
 
   class Context
-    def self.new: (string | _ToPath | ::URI::HTTP) -> instance
-    def transcribe: (string, Params) -> self
-                  | (string, Params) { (String) -> void } -> self
+    def self.new: (String | path | ::URI::HTTP) -> instance
+
+    # transcribe a single file
+    # can emit to a block results
+    #
+    #     params = Whisper::Params.new
+    #     params.duration = 60_000
+    #     whisper.transcribe "path/to/audio.wav", params do |text|
+    #       puts text
+    #     end
+    #
+    def transcribe: (string, Params, ?n_processors: Integer) -> self
+                  | (string, Params, ?n_processors: Integer) { (String) -> void } -> self
+
     def model_n_vocab: () -> Integer
     def model_n_audio_ctx: () -> Integer
     def model_n_audio_state: () -> Integer
@@ -34,22 +48,78 @@ module Whisper
     def model_n_mels: () -> Integer
     def model_ftype: () -> Integer
     def model_type: () -> String
+
+    # Yields each Whisper::Segment:
+    #
+    #     whisper.transcribe("path/to/audio.wav", params)
+    #     whisper.each_segment do |segment|
+    #       puts segment.text
+    #     end
+    #
+    # Returns an Enumerator if no block given:
+    #
+    #     whisper.transcribe("path/to/audio.wav", params)
+    #     enum = whisper.each_segment
+    #     enum.to_a # => [#<Whisper::Segment>, ...]
+    #
     def each_segment: { (Segment) -> void } -> void
                     | () -> Enumerator[Segment]
+
     def model: () -> Model
     def full_get_segment: (Integer nth) -> Segment
     def full_n_segments: () -> Integer
+
+    # Language ID, which can be converted to string by Whisper.lang_str and Whisper.lang_str_full.
+    #
     def full_lang_id: () -> Integer
+
+    # Start time of a segment indexed by +segment_index+ in centiseconds (10 times milliseconds).
+    #
+    #     full_get_segment_t0(3) # => 1668 (16680 ms)
+    #
     def full_get_segment_t0: (Integer) -> Integer
+
+    # End time of a segment indexed by +segment_index+ in centiseconds (10 times milliseconds).
+    #
+    #     full_get_segment_t1(3) # => 1668 (16680 ms)
+    #
     def full_get_segment_t1: (Integer) -> Integer
+
+    # Whether the next segment indexed by +segment_index+ is predicated as a speaker turn.
+    #
+    #     full_get_segment_speacker_turn_next(3) # => true
+    #
     def full_get_segment_speaker_turn_next: (Integer) -> (true | false)
+
+    # Text of a segment indexed by +segment_index+.
+    #
+    #     full_get_segment_text(3) # => "ask not what your country can do for you, ..."
+    #
     def full_get_segment_text: (Integer) -> String
+
     def full_get_segment_no_speech_prob: (Integer) -> Float
+
+    # Run the entire model: PCM -> log mel spectrogram -> encoder -> decoder -> text
+    # Not thread safe for same context
+    # Uses the specified decoding strategy to obtain the text.
+    #
+    # The second argument +samples+ must be an array of samples, respond to :length, or be a MemoryView of an array of float. It must be 32 bit float PCM audio data.
+    #
     def full: (Params, Array[Float] samples, ?Integer n_samples) -> self
             | (Params, _Samples, ?Integer n_samples) -> self
+
+    # Split the input audio in chunks and process each chunk separately using whisper_full_with_state()
+    # Result is stored in the default state of the context
+    # Not thread safe if executed in parallel on the same context.
+    # It seems this approach can offer some speedup in some cases.
+    # However, the transcription accuracy can be worse at the beginning and end of each chunk.
+    #
     def full_parallel: (Params, Array[Float], ?Integer n_samples) -> self
                      | (Params, _Samples, ?Integer n_samples) -> self
                      | (Params, _Samples, ?Integer? n_samples, Integer n_processors) -> self
+
+    def to_srt: () -> String
+    def to_webvtt: () -> String
   end
 
   class Params
@@ -82,76 +152,246 @@ module Whisper
       ?new_segment_callback_user_data: Object,
       ?progress_callback: progress_callback,
       ?progress_callback_user_data: Object,
+      ?encoder_begin_callback: encoder_begin_callback,
+      ?encoder_begin_callback_user_data: Object,
       ?abort_callback: abort_callback,
-      ?abort_callback_user_data: Object
+      ?abort_callback_user_data: Object,
+      ?vad: boolish,
+      ?vad_model_path: path | URI,
+      ?vad_params: Whisper::VAD::Params
     ) -> instance
+
+    # params.language = "auto" | "en", etc...
+    #
     def language=: (String) -> String # TODO: Enumerate lang names
+
     def language: () -> String
     def translate=: (boolish) -> boolish
     def translate: () -> (true | false)
     def no_context=: (boolish) -> boolish
+
+    # If true, does not use past transcription (if any) as initial prompt for the decoder.
+    #
     def no_context: () -> (true | false)
+
     def single_segment=: (boolish) -> boolish
+
+    # If true, forces single segment output (useful for streaming).
+    #
     def single_segment: () -> (true | false)
+
     def print_special=: (boolish) -> boolish
+
+    # If true, prints special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.).
+    #
     def print_special: () -> (true | false)
+
     def print_progress=: (boolish) -> boolish
+
+    # If true, prints progress information.
+    #
     def print_progress: () -> (true | false)
+
     def print_realtime=: (boolish) -> boolish
+
+    # If true, prints results from within whisper.cpp. (avoid it, use callback instead)
+    #
     def print_realtime: () -> (true | false)
+
+    # If true, prints timestamps for each text segment when printing realtime.
+    #
     def print_timestamps=: (boolish) -> boolish
+
     def print_timestamps: () -> (true | false)
+
     def suppress_blank=: (boolish) -> boolish
+
+    # If true, suppresses blank outputs.
+    #
     def suppress_blank: () -> (true | false)
+
     def suppress_nst=: (boolish) -> boolish
+
+    # If true, suppresses non-speech-tokens.
+    #
     def suppress_nst: () -> (true | false)
+
     def token_timestamps=: (boolish) -> boolish
+
+    # If true, enables token-level timestamps.
+    #
     def token_timestamps: () -> (true | false)
+
     def split_on_word=: (boolish) -> boolish
+
+    # If true, split on word rather than on token (when used with max_len).
+    #
     def split_on_word: () -> (true | false)
+
     def initial_prompt=: (_ToS) -> _ToS
+
+    # Tokens to provide to the whisper decoder as initial prompt
+    # these are prepended to any existing text context from a previous call
+    # use whisper_tokenize() to convert text to tokens.
+    # Maximum of whisper_n_text_ctx()/2 tokens are used (typically 224).
+    #
     def initial_prompt: () -> (String | nil)
+
     def diarize=: (boolish) -> boolish
+
+    # If true, enables diarization.
+    #
     def diarize: () -> (true | false)
+
     def offset=: (Integer) -> Integer
+
+    # Start offset in ms.
+    #
     def offset: () -> Integer
+
     def duration=: (Integer) -> Integer
+
+    # Audio duration to process in ms.
+    #
     def duration: () -> Integer
+
     def max_text_tokens=: (Integer) -> Integer
+
+    # Max tokens to use from past text as prompt for the decoder.
+    #
     def max_text_tokens: () -> Integer
+
     def temperature=: (Float) -> Float
     def temperature: () -> Float
     def max_initial_ts=: (Float) -> Float
+
+    # See https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
+    #
     def max_initial_ts: () -> Float
+
     def length_penalty=: (Float) -> Float
     def length_penalty: () -> Float
     def temperature_inc=: (Float) -> Float
     def temperature_inc: () -> Float
     def entropy_thold=: (Float) -> Float
+
+    # Similar to OpenAI's "compression_ratio_threshold"
+    #
     def entropy_thold: () -> Float
+
     def logprob_thold=: (Float) -> Float
     def logprob_thold: () -> Float
     def no_speech_thold=: (Float) -> Float
     def no_speech_thold: () -> Float
+
+    # Sets new segment callback, called for every newly generated text segment.
+    #
+    #     params.new_segment_callback = ->(context, _, n_new, user_data) {
+    #       # ...
+    #     }
+    #
     def new_segment_callback=: (new_segment_callback) -> new_segment_callback
     def new_segment_callback: () -> (new_segment_callback | nil)
+
+    # Sets user data passed to the last argument of new segment callback.
+    #
     def new_segment_callback_user_data=: (Object) -> Object
+
     def new_segment_callback_user_data: () -> Object
+
+    # Sets progress callback, called on each progress update.
+    #
+    #     params.new_segment_callback = ->(context, _, progress, user_data) {
+    #       # ...
+    #     }
+    #
+    # +progress+ is an Integer between 0 and 100.
+    #
     def progress_callback=: (progress_callback) -> progress_callback
+
     def progress_callback: () -> (progress_callback | nil)
+
+    # Sets user data passed to the last argument of progress callback.
+    #
     def progress_callback_user_data=: (Object) -> Object
+
     def progress_callback_user_data: () -> Object
+
+    # Sets encoder begin callback, called when the encoder starts.
+    #
+    def encoder_begin_callback=: (encoder_begin_callback) -> encoder_begin_callback
+
+    def encoder_begin_callback: () -> (encoder_begin_callback | nil)
+
+    # Sets user data passed to the last argument of encoder begin callback.
+    #
+    def encoder_begin_callback_user_data=: (Object) -> Object
+
+    def encoder_begin_callback_user_data: () -> Object
+
+    # Sets abort callback, called to check if the process should be aborted.
+    #
+    #     params.abort_callback = ->(user_data) {
+    #       # ...
+    #     }
+    #
+    #
     def abort_callback=: (abort_callback) -> abort_callback
+
     def abort_callback: () -> (abort_callback | nil)
+
+    # Sets user data passed to the last argument of abort callback.
+    #
     def abort_callback_user_data=: (Object) -> Object
+
     def abort_callback_user_data: () -> Object
+
+    # Enable VAD
+    #
+    def vad=: (boolish) -> boolish
+
+    def vad: () -> (true | false)
+
+    # Path to the VAD model
+    def vad_model_path=: (path | URI | nil) -> (path | URI | nil)
+
+    def vad_model_path: () -> (String | nil)
+
+    def vad_params=: (Whisper::VAD::Params) -> Whisper::VAD::Params
+    def vad_params: () -> (Whisper::VAD::Params)
+
+    # Hook called on new segment. Yields each Whisper::Segment.
+    #
+    #     whisper.on_new_segment do |segment|
+    #       # ...
+    #     end
+    #
     def on_new_segment: { (Segment) -> void } -> void
+
+    # Hook called on progress update. Yields each progress Integer between 0 and 100.
+    #
     def on_progress: { (Integer progress) -> void } -> void
+
+    # Hook called on encoder starts.
+    #
+    def on_encoder_begin: { () -> void } -> void
+
+    # Call block to determine whether abort or not. Return +true+ when you want to abort.
+    #
+    #     params.abort_on do
+    #       if some_condition
+    #         true # abort
+    #       else
+    #         false # continue
+    #       end
+    #     end
+    #
     def abort_on: { (Object user_data) -> boolish } -> void
   end
 
   class Model
     def self.pre_converted_models: () -> Hash[String, Model::URI]
+    def self.coreml_compiled_models: () -> Hash[Model::URI, Model::ZipURI]
     def self.new: () -> instance
     def n_vocab: () -> Integer
     def n_audio_ctx: () -> Integer
@@ -167,18 +407,99 @@ module Whisper
     def type: () -> String
 
     class URI
-      def self.new: (string | ::URI::HTTP) -> self
+      def self.new: (string | ::URI::HTTP) -> instance
       def to_path: -> String
       def clear_cache: -> void
     end
+
+    class ZipURI < URI
+      def cache: () -> Pathname
+      def clear_cache: () -> void
+    end
   end
 
   class Segment
+    type deconstructed_keys = {
+      start_time: (Integer | nil),
+      end_time: (Integer | nil),
+      text: (String | nil),
+      no_speech_prob: (Float | nil),
+      speaker_turn_next: (true | false | nil)
+    }
+
+    # Start time in milliseconds.
+    #
     def start_time: () -> Integer
+
+    # End time in milliseconds.
+    #
     def end_time: () -> Integer
-    def speaker_next_turn?: () -> (true | false)
+
+    # Whether the next segment is predicted as a speaker turn.
+    def speaker_turn_next?: () -> (true | false)
+
     def text: () -> String
     def no_speech_prob: () -> Float
+    def to_srt_cue: () -> String
+    def to_webvtt_cue: () -> String
+
+    #  Possible keys: :start_time, :end_time, :text, :no_speech_prob, :speaker_turn_next
+    #
+    #      whisper.each_segment do |segment|
+    #        segment => {start_time:, end_time:, text:, no_speech_prob:, speaker_turn_next:}
+    #
+    #        puts "[#{start_time} --> #{end_time}] #{text} (no speech prob: #{no_speech_prob}#{speaker_turn_next ? ', speaker turns next' : ''})"
+    #      end
+    def deconstruct_keys: (Array[:start_time | :end_time | :text | :no_speech_prob | :speaker_turn_next] | nil) -> deconstructed_keys
+  end
+
+  module VAD
+    class Params
+      def self.new: (
+        ?threshold: Float,
+        ?min_speech_duration_ms: Integer,
+        ?min_silence_duration_ms: Integer,
+        ?max_speech_duration_s: Float,
+        ?speech_pad_ms: Integer,
+        ?samples_overlap: Float
+      ) -> instance
+
+      # Probability threshold to consider as speech.
+      #
+      def threshold=: (Float) -> Float
+
+      def threshold: () -> Float
+
+      # Min duration for a valid speech segment.
+      #
+      def min_speech_duration_ms=: (Integer) -> Integer
+
+      def min_speech_duration_ms: () -> Integer
+
+      # Min silence duration to consider speech as ended.
+      #
+      def min_silence_duration_ms=: (Integer) -> Integer
+
+      def min_silence_duration_ms: () -> Integer
+
+      # Max duration of a speech segment before forcing a new segment.
+      def max_speech_duration_s=: (Float) -> Float
+
+      def max_speech_duration_s: () -> Float
+
+      # Padding added before and after speech segments.
+      #
+      def speech_pad_ms=: (Integer) -> Integer
+
+      def speech_pad_ms: () -> Integer
+
+      # Overlap in seconds when copying audio samples from speech segment.
+      #
+      def samples_overlap=: (Float) -> Float
+
+      def samples_overlap: () -> Float
+      def ==: (Params) -> (true | false)
+    end
   end
 
   class Error < StandardError

bindings/ruby/test/helper.rb

@@ -3,12 +3,12 @@ require "whisper"
 require_relative "jfk_reader/jfk_reader"
 
 class TestBase < Test::Unit::TestCase
-  AUDIO = File.join(__dir__, "..", "..", "..", "samples", "jfk.wav")
+  AUDIO = File.join(__dir__, "fixtures", "jfk.wav")
 
   class << self
-    attr_reader :whisper
+    def whisper
+      return @whisper if @whisper
 
-    def startup
       @whisper = Whisper::Context.new("base.en")
       params = Whisper::Params.new
       params.print_timestamps = false

bindings/ruby/test/test_callback.rb

@@ -111,6 +111,48 @@ class TestCallback < TestBase
     assert_equal 100, last
   end
 
+  def test_encoder_begin_callback
+    i = 0
+    @params.encoder_begin_callback = ->(context, state, user_data) {
+      i += 1
+    }
+    @whisper.transcribe(@audio, @params)
+    assert i > 0
+  end
+
+  def test_encoder_begin_callback_abort
+    logs = []
+    Whisper.log_set -> (level, buffer, user_data) {
+      logs << buffer if level == Whisper::LOG_LEVEL_ERROR
+    }, logs
+    @params.encoder_begin_callback = ->(context, state, user_data) {
+      return false
+    }
+    @whisper.transcribe(@audio, @params)
+    assert_match(/encoder_begin_callback returned false - aborting/, logs.join)
+    Whisper.log_set ->(level, buffer, user_data) {}, nil
+  end
+
+  def test_encoder_begin_callback_user_data
+    udata = Object.new
+    @params.encoder_begin_callback_user_data = udata
+    yielded = nil
+    @params.encoder_begin_callback = ->(context, state, user_data) {
+      yielded = user_data
+    }
+    @whisper.transcribe(@audio, @params)
+    assert_same udata, yielded
+  end
+
+  def test_on_encoder_begin
+    i = 0
+    @params.on_encoder_begin do
+      i += 1
+    end
+    @whisper.transcribe(@audio, @params)
+    assert i > 0
+  end
+
   def test_abort_callback
     i = 0
     @params.abort_callback = ->(user_data) {

bindings/ruby/test/test_model.rb

@@ -106,4 +106,13 @@ class TestModel < TestBase
     assert_equal 1, model.ftype
     assert_equal "base", model.type
   end
+
+  def test_coreml_model_auto_download
+    uri = Whisper::Model.coreml_compiled_models[Whisper::Model.pre_converted_models["tiny"]]
+    model_path = Pathname(uri.to_path).sub_ext("")
+    model_path.rmtree if model_path.exist?
+
+    uri.cache
+    assert_path_exist model_path
+  end
 end

bindings/ruby/test/test_package.rb

@@ -0,0 +1,51 @@
+require_relative "helper"
+require 'tempfile'
+require 'tmpdir'
+require 'shellwords'
+
+class TestPackage < TestBase
+  def test_build
+    Tempfile.create do |file|
+      assert system("gem", "build", "whispercpp.gemspec", "--output", file.to_path.shellescape, exception: true)
+      assert file.size > 0
+      assert_path_exist file.to_path
+    end
+  end
+
+  sub_test_case "Building binary on installation" do
+    def setup
+      system "rake", "build", exception: true
+    end
+
+    def test_install
+      gemspec = Gem::Specification.load("whispercpp.gemspec")
+      Dir.mktmpdir do |dir|
+        system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{gemspec.file_name.shellescape}", exception: true
+        assert_installed dir, gemspec.version
+      end
+    end
+
+    def test_install_with_coreml
+      omit_unless RUBY_PLATFORM.match?(/darwin/) do
+        gemspec = Gem::Specification.load("whispercpp.gemspec")
+        Dir.mktmpdir do |dir|
+          system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{gemspec.file_name.shellescape}", "--", "--enable-whisper-coreml", exception: true
+          assert_installed dir, gemspec.version
+          libdir = File.join(dir, "gems", "#{gemspec.name}-#{gemspec.version}", "lib")
+          assert_nothing_raised do
+            system "ruby", "-I", libdir, "-r", "whisper", "-e", "Whisper::Context.new('tiny')", exception: true
+          end
+          assert_match(/COREML = 1/, `ruby -I #{libdir.shellescape} -r whisper -e 'puts Whisper.system_info_str'`)
+        end
+      end
+    end
+
+    private
+
+    def assert_installed(dir, version)
+      assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", "whisper.#{RbConfig::CONFIG["DLEXT"]}")
+      assert_path_exist File.join(dir, "gems/whispercpp-#{version}/LICENSE")
+      assert_path_not_exist File.join(dir, "gems/whispercpp-#{version}/ext/build")
+    end
+  end
+end

bindings/ruby/test/test_params.rb

@@ -32,6 +32,9 @@ class TestParams < TestBase
     :progress_callback_user_data,
     :abort_callback,
     :abort_callback_user_data,
+    :vad,
+    :vad_model_path,
+    :vad_params,
   ]
 
   def setup
@@ -191,6 +194,50 @@ class TestParams < TestBase
     assert_in_delta 0.2, @params.no_speech_thold
   end
 
+  def test_vad
+    assert_false @params.vad
+    @params.vad = true
+    assert_true @params.vad
+  end
+
+  def test_vad_model_path
+    assert_nil @params.vad_model_path
+    @params.vad_model_path = "silero-v5.1.2"
+    assert_equal Whisper::Model.pre_converted_models["silero-v5.1.2"].to_path, @params.vad_model_path
+  end
+
+  def test_vad_model_path_with_nil
+    @params.vad_model_path = "silero-v5.1.2"
+    @params.vad_model_path = nil
+    assert_nil @params.vad_model_path
+  end
+
+  def test_vad_model_path_with_invalid
+    assert_raise TypeError do
+      @params.vad_model_path = Object.new
+    end
+  end
+
+  def test_vad_model_path_with_URI_string
+    @params.vad_model_path = "https://huggingface.co/ggml-org/whisper-vad/resolve/main/ggml-silero-v5.1.2.bin"
+    assert_equal @params.vad_model_path, Whisper::Model.pre_converted_models["silero-v5.1.2"].to_path
+  end
+
+  def test_vad_model_path_with_URI
+    @params.vad_model_path = URI("https://huggingface.co/ggml-org/whisper-vad/resolve/main/ggml-silero-v5.1.2.bin")
+    assert_equal @params.vad_model_path, Whisper::Model.pre_converted_models["silero-v5.1.2"].to_path
+  end
+
+  def test_vad_params
+    assert_kind_of Whisper::VAD::Params, @params.vad_params
+    default_params = @params.vad_params
+    assert_same default_params, @params.vad_params
+    assert_equal 0.5, default_params.threshold
+    new_params = Whisper::VAD::Params.new
+    @params.vad_params = new_params
+    assert_same new_params, @params.vad_params
+  end
+
   def test_new_with_kw_args
     params = Whisper::Params.new(language: "es")
     assert_equal "es", params.language
@@ -225,6 +272,10 @@ class TestParams < TestBase
               proc {}
             in [/_user_data\Z/, *]
               Object.new
+            in [:vad_model_path, *]
+              Whisper::Model.pre_converted_models["silero-v5.1.2"].to_path
+            in [:vad_params, *]
+              Whisper::VAD::Params.new
             end
     params = Whisper::Params.new(param => value)
     if Float === value

bindings/ruby/test/test_segment.rb

@@ -0,0 +1,146 @@
+require_relative "helper"
+
+class TestSegment < TestBase
+  def test_iteration
+    whisper.each_segment do |segment|
+      assert_instance_of Whisper::Segment, segment
+    end
+  end
+
+  def test_enumerator
+    enum = whisper.each_segment
+    assert_instance_of Enumerator, enum
+    enum.to_a.each_with_index do |segment, index|
+      assert_instance_of Whisper::Segment, segment
+      assert_kind_of Integer, index
+    end
+  end
+
+  def test_start_time
+    i = 0
+    whisper.each_segment do |segment|
+      assert_equal 0, segment.start_time if i == 0
+      i += 1
+    end
+  end
+
+  def test_end_time
+    i = 0
+    whisper.each_segment do |segment|
+      assert_equal whisper.full_get_segment_t1(i) * 10, segment.end_time
+      i += 1
+    end
+  end
+
+  def test_no_speech_prob
+    no_speech_prob = nil
+    whisper.each_segment do |segment|
+      no_speech_prob = segment.no_speech_prob
+    end
+    assert no_speech_prob > 0.0
+  end
+
+  def test_on_new_segment
+    params = Whisper::Params.new
+    seg = nil
+    index = 0
+    params.on_new_segment do |segment|
+      assert_instance_of Whisper::Segment, segment
+      if index == 0
+        seg = segment
+        assert_equal 0, segment.start_time
+        assert_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
+      end
+      index += 1
+    end
+    whisper.transcribe(AUDIO, params)
+    assert_equal 0, seg.start_time
+    assert_match(/ask not what your country can do for you, ask what you can do for your country/, seg.text)
+  end
+
+  def test_on_new_segment_twice
+    params = Whisper::Params.new
+    seg = nil
+    params.on_new_segment do |segment|
+      seg = segment
+      return
+    end
+    params.on_new_segment do |segment|
+      assert_same seg, segment
+      return
+    end
+    whisper.transcribe(AUDIO, params)
+  end
+
+  def test_transcription_after_segment_retrieved
+    params = Whisper::Params.new
+    segment = whisper.each_segment.first
+    assert_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
+
+    whisper.transcribe(AUDIO, Whisper::Params.new(offset: 5000))
+    assert_not_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
+    assert_match(/what you can do for your country/i, segment.text)
+  end
+
+  def test_pattern_matching
+    segment = whisper.each_segment.first
+    segment => {start_time:, end_time:, text:, no_speech_prob:, speaker_turn_next:}
+
+    assert_equal segment.start_time, start_time
+    assert_equal segment.end_time, end_time
+    assert_equal segment.text, text
+    assert_equal segment.no_speech_prob, no_speech_prob
+    assert_equal segment.speaker_turn_next?, speaker_turn_next
+  end
+
+  def test_pattern_matching_partial
+    segment = whisper.each_segment.first
+    segment => {start_time:, end_time:, text:}
+
+    assert_equal segment.start_time, start_time
+    assert_equal segment.end_time, end_time
+    assert_equal segment.text, text
+  end
+
+  def test_deconstruct_keys
+    segment = whisper.each_segment.first
+    expected = {
+      start_time: segment.start_time,
+      end_time: segment.end_time,
+      text: segment.text,
+      no_speech_prob: segment.no_speech_prob,
+      speaker_turn_next: segment.speaker_turn_next?
+    }
+    assert_equal expected, segment.deconstruct_keys([:start_time, :end_time, :text, :no_speech_prob, :speaker_turn_next])
+  end
+
+  def test_deconstruct_keys_non_existent
+    omit "Undefined behavior"
+
+    segment = whisper.each_segment.first
+
+    assert_equal({}, segment.deconstruct_keys([:non_existent]))
+  end
+
+  def test_deconstruct_keys_too_many_keys
+    omit "Undefined behavior"
+
+    segment = whisper.each_segment.first
+
+    assert_equal({}, segment.deconstruct_keys([:start_time, :end_time, :text, :no_speech_prob, :speaker_turn_next, :extra_key]))
+  end
+
+  def test_deconstruct_keys_includes_non_existent_keys_not_too_many
+    omit "Undefined behavior"
+
+    segment = whisper.each_segment.first
+
+    expected = {
+      start_time: segment.start_time,
+      end_time: segment.end_time,
+      text: segment.text,
+      no_speech_prob: segment.no_speech_prob
+    }
+    assert_equal(expected, segment.deconstruct_keys([:start_time, :end_time, :text, :no_speech_prob, :non_existent]))
+  end
+end

bindings/ruby/test/test_vad.rb

@@ -0,0 +1,19 @@
+require_relative "helper"
+
+class TestVAD < TestBase
+  def setup
+    @whisper = Whisper::Context.new("base.en")
+    vad_params = Whisper::VAD::Params.new
+    @params = Whisper::Params.new(
+      vad: true,
+      vad_model_path: "silero-v5.1.2",
+      vad_params:
+    )
+  end
+
+  def test_transcribe
+    @whisper.transcribe(TestBase::AUDIO, @params) do |text|
+      assert_match(/ask not what your country can do for you[,.] ask what you can do for your country/i, text)
+    end
+  end
+end

bindings/ruby/test/test_vad_params.rb

@@ -0,0 +1,103 @@
+require_relative "helper"
+
+class TestVADParams < TestBase
+  PARAM_NAMES = [
+    :threshold,
+    :min_speech_duration_ms,
+    :min_silence_duration_ms,
+    :max_speech_duration_s,
+    :speech_pad_ms,
+    :samples_overlap
+  ]
+
+  def setup
+    @params = Whisper::VAD::Params.new
+  end
+
+  def test_new
+    params = Whisper::VAD::Params.new
+    assert_kind_of Whisper::VAD::Params, params
+  end
+
+  def test_threshold
+    assert_in_delta @params.threshold, 0.5
+    @params.threshold = 0.7
+    assert_in_delta @params.threshold, 0.7
+  end
+
+  def test_min_speech_duration
+    pend
+  end
+
+  def test_min_speech_duration_ms
+    assert_equal 250, @params.min_speech_duration_ms
+    @params.min_speech_duration_ms = 500
+    assert_equal 500, @params.min_speech_duration_ms
+  end
+
+  def test_min_silence_duration_ms
+    assert_equal 100, @params.min_silence_duration_ms
+    @params.min_silence_duration_ms = 200
+    assert_equal 200, @params.min_silence_duration_ms
+  end
+
+  def test_max_speech_duration
+    pend
+  end
+
+  def test_max_speech_duration_s
+    assert @params.max_speech_duration_s >= 10e37 # Defaults to FLT_MAX
+    @params.max_speech_duration_s = 60.0
+    assert_equal 60.0, @params.max_speech_duration_s
+  end
+
+  def test_speech_pad_ms
+    assert_equal 30, @params.speech_pad_ms
+    @params.speech_pad_ms = 50
+    assert_equal 50, @params.speech_pad_ms
+  end
+
+  def test_samples_overlap
+    assert_in_delta @params.samples_overlap, 0.1
+    @params.samples_overlap = 0.5
+    assert_in_delta @params.samples_overlap, 0.5
+  end
+
+  def test_equal
+    assert_equal @params, Whisper::VAD::Params.new
+  end
+
+  def test_new_with_kw_args
+    params = Whisper::VAD::Params.new(threshold: 0.7)
+    assert_in_delta params.threshold, 0.7
+    assert_equal 250, params.min_speech_duration_ms
+  end
+
+  def test_new_with_kw_args_non_existent
+    assert_raise ArgumentError do
+      Whisper::VAD::Params.new(non_existent: "value")
+    end
+  end
+
+  data(PARAM_NAMES.collect {|param| [param, param]}.to_h)
+  def test_new_with_kw_args_default_values(param)
+    default_value = @params.send(param)
+    value = default_value + 1
+    params = Whisper::VAD::Params.new(param => value)
+    if Float === value
+      assert_in_delta value, params.send(param)
+    else
+      assert_equal value, params.send(param)
+    end
+
+    PARAM_NAMES.reject {|name| name == param}.each do |name|
+      expected = @params.send(name)
+      actual = params.send(name)
+      if Float === expected
+        assert_in_delta expected, actual
+      else
+        assert_equal expected, actual
+      end
+    end
+  end
+end

bindings/ruby/test/test_whisper.rb

@@ -20,6 +20,24 @@ class TestWhisper < TestBase
     }
   end
 
+  def test_transcribe_non_parallel
+    @whisper = Whisper::Context.new("base.en")
+    params  = Whisper::Params.new
+
+    @whisper.transcribe(AUDIO, params, n_processors: 1) {|text|
+      assert_match(/ask not what your country can do for you, ask what you can do for your country/, text)
+    }
+  end
+
+  def test_transcribe_n_processors
+    @whisper = Whisper::Context.new("base.en")
+    params  = Whisper::Params.new
+
+    @whisper.transcribe(AUDIO, params, n_processors: 4) {|text|
+      assert_match(/ask not what your country can do for you[,.] ask what you can do for your country/i, text)
+    }
+  end
+
   sub_test_case "After transcription" do
     def test_full_n_segments
       assert_equal 1, whisper.full_n_segments
@@ -94,6 +112,14 @@ class TestWhisper < TestBase
     end
   end
 
+  def test_system_info_str
+    assert_match(/\AWHISPER : COREML = \d | OPENVINO = \d |/, Whisper.system_info_str)
+  end
+
+  def test_version
+    assert_kind_of String, Whisper::VERSION
+  end
+
   def test_log_set
     user_data = Object.new
     logs = []
@@ -223,4 +249,48 @@ class TestWhisper < TestBase
       assert_match(/for your country/i, text)
     end
   end
+
+  def test_to_srt
+    whisper = Whisper::Context.new("base.en")
+    whisper.transcribe AUDIO, @params
+
+    lines = whisper.to_srt.lines
+    assert_match(/\A\d+\n/, lines[0])
+    assert_match(/\d{2}:\d{2}:\d{2},\d{3} --> \d{2}:\d{2}:\d{2},\d{3}\n/, lines[1])
+    assert_match(/ask not what your country can do for you, ask what you can do for your country/, lines[2])
+  end
+
+  def test_to_webvtt
+    whisper = Whisper::Context.new("base.en")
+    whisper.transcribe AUDIO, @params
+
+    lines = whisper.to_webvtt.lines
+    assert_equal "WEBVTT\n", lines[0]
+    assert_equal "\n", lines[1]
+    assert_match(/\A\d+\n/, lines[2])
+    assert_match(/\d{2}:\d{2}:\d{2}\.\d{3} --> \d{2}:\d{2}:\d{2}\.\d{3}\n/, lines[3])
+    assert_match(/ask not what your country can do for you, ask what you can do for your country/, lines[4])
+  end
+
+  sub_test_case "Format needs escape" do
+    def setup
+      @whisper = Whisper::Context.new("base.en")
+      @whisper.transcribe AUDIO, Whisper::Params.new
+      segment = @whisper.each_segment.first
+      segment.define_singleton_method :text do
+        "& so my fellow Americans --> ask not what your country can do for you <-- ask what you can do for your country."
+      end
+      @whisper.define_singleton_method :each_segment do
+        Enumerator.new(3) {|yielder| 3.times {yielder << segment}}
+      end
+    end
+
+    def test_to_srt_escape
+      assert_equal "&amp; so my fellow Americans --&gt; ask not what your country can do for you &lt;-- ask what you can do for your country.\n", @whisper.to_srt.lines[2]
+    end
+
+    def test_to_webvtt_escape
+      assert_equal "&amp; so my fellow Americans --&gt; ask not what your country can do for you &lt;-- ask what you can do for your country.\n", @whisper.to_webvtt.lines[4]
+    end
+  end
 end

bindings/ruby/tests/test_package.rb

@@ -1,31 +0,0 @@
-require_relative "helper"
-require 'tempfile'
-require 'tmpdir'
-require 'shellwords'
-
-class TestPackage < TestBase
-  def test_build
-    Tempfile.create do |file|
-      assert system("gem", "build", "whispercpp.gemspec", "--output", file.to_path.shellescape, exception: true)
-      assert file.size > 0
-      assert_path_exist file.to_path
-    end
-  end
-
-  sub_test_case "Building binary on installation" do
-    def setup
-      system "rake", "build", exception: true
-    end
-
-    def test_install
-      match_data = `rake -Tbuild`.match(/(whispercpp-(.+)\.gem)/)
-      filename = match_data[1]
-      version = match_data[2]
-      basename = "whisper.#{RbConfig::CONFIG["DLEXT"]}"
-      Dir.mktmpdir do |dir|
-        system "gem", "install", "--install-dir", dir.shellescape, "--no-document", "pkg/#{filename.shellescape}", exception: true
-        assert_path_exist File.join(dir, "gems/whispercpp-#{version}/lib", basename)
-      end
-    end
-  end
-end

bindings/ruby/tests/test_segment.rb

@@ -1,74 +0,0 @@
-require_relative "helper"
-
-class TestSegment < TestBase
-  def test_iteration
-    whisper.each_segment do |segment|
-      assert_instance_of Whisper::Segment, segment
-    end
-  end
-
-  def test_enumerator
-    enum = whisper.each_segment
-    assert_instance_of Enumerator, enum
-    enum.to_a.each_with_index do |segment, index|
-      assert_instance_of Whisper::Segment, segment
-      assert_kind_of Integer, index
-    end
-  end
-
-  def test_start_time
-    i = 0
-    whisper.each_segment do |segment|
-      assert_equal 0, segment.start_time if i == 0
-      i += 1
-    end
-  end
-
-  def test_end_time
-    i = 0
-    whisper.each_segment do |segment|
-      assert_equal whisper.full_get_segment_t1(i) * 10, segment.end_time
-      i += 1
-    end
-  end
-
-  def test_no_speech_prob
-    no_speech_prob = nil
-    whisper.each_segment do |segment|
-      no_speech_prob = segment.no_speech_prob
-    end
-    assert no_speech_prob > 0.0
-  end
-
-  def test_on_new_segment
-    params = Whisper::Params.new
-    seg = nil
-    index = 0
-    params.on_new_segment do |segment|
-      assert_instance_of Whisper::Segment, segment
-      if index == 0
-        seg = segment
-        assert_equal 0, segment.start_time
-        assert_match(/ask not what your country can do for you, ask what you can do for your country/, segment.text)
-      end
-      index += 1
-    end
-    whisper.transcribe(AUDIO, params)
-    assert_equal 0, seg.start_time
-    assert_match(/ask not what your country can do for you, ask what you can do for your country/, seg.text)
-  end
-
-  def test_on_new_segment_twice
-    params = Whisper::Params.new
-    seg = nil
-    params.on_new_segment do |segment|
-      seg = segment
-      return
-    end
-    params.on_new_segment do |segment|
-      assert_same seg, segment
-      return
-    end
-    whisper.transcribe(AUDIO, params)
-  end
-end

bindings/ruby/whispercpp.gemspec

@@ -3,8 +3,7 @@ require_relative "extsources"
 Gem::Specification.new do |s|
   s.name    = "whispercpp"
   s.authors = ["Georgi Gerganov", "Todd A. Fisher"]
-  s.version = '1.3.1'
-  s.date    = '2024-12-19'
+  s.version = '1.3.3'
   s.description = %q{High-performance inference of OpenAI's Whisper automatic speech recognition (ASR) model via Ruby}
   s.email   = 'todd.fisher@gmail.com'
   s.extra_rdoc_files = ['LICENSE', 'README.md']
@@ -15,18 +14,19 @@ Gem::Specification.new do |s|
                 if s.extra_rdoc_files.include?(basename)
                   basename
                 else
-                  file.sub("../..", "ext")
+                  file.sub("../..", "ext/sources")
+                      .sub("../javascript", "ext/sources/bindings/javascript")
                 end
               }
 
   s.summary = %q{Ruby whisper.cpp bindings}
-  s.test_files = s.files.select {|file| file.start_with? "tests/"}
+  s.test_files = s.files.select {|file| file.start_with? "test/"}
 
   s.extensions << 'ext/extconf.rb'
   s.required_ruby_version = '>= 3.1.0'
 
   #### Documentation and testing.
-  s.homepage = 'https://github.com/ggerganov/whisper.cpp'
+  s.homepage = 'https://github.com/ggml-org/whisper.cpp'
   s.rdoc_options = ['--main', 'README.md']
 
 

build-xcframework.sh

@@ -41,6 +41,11 @@ COMMON_CMAKE_ARGS=(
     -DGGML_OPENMP=${GGML_OPENMP}
 )
 
+XCODE_VERSION=$(xcodebuild -version 2>/dev/null | head -n1 | awk '{ print $2 }')
+MAJOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f1)
+MINOR_VERSION=$(echo $XCODE_VERSION | cut -d. -f2)
+echo "Detected Xcode version: $XCODE_VERSION"
+
 check_required_tool() {
     local tool=$1
     local install_message=$2
@@ -335,21 +340,28 @@ combine_static_libraries() {
 
     # Platform-specific post-processing for device builds
     if [[ "$is_simulator" == "false" ]]; then
-        if command -v vtool &>/dev/null; then
+        if command -v xcrun vtool &>/dev/null; then
             case "$platform" in
                 "ios")
                     echo "Marking binary as a framework binary for iOS..."
-                    vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
+                    xcrun vtool -set-build-version ios ${IOS_MIN_OS_VERSION} ${IOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
                 "visionos")
                     echo "Marking binary as a framework binary for visionOS..."
-                    vtool -set-build-version xros ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
+                    if [[ "$MAJOR_VERSION" -gt 16 ]] || [[ "$MAJOR_VERSION" -eq 16 && "$MINOR_VERSION" -gt 2 ]]; then
+                        echo "Xcode version greater than 16.2, using visionOS."
+                        VISION_OS_BUILD_VERSION="visionos"
+                    else
+                        echo "Xcode version less than or equal to 16.2, using xros."
+                        VISION_OS_BUILD_VERSION="xros"
+                    fi
+                    xcrun vtool -set-build-version ${VISION_OS_BUILD_VERSION} ${VISIONOS_MIN_OS_VERSION} ${VISIONOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
                 "tvos")
                     echo "Marking binary as a framework binary for tvOS..."
-                    vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
+                    xcrun vtool -set-build-version tvos ${TVOS_MIN_OS_VERSION} ${TVOS_MIN_OS_VERSION} -replace \
                         -output "${base_dir}/${output_lib}" "${base_dir}/${output_lib}"
                     ;;
             esac

examples/CMakeLists.txt

@@ -105,6 +105,7 @@ else()
     add_subdirectory(bench)
     add_subdirectory(server)
     add_subdirectory(quantize)
+    add_subdirectory(vad-speech-segments)
     if (WHISPER_SDL2)
         add_subdirectory(stream)
         add_subdirectory(command)

examples/addon.node/README.md

@@ -1,8 +1,10 @@
-# addon
+# whisper.cpp Node.js addon
 
 This is an addon demo that can **perform whisper model reasoning in `node` and `electron` environments**, based on [cmake-js](https://github.com/cmake-js/cmake-js).
 It can be used as a reference for using the whisper.cpp project in other node projects.
 
+This addon now supports **Voice Activity Detection (VAD)** for improved transcription performance.
+
 ## Install
 
 ```shell
@@ -26,12 +28,88 @@ For Electron addon and cmake-js options, you can see [cmake-js](https://github.c
 
 ## Run
 
+### Basic Usage
+
 ```shell
 cd examples/addon.node
 
 node index.js --language='language' --model='model-path' --fname_inp='file-path'
 ```
 
-Because this is a simple Demo, only the above parameters are set in the node environment.
+### VAD (Voice Activity Detection) Usage
 
-Other parameters can also be specified in the node environment.
+Run the VAD example with performance comparison:
+
+```shell
+node vad-example.js
+```
+
+## Voice Activity Detection (VAD) Support
+
+VAD can significantly improve transcription performance by only processing speech segments, which is especially beneficial for audio files with long periods of silence.
+
+### VAD Model Setup
+
+Before using VAD, download a VAD model:
+
+```shell
+# From the whisper.cpp root directory
+./models/download-vad-model.sh silero-v5.1.2
+```
+
+### VAD Parameters
+
+All VAD parameters are optional and have sensible defaults:
+
+- `vad`: Enable VAD (default: false)
+- `vad_model`: Path to VAD model file (required when VAD enabled)
+- `vad_threshold`: Speech detection threshold 0.0-1.0 (default: 0.5)
+- `vad_min_speech_duration_ms`: Min speech duration in ms (default: 250)
+- `vad_min_silence_duration_ms`: Min silence duration in ms (default: 100)
+- `vad_max_speech_duration_s`: Max speech duration in seconds (default: FLT_MAX)
+- `vad_speech_pad_ms`: Speech padding in ms (default: 30)
+- `vad_samples_overlap`: Sample overlap 0.0-1.0 (default: 0.1)
+
+### JavaScript API Example
+
+```javascript
+const path = require("path");
+const { whisper } = require(path.join(__dirname, "../../build/Release/addon.node"));
+const { promisify } = require("util");
+
+const whisperAsync = promisify(whisper);
+
+// With VAD enabled
+const vadParams = {
+  language: "en",
+  model: path.join(__dirname, "../../models/ggml-base.en.bin"),
+  fname_inp: path.join(__dirname, "../../samples/jfk.wav"),
+  vad: true,
+  vad_model: path.join(__dirname, "../../models/ggml-silero-v5.1.2.bin"),
+  vad_threshold: 0.5,
+  progress_callback: (progress) => console.log(`Progress: ${progress}%`)
+};
+
+whisperAsync(vadParams).then(result => console.log(result));
+```
+
+## Supported Parameters
+
+Both traditional whisper.cpp parameters and new VAD parameters are supported:
+
+- `language`: Language code (e.g., "en", "es", "fr")
+- `model`: Path to whisper model file
+- `fname_inp`: Path to input audio file
+- `use_gpu`: Enable GPU acceleration (default: true)
+- `flash_attn`: Enable flash attention (default: false)
+- `no_prints`: Disable console output (default: false)
+- `no_timestamps`: Disable timestamps (default: false)
+- `detect_language`: Auto-detect language (default: false)
+- `audio_ctx`: Audio context size (default: 0)
+- `max_len`: Maximum segment length (default: 0)
+- `max_context`: Maximum context size (default: -1)
+- `prompt`: Initial prompt for decoder
+- `comma_in_time`: Use comma in timestamps (default: true)
+- `print_progress`: Print progress info (default: false)
+- `progress_callback`: Progress callback function
+- VAD parameters (see above section)

examples/addon.node/__test__/whisper.spec.js

@@ -1,31 +1,133 @@
-const path = require("path");
-const { whisper } = require(path.join(
-  __dirname,
-  "../../../build/Release/addon.node"
-));
-const { promisify } = require("util");
+const { join } = require('path');
+const { whisper } = require('../../../build/Release/addon.node');
+const { promisify } = require('util');
 
 const whisperAsync = promisify(whisper);
 
-const whisperParamsMock = {
-  language: "en",
-  model: path.join(__dirname, "../../../models/ggml-base.en.bin"),
-  fname_inp: path.join(__dirname, "../../../samples/jfk.wav"),
+const commonParams = {
+  language: 'en',
+  model: join(__dirname, '../../../models/ggml-base.en.bin'),
+  fname_inp: join(__dirname, '../../../samples/jfk.wav'),
   use_gpu: true,
   flash_attn: false,
   no_prints: true,
-  comma_in_time: false,
-  translate: true,
   no_timestamps: false,
+  detect_language: false,
   audio_ctx: 0,
-  max_len: 0,
+  max_len: 0
 };
 
-describe("Run whisper.node", () => {
-    test("it should receive a non-empty value", async () => {
-        let result = await whisperAsync(whisperParamsMock);
+describe('Whisper.cpp Node.js addon with VAD support', () => {
+  test('Basic whisper transcription without VAD', async () => {
+    const params = {
+      ...commonParams,
+      vad: false
+    };
 
-        expect(result.length).toBeGreaterThan(0);
-    }, 10000);
+    const result = await whisperAsync(params);
+    
+    expect(typeof result).toBe('object');
+    expect(Array.isArray(result.transcription)).toBe(true);
+    expect(result.transcription.length).toBeGreaterThan(0);
+    
+    // Check that we got some transcription text
+    const text = result.transcription.map(segment => segment[2]).join(' ');
+    expect(text.length).toBeGreaterThan(0);
+    expect(text.toLowerCase()).toContain('ask not');
+  }, 30000);
+
+  test('VAD parameters validation', async () => {
+    // Test with invalid VAD model - should return empty transcription
+    const invalidParams = {
+      ...commonParams,
+      vad: true,
+      vad_model: 'non-existent-model.bin',
+      vad_threshold: 0.5
+    };
+
+    // This should handle the error gracefully and return empty transcription
+    const result = await whisperAsync(invalidParams);
+    expect(typeof result).toBe('object');
+    expect(Array.isArray(result.transcription)).toBe(true);
+    // When VAD model doesn't exist, it should return empty transcription
+    expect(result.transcription.length).toBe(0);
+  }, 10000);
+
+  test('VAD parameter parsing', async () => {
+    // Test that VAD parameters are properly parsed (even if VAD model doesn't exist)
+    const vadParams = {
+      ...commonParams,
+      vad: false, // Disabled so no model required
+      vad_threshold: 0.7,
+      vad_min_speech_duration_ms: 300,
+      vad_min_silence_duration_ms: 150,
+      vad_max_speech_duration_s: 45.0,
+      vad_speech_pad_ms: 50,
+      vad_samples_overlap: 0.15
+    };
+
+    const result = await whisperAsync(vadParams);
+    
+    expect(typeof result).toBe('object');
+    expect(Array.isArray(result.transcription)).toBe(true);
+  }, 30000);
+
+  test('Progress callback with VAD disabled', async () => {
+    let progressCalled = false;
+    let lastProgress = 0;
+
+    const params = {
+      ...commonParams,
+      vad: false,
+      progress_callback: (progress) => {
+        progressCalled = true;
+        lastProgress = progress;
+        expect(progress).toBeGreaterThanOrEqual(0);
+        expect(progress).toBeLessThanOrEqual(100);
+      }
+    };
+
+    const result = await whisperAsync(params);
+    
+    expect(progressCalled).toBe(true);
+    expect(lastProgress).toBe(100);
+    expect(typeof result).toBe('object');
+  }, 30000);
+
+  test('Language detection without VAD', async () => {
+    const params = {
+      ...commonParams,
+      vad: false,
+      detect_language: true,
+      language: 'auto'
+    };
+
+    const result = await whisperAsync(params);
+    
+    expect(typeof result).toBe('object');
+    expect(typeof result.language).toBe('string');
+    expect(result.language.length).toBeGreaterThan(0);
+  }, 30000);
+
+  test('Basic transcription with all VAD parameters set', async () => {
+    // Test with VAD disabled but all parameters set to ensure no crashes
+    const params = {
+      ...commonParams,
+      vad: false, // Disabled so it works without VAD model
+      vad_model: '', // Empty model path
+      vad_threshold: 0.6,
+      vad_min_speech_duration_ms: 200,
+      vad_min_silence_duration_ms: 80,
+      vad_max_speech_duration_s: 25.0,
+      vad_speech_pad_ms: 40,
+      vad_samples_overlap: 0.08
+    };
+
+    const result = await whisperAsync(params);
+    
+    expect(typeof result).toBe('object');
+    expect(Array.isArray(result.transcription)).toBe(true);
+    expect(result.transcription.length).toBeGreaterThan(0);
+  }, 30000);
 });
 

examples/addon.node/addon.cpp

@@ -9,6 +9,7 @@
 #include <vector>
 #include <cmath>
 #include <cstdint>
+#include <cfloat>
 
 struct whisper_params {
     int32_t n_threads    = std::min(4, (int32_t) std::thread::hardware_concurrency());
@@ -38,6 +39,7 @@ struct whisper_params {
     bool print_progress = false;
     bool no_timestamps  = false;
     bool no_prints      = false;
+    bool detect_language= false;
     bool use_gpu        = true;
     bool flash_attn     = false;
     bool comma_in_time  = true;
@@ -50,6 +52,16 @@ struct whisper_params {
     std::vector<std::string> fname_out = {};
 
     std::vector<float> pcmf32 = {}; // mono-channel F32 PCM
+
+    // Voice Activity Detection (VAD) parameters
+    bool        vad           = false;
+    std::string vad_model     = "";
+    float       vad_threshold = 0.5f;
+    int         vad_min_speech_duration_ms = 250;
+    int         vad_min_silence_duration_ms = 100;
+    float       vad_max_speech_duration_s = FLT_MAX;
+    int         vad_speech_pad_ms = 30;
+    float       vad_samples_overlap = 0.1f;
 };
 
 struct whisper_print_user_data {
@@ -82,7 +94,7 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
             t1 = whisper_full_get_segment_t1(ctx, i);
         }
 
-        if (!params.no_timestamps) {
+        if (!params.no_timestamps && !params.no_prints) {
             printf("[%s --> %s]  ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
         }
 
@@ -113,12 +125,14 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
 
         // colorful print bug
         //
-        const char * text = whisper_full_get_segment_text(ctx, i);
-        printf("%s%s", speaker.c_str(), text);
+        if (!params.no_prints) {
+            const char * text = whisper_full_get_segment_text(ctx, i);
+            printf("%s%s", speaker.c_str(), text);
+        }
 
 
         // with timestamps or speakers: each segment on new line
-        if (!params.no_timestamps || params.diarize) {
+        if ((!params.no_timestamps || params.diarize) && !params.no_prints) {
             printf("\n");
         }
 
@@ -128,6 +142,11 @@ void whisper_print_segment_callback(struct whisper_context * ctx, struct whisper
 
 void cb_log_disable(enum ggml_log_level, const char *, void *) {}
 
+struct whisper_result {
+    std::vector<std::vector<std::string>> segments;
+    std::string language;
+};
+
 class ProgressWorker : public Napi::AsyncWorker {
  public:
     ProgressWorker(Napi::Function& callback, whisper_params params, Napi::Function progress_callback, Napi::Env env)
@@ -158,15 +177,27 @@ class ProgressWorker : public Napi::AsyncWorker {
 
     void OnOK() override {
         Napi::HandleScope scope(Env());
-        Napi::Object res = Napi::Array::New(Env(), result.size());
-        for (uint64_t i = 0; i < result.size(); ++i) {
+
+        if (params.detect_language) {
+            Napi::Object resultObj = Napi::Object::New(Env());
+            resultObj.Set("language", Napi::String::New(Env(), result.language));
+            Callback().Call({Env().Null(), resultObj});
+        }
+
+        Napi::Object returnObj = Napi::Object::New(Env());
+        if (!result.language.empty()) {
+            returnObj.Set("language", Napi::String::New(Env(), result.language));
+        }
+        Napi::Array transcriptionArray = Napi::Array::New(Env(), result.segments.size());
+        for (uint64_t i = 0; i < result.segments.size(); ++i) {
             Napi::Object tmp = Napi::Array::New(Env(), 3);
             for (uint64_t j = 0; j < 3; ++j) {
-                tmp[j] = Napi::String::New(Env(), result[i][j]);
+                tmp[j] = Napi::String::New(Env(), result.segments[i][j]);
             }
-            res[i] = tmp;
-        }
-        Callback().Call({Env().Null(), res});
+            transcriptionArray[i] = tmp;
+         }
+         returnObj.Set("transcription", transcriptionArray);
+         Callback().Call({Env().Null(), returnObj});
     }
 
     // Progress callback function - using thread-safe function
@@ -183,12 +214,12 @@ class ProgressWorker : public Napi::AsyncWorker {
 
  private:
     whisper_params params;
-    std::vector<std::vector<std::string>> result;
+    whisper_result result;
     Napi::Env env;
     Napi::ThreadSafeFunction tsfn;
 
     // Custom run function with progress callback support
-    int run_with_progress(whisper_params &params, std::vector<std::vector<std::string>> &result) {
+    int run_with_progress(whisper_params &params, whisper_result & result) {
         if (params.no_prints) {
             whisper_log_set(cb_log_disable, NULL);
         }
@@ -277,7 +308,8 @@ class ProgressWorker : public Napi::AsyncWorker {
                 wparams.print_timestamps = !params.no_timestamps;
                 wparams.print_special    = params.print_special;
                 wparams.translate        = params.translate;
-                wparams.language         = params.language.c_str();
+                wparams.language         = params.detect_language ? "auto" : params.language.c_str();
+                wparams.detect_language  = params.detect_language;
                 wparams.n_threads        = params.n_threads;
                 wparams.n_max_text_ctx   = params.max_context >= 0 ? params.max_context : wparams.n_max_text_ctx;
                 wparams.offset_ms        = params.offset_t_ms;
@@ -312,34 +344,38 @@ class ProgressWorker : public Napi::AsyncWorker {
                 };
                 wparams.progress_callback_user_data = this;
 
-                // Abort mechanism example
-                {
-                    static bool is_aborted = false; // Note: this should be atomic to avoid data races
+                // Set VAD parameters
+                wparams.vad            = params.vad;
+                wparams.vad_model_path = params.vad_model.c_str();
 
-                    wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
-                        bool is_aborted = *(bool*)user_data;
-                        return !is_aborted;
-                    };
-                    wparams.encoder_begin_callback_user_data = &is_aborted;
-                }
+                wparams.vad_params.threshold               = params.vad_threshold;
+                wparams.vad_params.min_speech_duration_ms  = params.vad_min_speech_duration_ms;
+                wparams.vad_params.min_silence_duration_ms = params.vad_min_silence_duration_ms;
+                wparams.vad_params.max_speech_duration_s   = params.vad_max_speech_duration_s;
+                wparams.vad_params.speech_pad_ms           = params.vad_speech_pad_ms;
+                wparams.vad_params.samples_overlap         = params.vad_samples_overlap;
 
                 if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
                     fprintf(stderr, "failed to process audio\n");
                     return 10;
                 }
             }
-    }
+        }
 
+        if (params.detect_language || params.language == "auto") {
+            result.language = whisper_lang_str(whisper_full_lang_id(ctx));
+        }
         const int n_segments = whisper_full_n_segments(ctx);
-        result.resize(n_segments);
+        result.segments.resize(n_segments);
+
         for (int i = 0; i < n_segments; ++i) {
             const char * text = whisper_full_get_segment_text(ctx, i);
             const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
             const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
 
-            result[i].emplace_back(to_timestamp(t0, params.comma_in_time));
-            result[i].emplace_back(to_timestamp(t1, params.comma_in_time));
-            result[i].emplace_back(text);
+            result.segments[i].emplace_back(to_timestamp(t0, params.comma_in_time));
+            result.segments[i].emplace_back(to_timestamp(t1, params.comma_in_time));
+            result.segments[i].emplace_back(text);
         }
 
         whisper_print_timings(ctx);
@@ -360,13 +396,52 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
   std::string language = whisper_params.Get("language").As<Napi::String>();
   std::string model = whisper_params.Get("model").As<Napi::String>();
   std::string input = whisper_params.Get("fname_inp").As<Napi::String>();
-  bool use_gpu = whisper_params.Get("use_gpu").As<Napi::Boolean>();
-  bool flash_attn = whisper_params.Get("flash_attn").As<Napi::Boolean>();
-  bool no_prints = whisper_params.Get("no_prints").As<Napi::Boolean>();
-  bool no_timestamps = whisper_params.Get("no_timestamps").As<Napi::Boolean>();
-  int32_t audio_ctx = whisper_params.Get("audio_ctx").As<Napi::Number>();
-  bool comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>();
-  int32_t max_len = whisper_params.Get("max_len").As<Napi::Number>();
+  
+  bool use_gpu = true;
+  if (whisper_params.Has("use_gpu") && whisper_params.Get("use_gpu").IsBoolean()) {
+    use_gpu = whisper_params.Get("use_gpu").As<Napi::Boolean>();
+  }
+  
+  bool flash_attn = false;
+  if (whisper_params.Has("flash_attn") && whisper_params.Get("flash_attn").IsBoolean()) {
+    flash_attn = whisper_params.Get("flash_attn").As<Napi::Boolean>();
+  }
+  
+  bool no_prints = false;
+  if (whisper_params.Has("no_prints") && whisper_params.Get("no_prints").IsBoolean()) {
+    no_prints = whisper_params.Get("no_prints").As<Napi::Boolean>();
+  }
+  
+  bool no_timestamps = false;
+  if (whisper_params.Has("no_timestamps") && whisper_params.Get("no_timestamps").IsBoolean()) {
+    no_timestamps = whisper_params.Get("no_timestamps").As<Napi::Boolean>();
+  }
+  
+  bool detect_language = false;
+  if (whisper_params.Has("detect_language") && whisper_params.Get("detect_language").IsBoolean()) {
+    detect_language = whisper_params.Get("detect_language").As<Napi::Boolean>();
+  }
+  
+  int32_t audio_ctx = 0;
+  if (whisper_params.Has("audio_ctx") && whisper_params.Get("audio_ctx").IsNumber()) {
+    audio_ctx = whisper_params.Get("audio_ctx").As<Napi::Number>();
+  }
+  
+  bool comma_in_time = true;
+  if (whisper_params.Has("comma_in_time") && whisper_params.Get("comma_in_time").IsBoolean()) {
+    comma_in_time = whisper_params.Get("comma_in_time").As<Napi::Boolean>();
+  }
+  
+  int32_t max_len = 0;
+  if (whisper_params.Has("max_len") && whisper_params.Get("max_len").IsNumber()) {
+    max_len = whisper_params.Get("max_len").As<Napi::Number>();
+  }
+  
+  // Add support for max_context
+  int32_t max_context = -1;
+  if (whisper_params.Has("max_context") && whisper_params.Get("max_context").IsNumber()) {
+    max_context = whisper_params.Get("max_context").As<Napi::Number>();
+  }
   
   // support prompt
   std::string prompt = "";
@@ -376,7 +451,7 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
   
   // Add support for print_progress
   bool print_progress = false;
-  if (whisper_params.Has("print_progress")) {
+  if (whisper_params.Has("print_progress") && whisper_params.Get("print_progress").IsBoolean()) {
     print_progress = whisper_params.Get("print_progress").As<Napi::Boolean>();
   }
   // Add support for progress_callback
@@ -385,6 +460,47 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
     progress_callback = whisper_params.Get("progress_callback").As<Napi::Function>();
   }
 
+  // Add support for VAD parameters
+  bool vad = false;
+  if (whisper_params.Has("vad") && whisper_params.Get("vad").IsBoolean()) {
+    vad = whisper_params.Get("vad").As<Napi::Boolean>();
+  }
+  
+  std::string vad_model = "";
+  if (whisper_params.Has("vad_model") && whisper_params.Get("vad_model").IsString()) {
+    vad_model = whisper_params.Get("vad_model").As<Napi::String>();
+  }
+  
+  float vad_threshold = 0.5f;
+  if (whisper_params.Has("vad_threshold") && whisper_params.Get("vad_threshold").IsNumber()) {
+    vad_threshold = whisper_params.Get("vad_threshold").As<Napi::Number>();
+  }
+  
+  int vad_min_speech_duration_ms = 250;
+  if (whisper_params.Has("vad_min_speech_duration_ms") && whisper_params.Get("vad_min_speech_duration_ms").IsNumber()) {
+    vad_min_speech_duration_ms = whisper_params.Get("vad_min_speech_duration_ms").As<Napi::Number>();
+  }
+  
+  int vad_min_silence_duration_ms = 100;
+  if (whisper_params.Has("vad_min_silence_duration_ms") && whisper_params.Get("vad_min_silence_duration_ms").IsNumber()) {
+    vad_min_silence_duration_ms = whisper_params.Get("vad_min_silence_duration_ms").As<Napi::Number>();
+  }
+  
+  float vad_max_speech_duration_s = FLT_MAX;
+  if (whisper_params.Has("vad_max_speech_duration_s") && whisper_params.Get("vad_max_speech_duration_s").IsNumber()) {
+    vad_max_speech_duration_s = whisper_params.Get("vad_max_speech_duration_s").As<Napi::Number>();
+  }
+  
+  int vad_speech_pad_ms = 30;
+  if (whisper_params.Has("vad_speech_pad_ms") && whisper_params.Get("vad_speech_pad_ms").IsNumber()) {
+    vad_speech_pad_ms = whisper_params.Get("vad_speech_pad_ms").As<Napi::Number>();
+  }
+  
+  float vad_samples_overlap = 0.1f;
+  if (whisper_params.Has("vad_samples_overlap") && whisper_params.Get("vad_samples_overlap").IsNumber()) {
+    vad_samples_overlap = whisper_params.Get("vad_samples_overlap").As<Napi::Number>();
+  }
+
   Napi::Value pcmf32Value = whisper_params.Get("pcmf32");
   std::vector<float> pcmf32_vec;
   if (pcmf32Value.IsTypedArray()) {
@@ -407,8 +523,20 @@ Napi::Value whisper(const Napi::CallbackInfo& info) {
   params.pcmf32 = pcmf32_vec;
   params.comma_in_time = comma_in_time;
   params.max_len = max_len;
+  params.max_context = max_context;
   params.print_progress = print_progress;
   params.prompt = prompt;
+  params.detect_language = detect_language;
+
+  // Set VAD parameters
+  params.vad = vad;
+  params.vad_model = vad_model;
+  params.vad_threshold = vad_threshold;
+  params.vad_min_speech_duration_ms = vad_min_speech_duration_ms;
+  params.vad_min_silence_duration_ms = vad_min_silence_duration_ms;
+  params.vad_max_speech_duration_s = vad_max_speech_duration_s;
+  params.vad_speech_pad_ms = vad_speech_pad_ms;
+  params.vad_samples_overlap = vad_samples_overlap;
 
   Napi::Function callback = info[1].As<Napi::Function>();
   // Create a new Worker class with progress callback support

examples/addon.node/index.js

@@ -17,6 +17,7 @@ const whisperParams = {
   comma_in_time: false,
   translate: true,
   no_timestamps: false,
+  detect_language: false,
   audio_ctx: 0,
   max_len: 0,
   progress_callback: (progress) => {
@@ -31,6 +32,8 @@ const params = Object.fromEntries(
       const [key, value] = item.slice(2).split("=");
       if (key === "audio_ctx") {
         whisperParams[key] = parseInt(value);
+      } else if (key === "detect_language") {
+        whisperParams[key] = value === "true";
       } else {
         whisperParams[key] = value;
       }

examples/addon.node/vad-example.js

@@ -0,0 +1,132 @@
+const path = require("path");
+const { whisper } = require(path.join(
+  __dirname,
+  "../../build/Release/addon.node"
+));
+const { promisify } = require("util");
+
+const whisperAsync = promisify(whisper);
+
+// Example with VAD enabled
+const vadParams = {
+  language: "en",
+  model: path.join(__dirname, "../../models/ggml-base.en.bin"),
+  fname_inp: path.join(__dirname, "../../samples/jfk.wav"),
+  use_gpu: true,
+  flash_attn: false,
+  no_prints: false,
+  comma_in_time: true,
+  translate: false,
+  no_timestamps: false,
+  detect_language: false,
+  audio_ctx: 0,
+  max_len: 0,
+  // VAD parameters
+  vad: true,
+  vad_model: path.join(__dirname, "../../models/ggml-silero-v5.1.2.bin"), // You need to download this model
+  vad_threshold: 0.5,
+  vad_min_speech_duration_ms: 250,
+  vad_min_silence_duration_ms: 100,
+  vad_max_speech_duration_s: 30.0,
+  vad_speech_pad_ms: 30,
+  vad_samples_overlap: 0.1,
+  progress_callback: (progress) => {
+    console.log(`VAD Transcription progress: ${progress}%`);
+  }
+};
+
+// Example without VAD (traditional approach)
+const traditionalParams = {
+  language: "en",
+  model: path.join(__dirname, "../../models/ggml-base.en.bin"),
+  fname_inp: path.join(__dirname, "../../samples/jfk.wav"),
+  use_gpu: true,
+  flash_attn: false,
+  no_prints: false,
+  comma_in_time: true,
+  translate: false,
+  no_timestamps: false,
+  detect_language: false,
+  audio_ctx: 0,
+  max_len: 0,
+  vad: false, // Explicitly disable VAD
+  progress_callback: (progress) => {
+    console.log(`Traditional transcription progress: ${progress}%`);
+  }
+};
+
+async function runVADExample() {
+  try {
+    console.log("=== Whisper.cpp Node.js VAD Example ===\n");
+    
+    // Check if VAD model exists
+    const fs = require('fs');
+    if (!fs.existsSync(vadParams.vad_model)) {
+      console.log("⚠️  VAD model not found. Please download the VAD model first:");
+      console.log("   ./models/download-vad-model.sh silero-v5.1.2");
+      console.log("   Or run: python models/convert-silero-vad-to-ggml.py");
+      console.log("\n   Falling back to traditional transcription without VAD...\n");
+      
+      // Run without VAD
+      console.log("🎵 Running traditional transcription...");
+      const traditionalResult = await whisperAsync(traditionalParams);
+      console.log("\n📝 Traditional transcription result:");
+      console.log(traditionalResult);
+      return;
+    }
+    
+    console.log("🎵 Running transcription with VAD enabled...");
+    console.log("VAD Parameters:");
+    console.log(`  - Threshold: ${vadParams.vad_threshold}`);
+    console.log(`  - Min speech duration: ${vadParams.vad_min_speech_duration_ms}ms`);
+    console.log(`  - Min silence duration: ${vadParams.vad_min_silence_duration_ms}ms`);
+    console.log(`  - Max speech duration: ${vadParams.vad_max_speech_duration_s}s`);
+    console.log(`  - Speech padding: ${vadParams.vad_speech_pad_ms}ms`);
+    console.log(`  - Samples overlap: ${vadParams.vad_samples_overlap}\n`);
+    
+    const startTime = Date.now();
+    const vadResult = await whisperAsync(vadParams);
+    const vadDuration = Date.now() - startTime;
+    
+    console.log("\n✅ VAD transcription completed!");
+    console.log(`⏱️  Processing time: ${vadDuration}ms`);
+    console.log("\n📝 VAD transcription result:");
+    console.log(vadResult);
+    
+    // Compare with traditional approach
+    console.log("\n🔄 Running traditional transcription for comparison...");
+    const traditionalStartTime = Date.now();
+    const traditionalResult = await whisperAsync(traditionalParams);
+    const traditionalDuration = Date.now() - traditionalStartTime;
+    
+    console.log("\n✅ Traditional transcription completed!");
+    console.log(`⏱️  Processing time: ${traditionalDuration}ms`);
+    console.log("\n📝 Traditional transcription result:");
+    console.log(traditionalResult);
+    
+    // Performance comparison
+    console.log("\n📊 Performance Comparison:");
+    console.log(`VAD:         ${vadDuration}ms`);
+    console.log(`Traditional: ${traditionalDuration}ms`);
+    const speedup = traditionalDuration / vadDuration;
+    if (speedup > 1) {
+      console.log(`🚀 VAD is ${speedup.toFixed(2)}x faster!`);
+    } else {
+      console.log(`ℹ️  Traditional approach was ${(1/speedup).toFixed(2)}x faster in this case.`);
+    }
+    
+  } catch (error) {
+    console.error("❌ Error during transcription:", error);
+  }
+}
+
+// Run the example
+if (require.main === module) {
+  runVADExample();
+}
+
+module.exports = {
+  runVADExample,
+  vadParams,
+  traditionalParams
+}; 

examples/bench.wasm/CMakeLists.txt

@@ -35,7 +35,7 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     -s INITIAL_MEMORY=2000MB \
     -s TOTAL_MEMORY=2000MB \
     -s FORCE_FILESYSTEM=1 \
-    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
+    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap', 'HEAPU8']\" \
     ${EXTRA_FLAGS} \
     ")
 

examples/bench.wasm/README.md

@@ -28,5 +28,10 @@ to the server's HTTP path:
 ```
 # copy the produced page to your HTTP path
 cp bin/bench.wasm/*       /path/to/html/
+cp bin/libbench.js        /path/to/html/
 cp bin/libbench.worker.js /path/to/html/
 ```
+
+> 📝 **Note:** As of Emscripten 3.1.58 (April 2024), separate worker.js files are no
+> longer generated and the worker is embedded in the main JS file. So the worker
+> file will not be geneated for versions later than `3.1.58`.

examples/bench/README.md

@@ -4,7 +4,7 @@ A very basic tool for benchmarking the inference performance on your device. The
 the transformer on some random audio data and records the execution time. This way we can have an objective comparison
 of the performance of the model for various setups.
 
-Benchmark results are tracked in the following Github issue: https://github.com/ggerganov/whisper.cpp/issues/89
+Benchmark results are tracked in the following Github issue: https://github.com/ggml-org/whisper.cpp/issues/89
 
 ```bash
 # run the bench too on the small.en model using 4 threads
@@ -40,7 +40,7 @@ system_info: n_threads = 4 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WA
 
 If you wish, you can submit these results here:
 
-  https://github.com/ggerganov/whisper.cpp/issues/89
+  https://github.com/ggml-org/whisper.cpp/issues/89
 
 Please include the following information:
 

examples/bench/bench.cpp

@@ -66,13 +66,12 @@ static int whisper_bench_full(const whisper_params & params) {
     cparams.use_gpu    = params.use_gpu;
     cparams.flash_attn = params.flash_attn;
 
-    struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
-
     {
         fprintf(stderr, "\n");
         fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", params.n_threads, std::thread::hardware_concurrency(), whisper_print_system_info());
     }
 
+    struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
     if (ctx == nullptr) {
         fprintf(stderr, "error: failed to initialize whisper context\n");
         return 2;
@@ -156,6 +155,8 @@ static int whisper_bench_full(const whisper_params & params) {
 }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     whisper_params params;
 
     if (whisper_params_parse(argc, argv, params) == false) {

examples/cli/README.md

@@ -6,7 +6,8 @@ It can be used as a reference for using the `whisper.cpp` library in other proje
 ```
 ./build/bin/whisper-cli -h
 
-usage: ./build-pkg/bin/whisper-cli [options] file0.wav file1.wav ...
+usage: ./build/bin/whisper-cli [options] file0 file1 ...
+supported audio formats: flac, mp3, ogg, wav
 
 options:
   -h,        --help              [default] show this help message and exit
@@ -24,6 +25,7 @@ options:
   -wt N,     --word-thold N      [0.01   ] word timestamp probability threshold
   -et N,     --entropy-thold N   [2.40   ] entropy threshold for decoder fail
   -lpt N,    --logprob-thold N   [-1.00  ] log probability threshold for decoder fail
+  -nth N,    --no-speech-thold N [0.60   ] no speech threshold
   -tp,       --temperature N     [0.00   ] The sampling temperature, between 0 and 1
   -tpi,      --temperature-inc N [0.20   ] The increment of temperature, between 0 and 1
   -debug,    --debug-mode        [false  ] enable debug mode (eg. dump log_mel)
@@ -50,12 +52,13 @@ options:
   -dl,       --detect-language   [false  ] exit after automatically detecting language
              --prompt PROMPT     [       ] initial prompt (max n_text_ctx/2 tokens)
   -m FNAME,  --model FNAME       [models/ggml-base.en.bin] model path
-  -f FNAME,  --file FNAME        [       ] input WAV file path
+  -f FNAME,  --file FNAME        [       ] input audio file path
   -oved D,   --ov-e-device DNAME [CPU    ] the OpenVINO device used for encode inference
   -dtw MODEL --dtw MODEL         [       ] compute token-level timestamps
   -ls,       --log-score         [false  ] log best decoder scores of tokens
   -ng,       --no-gpu            [false  ] disable GPU
   -fa,       --flash-attn        [false  ] flash attention
+  -sns,      --suppress-nst      [false  ] suppress non-speech tokens
   --suppress-regex REGEX         [       ] regular expression matching tokens to suppress
   --grammar GRAMMAR              [       ] GBNF grammar to guide decoding
   --grammar-rule RULE            [       ] top-level GBNF grammar rule name

examples/cli/cli.cpp

@@ -11,6 +11,7 @@
 #include <thread>
 #include <vector>
 #include <cstring>
+#include <cfloat>
 
 #if defined(_WIN32)
 #ifndef NOMINMAX
@@ -19,10 +20,6 @@
 #include <windows.h>
 #endif
 
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
-#endif
-
 // helper function to replace substrings
 static void replace_all(std::string & s, const std::string & search, const std::string & replace) {
     for (size_t pos = 0; ; pos += replace.length()) {
@@ -73,6 +70,7 @@ struct whisper_params {
     bool no_prints       = false;
     bool print_special   = false;
     bool print_colors    = false;
+    bool print_confidence= false;
     bool print_progress  = false;
     bool no_timestamps   = false;
     bool log_score       = false;
@@ -101,6 +99,16 @@ struct whisper_params {
     std::vector<std::string> fname_out = {};
 
     grammar_parser::parse_state grammar_parsed;
+
+    // Voice Activity Detection (VAD) parameters
+    bool        vad           = false;
+    std::string vad_model     = "";
+    float       vad_threshold = 0.5f;
+    int         vad_min_speech_duration_ms = 250;
+    int         vad_min_silence_duration_ms = 100;
+    float       vad_max_speech_duration_s = FLT_MAX;
+    int         vad_speech_pad_ms = 30;
+    float       vad_samples_overlap = 0.1f;
 };
 
 static void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
@@ -172,6 +180,7 @@ static bool whisper_params_parse(int argc, char ** argv, whisper_params & params
         else if (arg == "-np"   || arg == "--no-prints")       { params.no_prints       = true; }
         else if (arg == "-ps"   || arg == "--print-special")   { params.print_special   = true; }
         else if (arg == "-pc"   || arg == "--print-colors")    { params.print_colors    = true; }
+        else if (                  arg == "--print-confidence"){ params.print_confidence= true; }
         else if (arg == "-pp"   || arg == "--print-progress")  { params.print_progress  = true; }
         else if (arg == "-nt"   || arg == "--no-timestamps")   { params.no_timestamps   = true; }
         else if (arg == "-l"    || arg == "--language")        { params.language        = whisper_param_turn_lowercase(ARGV_NEXT); }
@@ -189,6 +198,15 @@ static bool whisper_params_parse(int argc, char ** argv, whisper_params & params
         else if (                  arg == "--grammar")         { params.grammar         = ARGV_NEXT; }
         else if (                  arg == "--grammar-rule")    { params.grammar_rule    = ARGV_NEXT; }
         else if (                  arg == "--grammar-penalty") { params.grammar_penalty = std::stof(ARGV_NEXT); }
+        // Voice Activity Detection (VAD)
+        else if (                  arg == "--vad")                         { params.vad                         = true; }
+        else if (arg == "-vm"   || arg == "--vad-model")                   { params.vad_model                   = ARGV_NEXT; }
+        else if (arg == "-vt"   || arg == "--vad-threshold")               { params.vad_threshold               = std::stof(ARGV_NEXT); }
+        else if (arg == "-vspd" || arg == "--vad-min-speech-duration-ms")  { params.vad_min_speech_duration_ms  = std::stoi(ARGV_NEXT); }
+        else if (arg == "-vsd"  || arg == "--vad-min-silence-duration-ms") { params.vad_min_speech_duration_ms  = std::stoi(ARGV_NEXT); }
+        else if (arg == "-vmsd" || arg == "--vad-max-speech-duration-s")   { params.vad_max_speech_duration_s   = std::stof(ARGV_NEXT); }
+        else if (arg == "-vp"   || arg == "--vad-speech-pad-ms")           { params.vad_speech_pad_ms           = std::stoi(ARGV_NEXT); }
+        else if (arg == "-vo"   || arg == "--vad-samples-overlap")         { params.vad_samples_overlap         = std::stof(ARGV_NEXT); }
         else {
             fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
             whisper_print_usage(argc, argv, params);
@@ -241,6 +259,7 @@ static void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params
     fprintf(stderr, "  -np,       --no-prints         [%-7s] do not print anything other than the results\n",   params.no_prints ? "true" : "false");
     fprintf(stderr, "  -ps,       --print-special     [%-7s] print special tokens\n",                           params.print_special ? "true" : "false");
     fprintf(stderr, "  -pc,       --print-colors      [%-7s] print colors\n",                                   params.print_colors ? "true" : "false");
+    fprintf(stderr, "             --print-confidence  [%-7s] print confidence\n",                               params.print_confidence ? "true" : "false");
     fprintf(stderr, "  -pp,       --print-progress    [%-7s] print progress\n",                                 params.print_progress ? "true" : "false");
     fprintf(stderr, "  -nt,       --no-timestamps     [%-7s] do not print timestamps\n",                        params.no_timestamps ? "true" : "false");
     fprintf(stderr, "  -l LANG,   --language LANG     [%-7s] spoken language ('auto' for auto-detect)\n",       params.language.c_str());
@@ -258,6 +277,18 @@ static void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params
     fprintf(stderr, "  --grammar GRAMMAR              [%-7s] GBNF grammar to guide decoding\n",                 params.grammar.c_str());
     fprintf(stderr, "  --grammar-rule RULE            [%-7s] top-level GBNF grammar rule name\n",               params.grammar_rule.c_str());
     fprintf(stderr, "  --grammar-penalty N            [%-7.1f] scales down logits of nongrammar tokens\n",      params.grammar_penalty);
+    // Voice Activity Detection (VAD) parameters
+    fprintf(stderr, "\nVoice Activity Detection (VAD) options:\n");
+    fprintf(stderr, "             --vad                           [%-7s] enable Voice Activity Detection (VAD)\n",            params.vad ? "true" : "false");
+    fprintf(stderr, "  -vm FNAME, --vad-model FNAME               [%-7s] VAD model path\n",                                   params.vad_model.c_str());
+    fprintf(stderr, "  -vt N,     --vad-threshold N               [%-7.2f] VAD threshold for speech recognition\n",           params.vad_threshold);
+    fprintf(stderr, "  -vspd N,   --vad-min-speech-duration-ms  N [%-7d] VAD min speech duration (0.0-1.0)\n",                params.vad_min_speech_duration_ms);
+    fprintf(stderr, "  -vsd N,    --vad-min-silence-duration-ms N [%-7d] VAD min silence duration (to split segments)\n",      params.vad_min_silence_duration_ms);
+    fprintf(stderr, "  -vmsd N,   --vad-max-speech-duration-s   N [%-7s] VAD max speech duration (auto-split longer)\n",      params.vad_max_speech_duration_s == FLT_MAX ?
+                                                                                                                                  std::string("FLT_MAX").c_str() :
+                                                                                                                                  std::to_string(params.vad_max_speech_duration_s).c_str());
+    fprintf(stderr, "  -vp N,     --vad-speech-pad-ms           N [%-7d] VAD speech padding (extend segments)\n",             params.vad_speech_pad_ms);
+    fprintf(stderr, "  -vo N,     --vad-samples-overlap         N [%-7.2f] VAD samples overlap (seconds between segments)\n", params.vad_samples_overlap);
     fprintf(stderr, "\n");
 }
 
@@ -358,6 +389,26 @@ static void whisper_print_segment_callback(struct whisper_context * ctx, struct
 
                 printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m");
             }
+        } else if (params.print_confidence) {
+            for (int j = 0; j < whisper_full_n_tokens(ctx, i); ++j) {
+                if (params.print_special == false) {
+                    const whisper_token id = whisper_full_get_token_id(ctx, i, j);
+                    if (id >= whisper_token_eot(ctx)) {
+                        continue;
+                    }
+                }
+
+                const char * text = whisper_full_get_token_text(ctx, i, j);
+                const float  p    = whisper_full_get_token_p   (ctx, i, j);
+
+                int style_idx = 2;     // High confidence - dim
+                if (p < 0.33) {
+                    style_idx = 0;     // Low confidence - inverse (highlighted)
+                } else if (p < 0.66) {
+                    style_idx = 1;     // Medium confidence - underlined
+                }
+                printf("%s%s%s%s", speaker.c_str(), k_styles[style_idx].c_str(), text, "\033[0m");
+            }
         } else {
             const char * text = whisper_full_get_segment_text(ctx, i);
 
@@ -379,15 +430,7 @@ static void whisper_print_segment_callback(struct whisper_context * ctx, struct
     }
 }
 
-static bool output_txt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_txt(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
     const int n_segments = whisper_full_n_segments(ctx);
     for (int i = 0; i < n_segments; ++i) {
         const char * text = whisper_full_get_segment_text(ctx, i);
@@ -402,19 +445,9 @@ static bool output_txt(struct whisper_context * ctx, const char * fname, const w
 
         fout << speaker << text << "\n";
     }
-
-    return true;
 }
 
-static bool output_vtt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_vtt(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
     fout << "WEBVTT\n\n";
 
     const int n_segments = whisper_full_n_segments(ctx);
@@ -434,19 +467,9 @@ static bool output_vtt(struct whisper_context * ctx, const char * fname, const w
         fout << to_timestamp(t0) << " --> " << to_timestamp(t1) << "\n";
         fout << speaker << text << "\n\n";
     }
-
-    return true;
 }
 
-static bool output_srt(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_srt(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
     const int n_segments = whisper_full_n_segments(ctx);
     for (int i = 0; i < n_segments; ++i) {
         const char * text = whisper_full_get_segment_text(ctx, i);
@@ -463,8 +486,6 @@ static bool output_srt(struct whisper_context * ctx, const char * fname, const w
         fout << to_timestamp(t0, true) << " --> " << to_timestamp(t1, true) << "\n";
         fout << speaker << text << "\n\n";
     }
-
-    return true;
 }
 
 static char * escape_double_quotes_and_backslashes(const char * str) {
@@ -530,15 +551,7 @@ static char * escape_double_quotes_in_csv(const char * str) {
     return escaped;
 }
 
-static bool output_csv(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_csv(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
     const int n_segments = whisper_full_n_segments(ctx);
     fout << "start,end,";
     if (params.diarize && pcmf32s.size() == 2)
@@ -561,14 +574,9 @@ static bool output_csv(struct whisper_context * ctx, const char * fname, const w
         }
         fout << "\"" << text_escaped << "\"\n";
     }
-
-    return true;
 }
 
-static bool output_score(struct whisper_context * ctx, const char * fname, const whisper_params & /*params*/, std::vector<std::vector<float>> /*pcmf32s*/) {
-    std::ofstream fout(fname);
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_score(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & /*params*/, std::vector<std::vector<float>> /*pcmf32s*/) {
     const int n_segments = whisper_full_n_segments(ctx);
     // fprintf(stderr,"segments: %d\n",n_segments);
     for (int i = 0; i < n_segments; ++i) {
@@ -581,16 +589,14 @@ static bool output_score(struct whisper_context * ctx, const char * fname, const
             // fprintf(stderr,"token: %s %f\n",token,probability);
 	    }
     }
-    return true;
 }
 
-static bool output_json(
+static void output_json(
              struct whisper_context * ctx,
-                         const char * fname,
+                      std::ofstream & fout,
                const whisper_params & params,
-    std::vector<std::vector<float>>   pcmf32s,
-                               bool   full) {
-    std::ofstream fout(fname);
+    std::vector<std::vector<float>>   pcmf32s) {
+    const bool full = params.output_jsn_full;
     int indent = 0;
 
     auto doindent = [&]() {
@@ -670,12 +676,6 @@ static bool output_json(
         end_obj(end);
     };
 
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
     start_obj(nullptr);
         value_s("systeminfo", whisper_print_system_info(), false);
         start_obj("model");
@@ -749,17 +749,12 @@ static bool output_json(
 
         end_arr(true);
     end_obj(true);
-    return true;
 }
 
 // karaoke video generation
 // outputs a bash script that uses ffmpeg to generate a video with the subtitles
 // TODO: font parameter adjustments
-static bool output_wts(struct whisper_context * ctx, const char * fname, const char * fname_inp, const whisper_params & params, float t_sec, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static bool output_wts(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s, const char * fname_inp, float t_sec, const char * fname_out) {
     static const char * font = params.font_path.c_str();
 
     std::ifstream fin(font);
@@ -875,20 +870,12 @@ static bool output_wts(struct whisper_context * ctx, const char * fname, const c
 
     fout.close();
 
-    fprintf(stderr, "%s: run 'source %s' to generate karaoke video\n", __func__, fname);
+    fprintf(stderr, "# %s: run 'source %s' to generate karaoke video\n", __func__, fname_out);
 
     return true;
 }
 
-static bool output_lrc(struct whisper_context * ctx, const char * fname, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
-    std::ofstream fout(fname);
-    if (!fout.is_open()) {
-        fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname);
-        return false;
-    }
-
-    fprintf(stderr, "%s: saving output to '%s'\n", __func__, fname);
-
+static void output_lrc(struct whisper_context * ctx, std::ofstream & fout, const whisper_params & params, std::vector<std::vector<float>> pcmf32s) {
     fout << "[by:whisper.cpp]\n";
 
     const int n_segments = whisper_full_n_segments(ctx);
@@ -916,14 +903,14 @@ static bool output_lrc(struct whisper_context * ctx, const char * fname, const w
 
         fout <<  '[' << timestamp_lrc << ']' << speaker << text << "\n";
     }
-
-    return true;
 }
 
 
 static void cb_log_disable(enum ggml_log_level , const char * , void * ) { }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
 #if defined(_WIN32)
     // Set the console output code page to UTF-8, while command line arguments
     // are still encoded in the system's code page. In this way, we can print
@@ -1003,7 +990,6 @@ int main(int argc, char ** argv) {
     }
 
     // whisper init
-
     struct whisper_context_params cparams = whisper_context_default_params();
 
     cparams.use_gpu    = params.use_gpu;
@@ -1066,8 +1052,55 @@ int main(int argc, char ** argv) {
     }
 
     for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
-        const auto fname_inp = params.fname_inp[f];
-		const auto fname_out = f < (int) params.fname_out.size() && !params.fname_out[f].empty() ? params.fname_out[f] : params.fname_inp[f];
+        const auto & fname_inp = params.fname_inp[f];
+        struct fout_factory {
+            std::string fname_out;
+            const size_t basename_length;
+            const bool is_stdout;
+            bool used_stdout;
+            decltype(whisper_print_segment_callback) * const print_segment_callback;
+            std::ofstream fout;
+
+            fout_factory (const std::string & fname_out_, const std::string & fname_inp, whisper_params & params) :
+                    fname_out{!fname_out_.empty() ? fname_out_ : fname_inp},
+                    basename_length{fname_out.size()},
+                    is_stdout{fname_out == "-"},
+                    used_stdout{},
+                    print_segment_callback{is_stdout ? nullptr : whisper_print_segment_callback} {
+                if (!print_segment_callback) {
+                    params.print_progress = false;
+                }
+            }
+
+            bool open(const char * ext, const char * function) {
+                if (is_stdout) {
+                    if (used_stdout) {
+                        fprintf(stderr, "warning: Not appending multiple file formats to stdout\n");
+                        return false;
+                    }
+
+                    used_stdout = true;
+#ifdef _WIN32
+                    fout = std::ofstream{"CON"};
+#else
+                    fout = std::ofstream{"/dev/stdout"};
+#endif
+                    // Not using fprintf stderr here because it might equal stdout
+                    // Also assuming /dev is mounted
+                    return true;
+                }
+
+                fname_out.resize(basename_length);
+                fname_out += ext;
+                fout = std::ofstream{fname_out};
+                if (!fout.is_open()) {
+                    fprintf(stderr, "%s: failed to open '%s' for writing\n", __func__, fname_out.c_str());
+                    return false;
+                }
+                fprintf(stderr, "%s: saving output to '%s'\n", function, fname_out.c_str());
+                return true;
+            }
+        } fout_factory{f < (int) params.fname_out.size() ? params.fname_out[f] : "", fname_inp, params};
 
         std::vector<float> pcmf32;               // mono-channel F32 PCM
         std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
@@ -1104,6 +1137,11 @@ int main(int argc, char ** argv) {
                     params.tinydiarize ? "tdrz = 1, " : "",
                     params.no_timestamps ? 0 : 1);
 
+            if (params.print_colors) {
+                fprintf(stderr, "%s: color scheme: red (low confidence), yellow (medium), green (high confidence)\n", __func__);
+            } else if (params.print_confidence) {
+                fprintf(stderr, "%s: confidence: highlighted (low confidence), underlined (medium), dim (high confidence)\n", __func__);
+            }
             fprintf(stderr, "\n");
         }
 
@@ -1154,6 +1192,16 @@ int main(int argc, char ** argv) {
 
             wparams.suppress_nst     = params.suppress_nst;
 
+            wparams.vad            = params.vad;
+            wparams.vad_model_path = params.vad_model.c_str();
+
+            wparams.vad_params.threshold               = params.vad_threshold;
+            wparams.vad_params.min_speech_duration_ms  = params.vad_min_speech_duration_ms;
+            wparams.vad_params.min_silence_duration_ms = params.vad_min_silence_duration_ms;
+            wparams.vad_params.max_speech_duration_s   = params.vad_max_speech_duration_s;
+            wparams.vad_params.speech_pad_ms           = params.vad_speech_pad_ms;
+            wparams.vad_params.samples_overlap         = params.vad_samples_overlap;
+
             whisper_print_user_data user_data = { &params, &pcmf32s, 0 };
 
             const auto & grammar_parsed = params.grammar_parsed;
@@ -1172,7 +1220,7 @@ int main(int argc, char ** argv) {
 
             // this callback is called on each new segment
             if (!wparams.print_realtime) {
-                wparams.new_segment_callback           = whisper_print_segment_callback;
+                wparams.new_segment_callback           = fout_factory.print_segment_callback;
                 wparams.new_segment_callback_user_data = &user_data;
             }
 
@@ -1214,54 +1262,26 @@ int main(int argc, char ** argv) {
 
         // output stuff
         {
-            printf("\n");
+            // macros to stringify function name
+#define output_func(func, ext, param, ...) if (param && fout_factory.open(ext, #func)) {\
+    func(ctx, fout_factory.fout, params, __VA_ARGS__); \
+}
+#define output_ext(ext, ...) output_func(output_##ext, "." #ext, params.output_##ext, __VA_ARGS__)
 
-            // output to text file
-            if (params.output_txt) {
-                const auto fname_txt = fname_out + ".txt";
-                output_txt(ctx, fname_txt.c_str(), params, pcmf32s);
-            }
+            output_ext(txt, pcmf32s);
+            output_ext(vtt, pcmf32s);
+            output_ext(srt, pcmf32s);
+            output_ext(wts, pcmf32s, fname_inp.c_str(), float(pcmf32.size() + 1000)/WHISPER_SAMPLE_RATE, fout_factory.fname_out.c_str());
+            output_ext(csv, pcmf32s);
+            output_func(output_json, ".json", params.output_jsn, pcmf32s);
+            output_ext(lrc, pcmf32s);
+            output_func(output_score, ".score.txt", params.log_score, pcmf32s);
 
-            // output to VTT file
-            if (params.output_vtt) {
-                const auto fname_vtt = fname_out + ".vtt";
-                output_vtt(ctx, fname_vtt.c_str(), params, pcmf32s);
-            }
+#undef output_ext
+#undef output_func
 
-            // output to SRT file
-            if (params.output_srt) {
-                const auto fname_srt = fname_out + ".srt";
-                output_srt(ctx, fname_srt.c_str(), params, pcmf32s);
-            }
-
-            // output to WTS file
-            if (params.output_wts) {
-                const auto fname_wts = fname_out + ".wts";
-                output_wts(ctx, fname_wts.c_str(), fname_inp.c_str(), params, float(pcmf32.size() + 1000)/WHISPER_SAMPLE_RATE, pcmf32s);
-            }
-
-            // output to CSV file
-            if (params.output_csv) {
-                const auto fname_csv = fname_out + ".csv";
-                output_csv(ctx, fname_csv.c_str(), params, pcmf32s);
-            }
-
-            // output to JSON file
-            if (params.output_jsn) {
-                const auto fname_jsn = fname_out + ".json";
-                output_json(ctx, fname_jsn.c_str(), params, pcmf32s, params.output_jsn_full);
-            }
-
-            // output to LRC file
-            if (params.output_lrc) {
-                const auto fname_lrc = fname_out + ".lrc";
-                output_lrc(ctx, fname_lrc.c_str(), params, pcmf32s);
-            }
-
-            // output to score file
-            if (params.log_score) {
-                const auto fname_score = fname_out + ".score.txt";
-                output_score(ctx, fname_score.c_str(), params, pcmf32s);
+            if (fout_factory.is_stdout && !fout_factory.used_stdout) {
+                fprintf(stderr, "warning: '--output-file -' used without any other '--output-*'");
             }
         }
     }

examples/command.wasm/CMakeLists.txt

@@ -36,7 +36,7 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     -s INITIAL_MEMORY=1024MB \
     -s TOTAL_MEMORY=1024MB \
     -s FORCE_FILESYSTEM=1 \
-    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
+    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap', 'HEAPU8']\" \
     ${EXTRA_FLAGS} \
     ")
 

examples/command.wasm/README.md

@@ -28,5 +28,10 @@ To run the example in a different server, you need to copy the following files
 to the server's HTTP path:
 ```
 cp bin/command.wasm/*       /path/to/html/
+cp bin/libcommand.js        /path/to/html/
 cp bin/libcommand.worker.js /path/to/html/
 ```
+
+> 📝 **Note:** As of Emscripten 3.1.58 (April 2024), separate worker.js files are no
+> longer generated and the worker is embedded in the main JS file. So the worker
+> file will not be geneated for versions later than `3.1.58`.

examples/command/command.cpp

@@ -3,7 +3,7 @@
 // Speak short text commands to the microphone.
 // This program will detect your voice command and convert them to text.
 //
-// ref: https://github.com/ggerganov/whisper.cpp/issues/171
+// ref: https://github.com/ggml-org/whisper.cpp/issues/171
 //
 
 #include "common-sdl.h"
@@ -251,7 +251,7 @@ static std::vector<std::string> get_words(const std::string &txt) {
 
 // command-list mode
 // guide the transcription to match the most likely command from a provided list
-static int process_command_list(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
+static int process_command_list(struct whisper_context * ctx, audio_async &audio, const whisper_params &params, std::ofstream &fout) {
     fprintf(stderr, "\n");
     fprintf(stderr, "%s: guided mode\n", __func__);
 
@@ -444,12 +444,16 @@ static int process_command_list(struct whisper_context * ctx, audio_async &audio
 
                     const float prob = probs_id[0].first;
                     const int index = probs_id[0].second;
+                    const char * best_command = allowed_commands[index].c_str();
 
                     fprintf(stdout, "\n");
                     fprintf(stdout, "%s: detected command: %s%s%s | p = %f | t = %d ms\n", __func__,
-                            "\033[1m", allowed_commands[index].c_str(), "\033[0m", prob,
+                            "\033[1m", best_command, "\033[0m", prob,
                             (int) std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count());
                     fprintf(stdout, "\n");
+                    if (fout.is_open()) {
+                        fout << best_command << std::endl;
+                    }
                 }
             }
 
@@ -462,7 +466,7 @@ static int process_command_list(struct whisper_context * ctx, audio_async &audio
 
 // always-prompt mode
 // transcribe the voice into text after valid prompt
-static int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
+static int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params, std::ofstream & fout) {
     bool is_running = true;
     bool ask_prompt = true;
 
@@ -528,6 +532,9 @@ static int always_prompt_transcription(struct whisper_context * ctx, audio_async
 
                 if ((sim > 0.7f) && (command.size() > 0)) {
                     fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
+                    if (fout.is_open()) {
+                        fout << command << std::endl;
+                    }
                 }
 
                 fprintf(stdout, "\n");
@@ -542,7 +549,7 @@ static int always_prompt_transcription(struct whisper_context * ctx, audio_async
 
 // general-purpose mode
 // freely transcribe the voice into text
-static int process_general_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
+static int process_general_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params, std::ofstream & fout) {
     bool is_running  = true;
     bool have_prompt = false;
     bool ask_prompt  = true;
@@ -662,8 +669,10 @@ static int process_general_transcription(struct whisper_context * ctx, audio_asy
                     } else {
                         // cut the prompt from the decoded text
                         const std::string command = ::trim(txt.substr(best_len));
-
                         fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
+                        if (fout.is_open()) {
+                            fout << command << std::endl;
+                        }
                     }
 
                     fprintf(stdout, "\n");
@@ -678,6 +687,8 @@ static int process_general_transcription(struct whisper_context * ctx, audio_asy
 }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     whisper_params params;
 
     if (whisper_params_parse(argc, argv, params) == false) {
@@ -698,6 +709,10 @@ int main(int argc, char ** argv) {
     cparams.flash_attn = params.flash_attn;
 
     struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
+    if (ctx == nullptr) {
+        fprintf(stderr, "error: failed to initialize whisper context\n");
+        return 2;
+    }
 
     // print some info about the processing
     {
@@ -757,13 +772,22 @@ int main(int argc, char ** argv) {
         }
     }
 
+    std::ofstream fout;
+    if (params.fname_out.length() > 0) {
+        fout.open(params.fname_out);
+        if (!fout.is_open()) {
+            fprintf(stderr, "%s: failed to open output file '%s'!\n", __func__, params.fname_out.c_str());
+            return 1;
+        }
+    }
+
     if (ret_val == 0) {
         if (!params.commands.empty()) {
-            ret_val = process_command_list(ctx, audio, params);
+            ret_val = process_command_list(ctx, audio, params, fout);
         } else if (!params.prompt.empty() && params.grammar_parsed.rules.empty()) {
-            ret_val = always_prompt_transcription(ctx, audio, params);
+            ret_val = always_prompt_transcription(ctx, audio, params, fout);
         } else {
-            ret_val = process_general_transcription(ctx, audio, params);
+            ret_val = process_general_transcription(ctx, audio, params, fout);
         }
     }
 

examples/common-whisper.cpp

@@ -26,10 +26,6 @@
 #define MINIAUDIO_IMPLEMENTATION
 #include "miniaudio.h"
 
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
-#endif
-
 #ifdef _WIN32
 #include <fcntl.h>
 #include <io.h>
@@ -116,13 +112,20 @@ bool read_audio_data(const std::string & fname, std::vector<float>& pcmf32, std:
     }
 
     if (stereo) {
-		pcmf32s.resize(2);
-		pcmf32s[0].resize(frame_count);
-		pcmf32s[1].resize(frame_count);
-		for (uint64_t i = 0; i < frame_count; i++) {
-			pcmf32s[0][i] = pcmf32[2*i];
-			pcmf32s[1][i] = pcmf32[2*i + 1];
-		}
+        std::vector<float> stereo_data = pcmf32;
+        pcmf32.resize(frame_count);
+
+        for (uint64_t i = 0; i < frame_count; i++) {
+            pcmf32[i] = (stereo_data[2*i] + stereo_data[2*i + 1]);
+        }
+
+        pcmf32s.resize(2);
+        pcmf32s[0].resize(frame_count);
+        pcmf32s[1].resize(frame_count);
+        for (uint64_t i = 0; i < frame_count; i++) {
+            pcmf32s[0][i] = stereo_data[2*i];
+            pcmf32s[1][i] = stereo_data[2*i + 1];
+        }
     }
 
     ma_decoder_uninit(&decoder);

examples/common.cpp

@@ -10,10 +10,6 @@
 #include <regex>
 #include <sstream>
 
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
-#endif
-
 // Function to check if the next argument exists
 static std::string get_next_arg(int& i, int argc, char** argv, const std::string& flag, gpt_params& params) {
     if (i + 1 < argc && argv[i + 1][0] != '-') {

examples/common.h

@@ -283,7 +283,7 @@ static std::string set_xterm256_foreground(int r, int g, int b) {
 }
 
 // Lowest is red, middle is yellow, highest is green. Color scheme from
-// Paul Tol; it is colorblind friendly https://personal.sron.nl/~pault/
+// Paul Tol; it is colorblind friendly https://sronpersonalpages.nl/~pault
 const std::vector<std::string> k_colors = {
     set_xterm256_foreground(220,   5,  12),
     set_xterm256_foreground(232,  96,  28),
@@ -294,6 +294,26 @@ const std::vector<std::string> k_colors = {
     set_xterm256_foreground( 78, 178, 101),
 };
 
+// ANSI formatting codes
+static std::string set_inverse() {
+    return "\033[7m";
+}
+
+static std::string set_underline() {
+    return "\033[4m";
+}
+
+static std::string set_dim() {
+    return "\033[2m";
+}
+
+// Style scheme for different confidence levels
+const std::vector<std::string> k_styles = {
+    set_inverse(),   // Low confidence - inverse (highlighted)
+    set_underline(), // Medium confidence - underlined
+    set_dim(),       // High confidence - dim
+};
+
 //
 // Other utils
 //

examples/ffmpeg-transcode.cpp

@@ -194,7 +194,7 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 	AVIOContext *avio_ctx;
 	AVStream *stream;
 	AVCodecContext *codec;
-	AVPacket packet;
+	AVPacket *packet;
 	AVFrame *frame;
 	struct SwrContext *swr;
 	u8 *avio_ctx_buffer;
@@ -249,6 +249,20 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 	/* prepare resampler */
 	swr = swr_alloc();
 
+#if LIBAVCODEC_VERSION_MAJOR > 60
+	AVChannelLayout in_ch_layout = codec->ch_layout;
+	AVChannelLayout out_ch_layout = AV_CHANNEL_LAYOUT_MONO;
+
+	/* Set the source audio layout as-is */
+	av_opt_set_chlayout(swr, "in_chlayout", &in_ch_layout, 0);
+	av_opt_set_int(swr, "in_sample_rate", codec->sample_rate, 0);
+	av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0);
+
+	/* Convert it into 16khz Mono */
+	av_opt_set_chlayout(swr, "out_chlayout", &out_ch_layout, 0);
+	av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0);
+	av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0);
+#else
 	av_opt_set_int(swr, "in_channel_count", codec->channels, 0);
 	av_opt_set_int(swr, "out_channel_count", 1, 0);
 	av_opt_set_int(swr, "in_channel_layout", codec->channel_layout, 0);
@@ -257,6 +271,7 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 	av_opt_set_int(swr, "out_sample_rate", WAVE_SAMPLE_RATE, 0);
 	av_opt_set_sample_fmt(swr, "in_sample_fmt", codec->sample_fmt, 0);
 	av_opt_set_sample_fmt(swr, "out_sample_fmt", AV_SAMPLE_FMT_S16, 0);
+#endif
 
 	swr_init(swr);
 	if (!swr_is_initialized(swr)) {
@@ -264,7 +279,11 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 		return -1;
 	}
 
-	av_init_packet(&packet);
+	packet=av_packet_alloc();
+	if (!packet) {
+		LOG("Error allocating the packet\n");
+		return -1;
+	}
 	frame = av_frame_alloc();
 	if (!frame) {
         LOG("Error allocating the frame\n");
@@ -274,8 +293,8 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 	/* iterate through frames */
 	*data = NULL;
 	*size = 0;
-	while (av_read_frame(fmt_ctx, &packet) >= 0) {
-		avcodec_send_packet(codec, &packet);
+	while (av_read_frame(fmt_ctx, packet) >= 0) {
+		avcodec_send_packet(codec, packet);
 
 		err = avcodec_receive_frame(codec, frame);
 		if (err == AVERROR(EAGAIN))
@@ -286,10 +305,11 @@ static int decode_audio(struct audio_buffer *audio_buf, s16 **data, int *size)
 	/* Flush any remaining conversion buffers... */
 	convert_frame(swr, codec, frame, data, size, true);
 
+	av_packet_free(&packet);
 	av_frame_free(&frame);
 	swr_free(&swr);
     //avio_context_free(); // todo?
-	avcodec_close(codec);
+	avcodec_free_context(&codec);
 	avformat_close_input(&fmt_ctx);
 	avformat_free_context(fmt_ctx);
 

examples/livestream.sh

@@ -2,7 +2,7 @@
 #
 # Transcribe audio livestream by feeding ffmpeg output to whisper.cpp at regular intervals
 # Idea by @semiformal-net
-# ref: https://github.com/ggerganov/whisper.cpp/issues/185
+# ref: https://github.com/ggml-org/whisper.cpp/issues/185
 #
 
 set -eo pipefail

examples/lsp/lsp.cpp

@@ -424,6 +424,8 @@ static void process_loop(struct whisper_context * ctx, audio_async &audio, const
 }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     whisper_params params;
     if (whisper_params_parse(argc, argv, params) == false) {
         return 1;

examples/quantize/quantize.cpp

@@ -1,4 +1,5 @@
 #include "ggml.h"
+#include "ggml-backend.h"
 
 #include "common.h"
 #include "common-ggml.h"
@@ -176,6 +177,8 @@ static bool whisper_model_quantize(const std::string & fname_inp, const std::str
 }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     if (argc != 4) {
         fprintf(stderr, "usage: %s model-f32.bin model-quant.bin type\n", argv[0]);
         ggml_print_ftypes(stderr);

examples/server.py

@@ -1,39 +1,115 @@
 import http.server
 import socketserver
 import os
+import sys
 from pathlib import Path
+import urllib.parse
 
 SCRIPT_DIR = Path(__file__).parent.absolute()
 DIRECTORY = os.path.join(SCRIPT_DIR, "../build-em/bin")
 DIRECTORY = os.path.abspath(DIRECTORY)
 
+# The context root we want for all applications
+CONTEXT_ROOT = "/whisper.cpp"
+
 class CustomHTTPRequestHandler(http.server.SimpleHTTPRequestHandler):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, directory=DIRECTORY, **kwargs)
 
     def do_GET(self):
-        # If requesting a worker file from any subdirectory
-        if '.worker.js' in self.path:
+        # Redirect root to the context root
+        if self.path == '/':
+            self.send_response(302)
+            self.send_header('Location', CONTEXT_ROOT + '/')
+            self.end_headers()
+            return
+
+        # Handle requests under the context root
+        if self.path.startswith(CONTEXT_ROOT):
+            # Remove the context root prefix to get the actual path
+            actual_path = self.path[len(CONTEXT_ROOT):]
+
+            if not actual_path:
+                self.send_response(302)
+                self.send_header('Location', CONTEXT_ROOT + '/')
+                self.end_headers()
+                return
+
+            if '.worker.js' in actual_path:
+                worker_file = os.path.basename(actual_path)
+                worker_path = os.path.join(DIRECTORY, worker_file)
+
+                if os.path.exists(worker_path):
+                    print(f"Found worker file: {worker_path}")
+                    self.path = '/' + worker_file
+                else:
+                    print(f"Worker file not found: {worker_path}")
+
+            elif actual_path == '/':
+                self.path = '/whisper.wasm/index.html'
+            elif actual_path.startswith('/bench.wasm/') or actual_path.startswith('/command.wasm/') or actual_path.startswith('/stream.wasm/'):
+                # Keep the path as is, just remove the context root
+                self.path = actual_path
+            # For all other paths under the context root
+            else:
+                # Check if this is a request to a file in whisper.wasm
+                potential_file = os.path.join(DIRECTORY, 'whisper.wasm', actual_path.lstrip('/'))
+                if os.path.exists(potential_file) and not os.path.isdir(potential_file):
+                    self.path = '/whisper.wasm' + actual_path
+                else:
+                    # Try to resolve the file from the base directory
+                    potential_file = os.path.join(DIRECTORY, actual_path.lstrip('/'))
+                    if os.path.exists(potential_file):
+                        self.path = actual_path
+
+        # For direct requests to worker files (without context root as these
+        # are in the build-em/bin directory
+        elif '.worker.js' in self.path:
             worker_file = os.path.basename(self.path)
             worker_path = os.path.join(DIRECTORY, worker_file)
 
             if os.path.exists(worker_path):
                 self.path = '/' + worker_file
 
+        # Handle coi-serviceworker.js separately
+        if 'coi-serviceworker.js' in self.path:
+            worker_file = "coi-serviceworker.js"
+            worker_path = os.path.join(SCRIPT_DIR, worker_file)
+            if os.path.exists(worker_path):
+                self.send_response(200)
+                self.send_header('Content-type', 'application/javascript')
+                self.end_headers()
+                with open(worker_path, 'rb') as file:
+                    self.wfile.write(file.read())
+                return
+            else:
+                print(f"Warning: Could not find {worker_path}")
+
         return super().do_GET()
 
     def end_headers(self):
         # Add required headers for SharedArrayBuffer
         self.send_header("Cross-Origin-Opener-Policy", "same-origin")
         self.send_header("Cross-Origin-Embedder-Policy", "require-corp")
-        self.send_header("Access-Control-Allow-Origin", "*");
+        self.send_header("Access-Control-Allow-Origin", "*")
         super().end_headers()
 
 PORT = 8000
 
-with socketserver.TCPServer(("", PORT), CustomHTTPRequestHandler) as httpd:
-    print(f"Serving directory '{DIRECTORY}' at http://localhost:{PORT}")
-    try:
-        httpd.serve_forever()
-    except KeyboardInterrupt:
-        print("\nServer stopped.")
+# Enable address reuse
+class CustomServer(socketserver.TCPServer):
+    allow_reuse_address = True
+
+try:
+    with CustomServer(("", PORT), CustomHTTPRequestHandler) as httpd:
+        print(f"Serving directory '{DIRECTORY}' at http://localhost:{PORT}")
+        print(f"Application context root: http://localhost:{PORT}{CONTEXT_ROOT}/")
+        try:
+            httpd.serve_forever()
+        except KeyboardInterrupt:
+            print("\nServer stopped.")
+            # Force complete exit
+            sys.exit(0)
+except OSError as e:
+    print(f"Error: {e}")
+    sys.exit(1)

examples/server/CMakeLists.txt

@@ -1,3 +1,6 @@
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+
 set(TARGET whisper-server)
 add_executable(${TARGET} server.cpp httplib.h)
 

examples/server/README.md

@@ -23,6 +23,7 @@ options:
   -sow,      --split-on-word     [false  ] split on word rather than on token
   -bo N,     --best-of N         [2      ] number of best candidates to keep
   -bs N,     --beam-size N       [-1     ] beam size for beam search
+  -ac N,     --audio-ctx N       [0      ] audio context size (0 - all)
   -wt N,     --word-thold N      [0.01   ] word timestamp probability threshold
   -et N,     --entropy-thold N   [2.40   ] entropy threshold for decoder fail
   -lpt N,    --logprob-thold N   [-1.00  ] log probability threshold for decoder fail
@@ -41,9 +42,28 @@ options:
              --prompt PROMPT     [       ] initial prompt
   -m FNAME,  --model FNAME       [models/ggml-base.en.bin] model path
   -oved D,   --ov-e-device DNAME [CPU    ] the OpenVINO device used for encode inference
+  -dtw MODEL --dtw MODEL         [       ] compute token-level timestamps
   --host HOST,                   [127.0.0.1] Hostname/ip-adress for the server
   --port PORT,                   [8080   ] Port number for the server
+  --public PATH,                 [examples/server/public] Path to the public folder
+  --request-path PATH,           [       ] Request path for all requests
+  --inference-path PATH,         [/inference] Inference path for all requests
   --convert,                     [false  ] Convert audio to WAV, requires ffmpeg on the server
+  -sns,      --suppress-nst      [false  ] suppress non-speech tokens
+  -nth N,    --no-speech-thold N [0.60   ] no speech threshold
+  -nc,       --no-context        [false  ] do not use previous audio context
+  -ng,       --no-gpu            [false  ] do not use gpu
+  -fa,       --flash-attn        [false  ] flash attention
+
+Voice Activity Detection (VAD) options:
+             --vad                           [false  ] enable Voice Activity Detection (VAD)
+  -vm FNAME, --vad-model FNAME               [       ] VAD model path
+  -vt N,     --vad-threshold N               [0.50   ] VAD threshold for speech recognition
+  -vspd N,   --vad-min-speech-duration-ms  N [250    ] VAD min speech duration (0.0-1.0)
+  -vsd N,    --vad-min-silence-duration-ms N [100    ] VAD min silence duration (to split segments)
+  -vmsd N,   --vad-max-speech-duration-s   N [FLT_MAX] VAD max speech duration (auto-split longer)
+  -vp N,     --vad-speech-pad-ms           N [30     ] VAD speech padding (extend segments)
+  -vo N,     --vad-samples-overlap         N [0.10   ] VAD samples overlap (seconds between segments)
 ```
 
 > [!WARNING]
@@ -67,3 +87,35 @@ curl 127.0.0.1:8080/load \
 -H "Content-Type: multipart/form-data" \
 -F model="<path-to-model-file>"
 ```
+
+## Load testing with k6
+
+> **Note:** Install [k6](https://k6.io/docs/get-started/installation/) before running the benchmark script.
+
+You can benchmark the Whisper server using the provided bench.js script with [k6](https://k6.io/). This script sends concurrent multipart requests to the /inference endpoint and is fully configurable via environment variables.
+
+**Example usage:**
+
+```
+k6 run bench.js \
+  --env FILE_PATH=/absolute/path/to/samples/jfk.wav \
+  --env BASE_URL=http://127.0.0.1:8080 \
+  --env ENDPOINT=/inference \
+  --env CONCURRENCY=4 \
+  --env TEMPERATURE=0.0 \
+  --env TEMPERATURE_INC=0.2 \
+  --env RESPONSE_FORMAT=json
+```
+
+**Environment variables:**
+- `FILE_PATH`: Path to the audio file to send (must be absolute or relative to the k6 working directory)
+- `BASE_URL`: Server base URL (default: `http://127.0.0.1:8080`)
+- `ENDPOINT`: API endpoint (default: `/inference`)
+- `CONCURRENCY`: Number of concurrent requests (default: 4)
+- `TEMPERATURE`: Decoding temperature (default: 0.0)
+- `TEMPERATURE_INC`: Temperature increment (default: 0.2)
+- `RESPONSE_FORMAT`: Response format (default: `json`)
+
+**Note:**
+- The server must be running and accessible at the specified `BASE_URL` and `ENDPOINT`.
+- The script is located in the same directory as this README: `bench.js`.

examples/server/bench.js

@@ -0,0 +1,29 @@
+import http from 'k6/http'
+import { check } from 'k6'
+
+export let options = {
+  vus: parseInt(__ENV.CONCURRENCY) || 4,
+  iterations: parseInt(__ENV.CONCURRENCY) || 4,
+}
+
+const filePath        = __ENV.FILE_PATH
+const baseURL         = __ENV.BASE_URL        || 'http://127.0.0.1:8080'
+const endpoint        = __ENV.ENDPOINT        || '/inference'
+const temperature     = __ENV.TEMPERATURE     || '0.0'
+const temperatureInc  = __ENV.TEMPERATURE_INC || '0.2'
+const responseFormat  = __ENV.RESPONSE_FORMAT || 'json'
+
+// Read the file ONCE at init time
+const fileBin = open(filePath, 'b')
+
+export default function () {
+  const payload = {
+    file:           http.file(fileBin, filePath),
+    temperature:    temperature,
+    temperature_inc: temperatureInc,
+    response_format: responseFormat,
+  }
+
+  const res = http.post(`${baseURL}${endpoint}`, payload)
+  check(res, { 'status is 200': r => r.status === 200 })
+} 

examples/server/server.cpp

@@ -5,6 +5,7 @@
 #include "httplib.h"
 #include "json.hpp"
 
+#include <cfloat>
 #include <chrono>
 #include <cmath>
 #include <cstdio>
@@ -13,14 +14,23 @@
 #include <string>
 #include <thread>
 #include <vector>
-
-#if defined(_MSC_VER)
-#pragma warning(disable: 4244 4267) // possible loss of data
+#include <memory>
+#include <csignal>
+#include <atomic>
+#include <functional>
+#include <cstdlib>
+#if defined (_WIN32)
+#include <windows.h>
 #endif
 
 using namespace httplib;
 using json = nlohmann::ordered_json;
 
+enum server_state {
+    SERVER_STATE_LOADING_MODEL,  // Server is starting up, model not fully loaded yet
+    SERVER_STATE_READY,          // Server is ready and model is loaded
+};
+
 namespace {
 
 // output formats
@@ -30,6 +40,20 @@ const std::string srt_format    = "srt";
 const std::string vjson_format  = "verbose_json";
 const std::string vtt_format    = "vtt";
 
+std::function<void(int)> shutdown_handler;
+std::atomic_flag is_terminating = ATOMIC_FLAG_INIT;
+
+inline void signal_handler(int signal) {
+    if (is_terminating.test_and_set()) {
+        // in case it hangs, we can force terminate the server by hitting Ctrl+C twice
+        // this is for better developer experience, we can remove when the server is stable enough
+        fprintf(stderr, "Received second interrupt, terminating immediately.\n");
+        exit(1);
+    }
+
+    shutdown_handler(signal);
+}
+
 struct server_params
 {
     std::string hostname = "127.0.0.1";
@@ -79,6 +103,7 @@ struct whisper_params {
     bool use_gpu         = true;
     bool flash_attn      = false;
     bool suppress_nst    = false;
+    bool no_context      = false;
 
     std::string language        = "en";
     std::string prompt          = "";
@@ -93,6 +118,16 @@ struct whisper_params {
     std::string openvino_encode_device = "CPU";
 
     std::string dtw = "";
+
+    // Voice Activity Detection (VAD) parameters
+    bool        vad           = false;
+    std::string vad_model     = "";
+    float       vad_threshold = 0.5f;
+    int         vad_min_speech_duration_ms = 250;
+    int         vad_min_silence_duration_ms = 100;
+    float       vad_max_speech_duration_s = FLT_MAX;
+    int         vad_speech_pad_ms = 30;
+    float       vad_samples_overlap = 0.1f;
 };
 
 void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & params, const server_params& sparams) {
@@ -140,6 +175,21 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
     fprintf(stderr, "  --convert,                     [%-7s] Convert audio to WAV, requires ffmpeg on the server\n", sparams.ffmpeg_converter ? "true" : "false");
     fprintf(stderr, "  -sns,      --suppress-nst      [%-7s] suppress non-speech tokens\n", params.suppress_nst ? "true" : "false");
     fprintf(stderr, "  -nth N,    --no-speech-thold N [%-7.2f] no speech threshold\n",   params.no_speech_thold);
+    fprintf(stderr, "  -nc,       --no-context        [%-7s] do not use previous audio context\n", params.no_context ? "true" : "false");
+    fprintf(stderr, "  -ng,       --no-gpu            [%-7s] do not use gpu\n", params.use_gpu ? "false" : "true");
+    fprintf(stderr, "  -fa,       --flash-attn        [%-7s] flash attention\n", params.flash_attn ? "true" : "false");
+    // Voice Activity Detection (VAD) parameters
+    fprintf(stderr, "\nVoice Activity Detection (VAD) options:\n");
+    fprintf(stderr, "             --vad                           [%-7s] enable Voice Activity Detection (VAD)\n",            params.vad ? "true" : "false");
+    fprintf(stderr, "  -vm FNAME, --vad-model FNAME               [%-7s] VAD model path\n",                                   params.vad_model.c_str());
+    fprintf(stderr, "  -vt N,     --vad-threshold N               [%-7.2f] VAD threshold for speech recognition\n",           params.vad_threshold);
+    fprintf(stderr, "  -vspd N,   --vad-min-speech-duration-ms  N [%-7d] VAD min speech duration (0.0-1.0)\n",                params.vad_min_speech_duration_ms);
+    fprintf(stderr, "  -vsd N,    --vad-min-silence-duration-ms N [%-7d] VAD min silence duration (to split segments)\n",      params.vad_min_silence_duration_ms);
+    fprintf(stderr, "  -vmsd N,   --vad-max-speech-duration-s   N [%-7s] VAD max speech duration (auto-split longer)\n",      params.vad_max_speech_duration_s == FLT_MAX ?
+                                                                                                                                  std::string("FLT_MAX").c_str() :
+                                                                                                                                  std::to_string(params.vad_max_speech_duration_s).c_str());
+    fprintf(stderr, "  -vp N,     --vad-speech-pad-ms           N [%-7d] VAD speech padding (extend segments)\n",             params.vad_speech_pad_ms);
+    fprintf(stderr, "  -vo N,     --vad-samples-overlap         N [%-7.2f] VAD samples overlap (seconds between segments)\n", params.vad_samples_overlap);
     fprintf(stderr, "\n");
 }
 
@@ -186,6 +236,7 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params, serve
         else if (arg == "-fa"   || arg == "--flash-attn")      { params.flash_attn      = true; }
         else if (arg == "-sns"  || arg == "--suppress-nst")    { params.suppress_nst    = true; }
         else if (arg == "-nth"  || arg == "--no-speech-thold") { params.no_speech_thold = std::stof(argv[++i]); }
+        else if (arg == "-nc"   || arg == "--no-context")      { params.no_context      = true; }
 
         // server params
         else if (                  arg == "--port")            { sparams.port        = std::stoi(argv[++i]); }
@@ -194,6 +245,16 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params, serve
         else if (                  arg == "--request-path")    { sparams.request_path = argv[++i]; }
         else if (                  arg == "--inference-path")  { sparams.inference_path = argv[++i]; }
         else if (                  arg == "--convert")         { sparams.ffmpeg_converter     = true; }
+
+        // Voice Activity Detection (VAD)
+        else if (                  arg == "--vad")                         { params.vad                         = true; }
+        else if (arg == "-vm"   || arg == "--vad-model")                   { params.vad_model                   = argv[++i]; }
+        else if (arg == "-vt"   || arg == "--vad-threshold")               { params.vad_threshold               = std::stof(argv[++i]); }
+        else if (arg == "-vspd" || arg == "--vad-min-speech-duration-ms")  { params.vad_min_speech_duration_ms  = std::stoi(argv[++i]); }
+        else if (arg == "-vsd"  || arg == "--vad-min-silence-duration-ms") { params.vad_min_speech_duration_ms  = std::stoi(argv[++i]); }
+        else if (arg == "-vmsd" || arg == "--vad-max-speech-duration-s")   { params.vad_max_speech_duration_s   = std::stof(argv[++i]); }
+        else if (arg == "-vp"   || arg == "--vad-speech-pad-ms")           { params.vad_speech_pad_ms           = std::stoi(argv[++i]); }
+        else if (arg == "-vo"   || arg == "--vad-samples-overlap")         { params.vad_samples_overlap         = std::stof(argv[++i]); }
         else {
             fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
             whisper_print_usage(argc, argv, params, sparams);
@@ -506,11 +567,45 @@ void get_req_parameters(const Request & req, whisper_params & params)
     {
         params.suppress_nst = parse_str_to_bool(req.get_file_value("suppress_nst").content);
     }
+    if (req.has_file("no_context"))
+    {
+        params.no_context = parse_str_to_bool(req.get_file_value("no_context").content);
+    }
+    if (req.has_file("vad"))
+    {
+        params.vad = parse_str_to_bool(req.get_file_value("vad").content);
+    }
+    if (req.has_file("vad_threshold"))
+    {
+        params.vad_threshold = std::stof(req.get_file_value("vad_threshold").content);
+    }
+    if (req.has_file("vad_min_speech_duration_ms"))
+    {
+        params.vad_min_speech_duration_ms = std::stof(req.get_file_value("vad_min_speech_duration_ms").content);
+    }
+    if (req.has_file("vad_min_silence_duration_ms"))
+    {
+        params.vad_min_silence_duration_ms = std::stof(req.get_file_value("vad_min_silence_duration_ms").content);
+    }
+    if (req.has_file("vad_max_speech_duration_s"))
+    {
+        params.vad_max_speech_duration_s = std::stof(req.get_file_value("vad_max_speech_duration_s").content);
+    }
+    if (req.has_file("vad_speech_pad_ms"))
+    {
+        params.vad_speech_pad_ms = std::stoi(req.get_file_value("vad_speech_pad_ms").content);
+    }
+    if (req.has_file("vad_samples_overlap"))
+    {
+        params.vad_samples_overlap = std::stof(req.get_file_value("vad_samples_overlap").content);
+    }
 }
 
 }  // namespace
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     whisper_params params;
     server_params sparams;
 
@@ -586,6 +681,9 @@ int main(int argc, char ** argv) {
         }
     }
 
+    std::unique_ptr<httplib::Server> svr = std::make_unique<httplib::Server>();
+    std::atomic<server_state> state{SERVER_STATE_LOADING_MODEL};
+
     struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
 
     if (ctx == nullptr) {
@@ -595,9 +693,10 @@ int main(int argc, char ** argv) {
 
     // initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured
     whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr);
+    state.store(SERVER_STATE_READY);
 
-    Server svr;
-    svr.set_default_headers({{"Server", "whisper.cpp"},
+
+    svr->set_default_headers({{"Server", "whisper.cpp"},
                              {"Access-Control-Allow-Origin", "*"},
                              {"Access-Control-Allow-Headers", "content-type, authorization"}});
 
@@ -676,15 +775,15 @@ int main(int argc, char ** argv) {
     whisper_params default_params = params;
 
     // this is only called if no index.html is found in the public --path
-    svr.Get(sparams.request_path + "/", [&default_content](const Request &, Response &res){
+    svr->Get(sparams.request_path + "/", [&](const Request &, Response &res){
         res.set_content(default_content, "text/html");
         return false;
     });
 
-    svr.Options(sparams.request_path + sparams.inference_path, [&](const Request &, Response &){
+    svr->Options(sparams.request_path + sparams.inference_path, [&](const Request &, Response &){
     });
 
-    svr.Post(sparams.request_path + sparams.inference_path, [&](const Request &req, Response &res){
+    svr->Post(sparams.request_path + sparams.inference_path, [&](const Request &req, Response &res){
         // acquire whisper model mutex lock
         std::lock_guard<std::mutex> lock(whisper_mutex);
 
@@ -818,9 +917,20 @@ int main(int argc, char ** argv) {
 
             wparams.no_timestamps    = params.no_timestamps;
             wparams.token_timestamps = !params.no_timestamps && params.response_format == vjson_format;
+            wparams.no_context       = params.no_context;
 
             wparams.suppress_nst     = params.suppress_nst;
 
+            wparams.vad              = params.vad;
+            wparams.vad_model_path   = params.vad_model.c_str();
+
+            wparams.vad_params.threshold               = params.vad_threshold;
+            wparams.vad_params.min_speech_duration_ms  = params.vad_min_speech_duration_ms;
+            wparams.vad_params.min_silence_duration_ms = params.vad_min_silence_duration_ms;
+            wparams.vad_params.max_speech_duration_s   = params.vad_max_speech_duration_s;
+            wparams.vad_params.speech_pad_ms           = params.vad_speech_pad_ms;
+            wparams.vad_params.samples_overlap         = params.vad_samples_overlap;
+
             whisper_print_user_data user_data = { &params, &pcmf32s, 0 };
 
             // this callback is called on each new segment
@@ -834,33 +944,25 @@ int main(int argc, char ** argv) {
                 wparams.progress_callback_user_data = &user_data;
             }
 
-            // examples for abort mechanism
-            // in examples below, we do not abort the processing, but we could if the flag is set to true
-
-            // the callback is called before every encoder run - if it returns false, the processing is aborted
-            {
-                static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
-
-                wparams.encoder_begin_callback = [](struct whisper_context * /*ctx*/, struct whisper_state * /*state*/, void * user_data) {
-                    bool is_aborted = *(bool*)user_data;
-                    return !is_aborted;
-                };
-                wparams.encoder_begin_callback_user_data = &is_aborted;
-            }
-
-            // the callback is called before every computation - if it returns true, the computation is aborted
-            {
-                static bool is_aborted = false; // NOTE: this should be atomic to avoid data race
-
-                wparams.abort_callback = [](void * user_data) {
-                    bool is_aborted = *(bool*)user_data;
-                    return is_aborted;
-                };
-                wparams.abort_callback_user_data = &is_aborted;
-            }
+            // tell whisper to abort if the HTTP connection closed
+            wparams.abort_callback = [](void *user_data) {
+                // user_data is a pointer to our Request
+                auto req_ptr = static_cast<const httplib::Request*>(user_data);
+                return req_ptr->is_connection_closed();
+            };
+            wparams.abort_callback_user_data = (void*)&req;
 
             if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
+                // handle failure or early abort
+                if (req.is_connection_closed()) {
+                    // log client disconnect
+                    fprintf(stderr, "client disconnected, aborted processing\n");
+                    res.status = 499; // Client Closed Request (nginx convention)
+                    res.set_content("{\"error\":\"client disconnected\"}", "application/json");
+                    return;
+                }
                 fprintf(stderr, "%s: failed to process audio\n", argv[0]);
+                res.status = 500; // Internal Server Error
                 const std::string error_resp = "{\"error\":\"failed to process audio\"}";
                 res.set_content(error_resp, "application/json");
                 return;
@@ -918,14 +1020,26 @@ int main(int argc, char ** argv) {
             res.set_content(ss.str(), "text/vtt");
         } else if (params.response_format == vjson_format) {
             /* try to match openai/whisper's Python format */
-            std::string results = output_str(ctx, params, pcmf32s);
+            std::string results = output_str(ctx, params, pcmf32s); 
+            // Get language probabilities
+            std::vector<float> lang_probs(whisper_lang_max_id() + 1, 0.0f);
+            const auto detected_lang_id = whisper_lang_auto_detect(ctx, 0, params.n_threads, lang_probs.data());
             json jres = json{
                 {"task", params.translate ? "translate" : "transcribe"},
                 {"language", whisper_lang_str_full(whisper_full_lang_id(ctx))},
                 {"duration", float(pcmf32.size())/WHISPER_SAMPLE_RATE},
                 {"text", results},
-                {"segments", json::array()}
+                {"segments", json::array()},
+                {"detected_language", whisper_lang_str_full(detected_lang_id)},
+                {"detected_language_probability", lang_probs[detected_lang_id]},
+                {"language_probabilities", json::object()}
             };
+            // Add all language probabilities
+            for (int i = 0; i <= whisper_lang_max_id(); ++i) {
+                if (lang_probs[i] > 0.001f) { // Only include non-negligible probabilities
+                    jres["language_probabilities"][whisper_lang_str(i)] = lang_probs[i];
+                }
+            }
             const int n_segments = whisper_full_n_segments(ctx);
             for (int i = 0; i < n_segments; ++i)
             {
@@ -985,8 +1099,9 @@ int main(int argc, char ** argv) {
         // reset params to their defaults
         params = default_params;
     });
-    svr.Post(sparams.request_path + "/load", [&](const Request &req, Response &res){
+    svr->Post(sparams.request_path + "/load", [&](const Request &req, Response &res){
         std::lock_guard<std::mutex> lock(whisper_mutex);
+        state.store(SERVER_STATE_LOADING_MODEL);
         if (!req.has_file("model"))
         {
             fprintf(stderr, "error: no 'model' field in the request\n");
@@ -1018,18 +1133,25 @@ int main(int argc, char ** argv) {
         // initialize openvino encoder. this has no effect on whisper.cpp builds that don't have OpenVINO configured
         whisper_ctx_init_openvino_encoder(ctx, nullptr, params.openvino_encode_device.c_str(), nullptr);
 
+        state.store(SERVER_STATE_READY);
         const std::string success = "Load was successful!";
         res.set_content(success, "application/text");
 
         // check if the model is in the file system
     });
 
-    svr.Get(sparams.request_path + "/health", [&](const Request &, Response &res){
-        const std::string health_response = "{\"status\":\"ok\"}";
-        res.set_content(health_response, "application/json");
+    svr->Get(sparams.request_path + "/health", [&](const Request &, Response &res){
+        server_state current_state = state.load();
+        if (current_state == SERVER_STATE_READY) {
+            const std::string health_response = "{\"status\":\"ok\"}";
+            res.set_content(health_response, "application/json");
+        } else {
+            res.set_content("{\"status\":\"loading model\"}", "application/json");
+            res.status = 503;
+        }
     });
 
-    svr.set_exception_handler([](const Request &, Response &res, std::exception_ptr ep) {
+    svr->set_exception_handler([](const Request &, Response &res, std::exception_ptr ep) {
         const char fmt[] = "500 Internal Server Error\n%s";
         char buf[BUFSIZ];
         try {
@@ -1043,7 +1165,7 @@ int main(int argc, char ** argv) {
         res.status = 500;
     });
 
-    svr.set_error_handler([](const Request &req, Response &res) {
+    svr->set_error_handler([](const Request &req, Response &res) {
         if (res.status == 400) {
             res.set_content("Invalid request", "text/plain");
         } else if (res.status != 500) {
@@ -1053,10 +1175,10 @@ int main(int argc, char ** argv) {
     });
 
     // set timeouts and change hostname and port
-    svr.set_read_timeout(sparams.read_timeout);
-    svr.set_write_timeout(sparams.write_timeout);
+    svr->set_read_timeout(sparams.read_timeout);
+    svr->set_write_timeout(sparams.write_timeout);
 
-    if (!svr.bind_to_port(sparams.hostname, sparams.port))
+    if (!svr->bind_to_port(sparams.hostname, sparams.port))
     {
         fprintf(stderr, "\ncouldn't bind to server socket: hostname=%s port=%d\n\n",
                 sparams.hostname.c_str(), sparams.port);
@@ -1064,18 +1186,50 @@ int main(int argc, char ** argv) {
     }
 
     // Set the base directory for serving static files
-    svr.set_base_dir(sparams.public_path);
+    svr->set_base_dir(sparams.public_path);
 
     // to make it ctrl+clickable:
     printf("\nwhisper server listening at http://%s:%d\n\n", sparams.hostname.c_str(), sparams.port);
 
-    if (!svr.listen_after_bind())
-    {
-        return 1;
-    }
+    shutdown_handler = [&](int signal) {
+        printf("\nCaught signal %d, shutting down gracefully...\n", signal);
+        if (svr) {
+            svr->stop();
+        }
+    };
 
-    whisper_print_timings(ctx);
-    whisper_free(ctx);
+#if defined (__unix__) || (defined (__APPLE__) && defined (__MACH__))
+    struct sigaction sigint_action;
+    sigint_action.sa_handler = signal_handler;
+    sigemptyset (&sigint_action.sa_mask);
+    sigint_action.sa_flags = 0;
+    sigaction(SIGINT, &sigint_action, NULL);
+    sigaction(SIGTERM, &sigint_action, NULL);
+#elif defined (_WIN32)
+    auto console_ctrl_handler = +[](DWORD ctrl_type) -> BOOL {
+        return (ctrl_type == CTRL_C_EVENT) ? (signal_handler(SIGINT), true) : false;
+    };
+    SetConsoleCtrlHandler(reinterpret_cast<PHANDLER_ROUTINE>(console_ctrl_handler), true);
+#endif
+
+    // clean up function, to be called before exit
+    auto clean_up = [&]() {
+        whisper_print_timings(ctx);
+        whisper_free(ctx);
+    };
+
+    std::thread t([&] {
+        if (!svr->listen_after_bind()) {
+            fprintf(stderr, "error: server listen failed\n");
+        }
+    });
+
+    svr->wait_until_ready();
+
+    t.join();
+
+
+    clean_up();
 
     return 0;
 }

examples/stream.wasm/CMakeLists.txt

@@ -35,7 +35,7 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     -s INITIAL_MEMORY=1024MB \
     -s TOTAL_MEMORY=1024MB \
     -s FORCE_FILESYSTEM=1 \
-    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
+    -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap', 'HEAPU8']\" \
     ${EXTRA_FLAGS} \
     ")
 

examples/stream.wasm/README.md

@@ -26,5 +26,10 @@ to the server's HTTP path:
 ```
 # copy the produced page to your HTTP path
 cp bin/stream.wasm/*       /path/to/html/
+cp bin/libstream.js        /path/to/html/
 cp bin/libstream.worker.js /path/to/html/
 ```
+
+> 📝 **Note:** As of Emscripten 3.1.58 (April 2024), separate worker.js files are no
+> longer generated and the worker is embedded in the main JS file. So the worker
+> file will not be geneated for versions later than `3.1.58`.

examples/stream/stream.cpp

@@ -116,6 +116,8 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
 }
 
 int main(int argc, char ** argv) {
+    ggml_backend_load_all();
+
     whisper_params params;
 
     if (whisper_params_parse(argc, argv, params) == false) {
@@ -161,6 +163,10 @@ int main(int argc, char ** argv) {
     cparams.flash_attn = params.flash_attn;
 
     struct whisper_context * ctx = whisper_init_from_file_with_params(params.model.c_str(), cparams);
+    if (ctx == nullptr) {
+        fprintf(stderr, "error: failed to initialize whisper context\n");
+        return 2;
+    }
 
     std::vector<float> pcmf32    (n_samples_30s, 0.0f);
     std::vector<float> pcmf32_old;

examples/talk-llama/CMakeLists.txt

@@ -12,11 +12,18 @@ if (WHISPER_SDL2)
         llama-context.cpp
         llama-cparams.cpp
         llama-grammar.cpp
+        llama-graph.cpp
         llama-hparams.cpp
         llama-impl.cpp
-        llama-kv-cache.cpp
+        llama-io.cpp
+        llama-kv-cache-unified.cpp
+        llama-kv-cache-unified-iswa.cpp
+        llama-memory-recurrent.cpp
+        llama-memory-hybrid.cpp
+        llama-memory.cpp
         llama-mmap.cpp
         llama-model-loader.cpp
+        llama-model-saver.cpp
         llama-model.cpp
         llama-quant.cpp
         llama-sampling.cpp

examples/talk-llama/llama-adapter.cpp

@@ -4,14 +4,13 @@
 #include "llama-mmap.h"
 #include "llama-model.h"
 
-#include <algorithm>
 #include <map>
 #include <cassert>
 #include <stdexcept>
 
 // vec
 
-struct ggml_tensor * llama_adapter_cvec::tensor_for(int il) const {
+ggml_tensor * llama_adapter_cvec::tensor_for(int il) const {
     if (il < 0 || il < layer_start || il > layer_end || (size_t) il >= tensors.size()) {
         return nullptr;
     }
@@ -19,7 +18,7 @@ struct ggml_tensor * llama_adapter_cvec::tensor_for(int il) const {
     return tensors[il];
 }
 
-struct ggml_tensor * llama_adapter_cvec::apply_to(struct ggml_context * ctx, struct ggml_tensor * cur, int  il) const {
+ggml_tensor * llama_adapter_cvec::apply_to(ggml_context * ctx, ggml_tensor * cur, int  il) const {
     ggml_tensor * layer_dir = tensor_for(il);
     if (layer_dir != nullptr) {
         cur = ggml_add(ctx, cur, layer_dir);
@@ -40,7 +39,7 @@ bool llama_adapter_cvec::init(const llama_model & model) {
     auto ctx_for_buft = [&](ggml_backend_buffer_type_t buft) -> ggml_context * {
         auto it = ctx_map.find(buft);
         if (it == ctx_map.end()) {
-            struct ggml_init_params params = {
+            ggml_init_params params = {
                 /*.mem_size   =*/ hparams.n_layer*ggml_tensor_overhead(),
                 /*.mem_buffer =*/ NULL,
                 /*.no_alloc   =*/ true,
@@ -91,7 +90,7 @@ bool llama_adapter_cvec::init(const llama_model & model) {
     return true;
 }
 
-int32_t llama_adapter_cvec::apply(
+bool llama_adapter_cvec::apply(
         const llama_model & model,
         const float * data,
         size_t len,
@@ -104,17 +103,17 @@ int32_t llama_adapter_cvec::apply(
         // disable the current control vector (but leave allocated for later)
         layer_start = -1;
         layer_end   = -1;
-        return 0;
+        return true;
     }
 
     if (n_embd != (int) hparams.n_embd) {
         LLAMA_LOG_ERROR("%s: control vector n_embd does not match model\n", __func__);
-        return 1;
+        return false;
     }
 
     if (tensors.empty()) {
         if (!init(model)) {
-            return 1;
+            return false;
         }
     }
 
@@ -130,12 +129,12 @@ int32_t llama_adapter_cvec::apply(
         }
     }
 
-    return 0;
+    return true;
 }
 
 // lora
 
-llama_adapter_lora_weight * llama_adapter_lora::get_weight(struct ggml_tensor * w) {
+llama_adapter_lora_weight * llama_adapter_lora::get_weight(ggml_tensor * w) {
     const std::string name(w->name);
 
     const auto pos = ab_map.find(name);
@@ -146,11 +145,11 @@ llama_adapter_lora_weight * llama_adapter_lora::get_weight(struct ggml_tensor *
     return nullptr;
 }
 
-static void llama_adapter_lora_init_impl(struct llama_model & model, const char * path_lora, struct llama_adapter_lora & adapter) {
+static void llama_adapter_lora_init_impl(llama_model & model, const char * path_lora, llama_adapter_lora & adapter) {
     LLAMA_LOG_INFO("%s: loading lora adapter from '%s' ...\n", __func__, path_lora);
 
     ggml_context * ctx_init;
-    struct gguf_init_params meta_gguf_params = {
+    gguf_init_params meta_gguf_params = {
         /* .no_alloc = */ true,
         /* .ctx      = */ &ctx_init,
     };
@@ -201,7 +200,7 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
         auto it = ctx_map.find(buft);
         if (it == ctx_map.end()) {
             // add a new context
-            struct ggml_init_params params = {
+            ggml_init_params params = {
                 /*.mem_size   =*/ n_tensors*ggml_tensor_overhead(),
                 /*.mem_buffer =*/ NULL,
                 /*.no_alloc   =*/ true,
@@ -248,6 +247,29 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
         }
     }
 
+    // get extra buffer types of the CPU
+    // TODO: a more general solution for non-CPU extra buft should be imlpemented in the future
+    //       ref: https://github.com/ggml-org/llama.cpp/pull/12593#pullrequestreview-2718659948
+    std::vector<ggml_backend_buffer_type_t> buft_extra;
+    {
+        auto * cpu_dev = ggml_backend_dev_by_type(GGML_BACKEND_DEVICE_TYPE_CPU);
+        if (!cpu_dev) {
+            throw std::runtime_error(format("%s: no CPU backend found", __func__));
+        }
+        auto * cpu_reg = ggml_backend_dev_backend_reg(cpu_dev);
+
+        auto ggml_backend_dev_get_extra_bufts_fn = (ggml_backend_dev_get_extra_bufts_t)
+            ggml_backend_reg_get_proc_address(cpu_reg, "ggml_backend_dev_get_extra_bufts");
+
+        if (ggml_backend_dev_get_extra_bufts_fn) {
+            ggml_backend_buffer_type_t * extra_bufts = ggml_backend_dev_get_extra_bufts_fn(cpu_dev);
+            while (extra_bufts && *extra_bufts) {
+                buft_extra.emplace_back(*extra_bufts);
+                ++extra_bufts;
+            }
+        }
+    }
+
     // add tensors
     for (auto & it : ab_map) {
         const std::string & name = it.first;
@@ -264,7 +286,26 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
             throw std::runtime_error("LoRA tensor '" + name + "' does not exist in base model (hint: maybe wrong base model?)");
         }
 
-        struct ggml_context * dev_ctx = ctx_for_buft(ggml_backend_buffer_get_type(model_tensor->buffer));
+        auto * buft = ggml_backend_buffer_get_type(model_tensor->buffer);
+
+        // do not load loras to extra buffer types (i.e. bufts for repacking) -> use the CPU in that case
+        for (auto & ex : buft_extra) {
+            if (ex == buft) {
+                LLAMA_LOG_WARN("%s: lora for '%s' cannot use buft '%s', fallback to CPU\n", __func__, model_tensor->name, ggml_backend_buft_name(buft));
+
+                auto * cpu_dev = ggml_backend_dev_by_type(GGML_BACKEND_DEVICE_TYPE_CPU);
+                if (!cpu_dev) {
+                    throw std::runtime_error(format("%s: no CPU backend found", __func__));
+                }
+                buft = ggml_backend_dev_buffer_type(cpu_dev);
+
+                break;
+            }
+        }
+
+        LLAMA_LOG_DEBUG("%s: lora for '%s' -> '%s'\n", __func__, model_tensor->name, ggml_backend_buft_name(buft));
+
+        ggml_context * dev_ctx = ctx_for_buft(buft);
         // validate tensor shape
         if (is_token_embd) {
             // expect B to be non-transposed, A and B are flipped; see llm_build_inp_embd()
@@ -281,8 +322,8 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
         }
 
         // save tensor to adapter
-        struct ggml_tensor * tensor_a = ggml_dup_tensor(dev_ctx, w.a);
-        struct ggml_tensor * tensor_b = ggml_dup_tensor(dev_ctx, w.b);
+        ggml_tensor * tensor_a = ggml_dup_tensor(dev_ctx, w.a);
+        ggml_tensor * tensor_b = ggml_dup_tensor(dev_ctx, w.b);
         ggml_set_name(tensor_a, w.a->name);
         ggml_set_name(tensor_b, w.b->name);
         adapter.ab_map[name] = llama_adapter_lora_weight(tensor_a, tensor_b);
@@ -308,7 +349,7 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
     {
         llama_file gguf_file(path_lora, "rb");
         std::vector<uint8_t> read_buf;
-        auto set_tensor = [&](struct ggml_tensor * orig, struct ggml_tensor * dev) {
+        auto set_tensor = [&](ggml_tensor * orig, ggml_tensor * dev) {
             size_t offs = gguf_get_data_offset(ctx_gguf.get()) + gguf_get_tensor_offset(ctx_gguf.get(), gguf_find_tensor(ctx_gguf.get(), orig->name));
             size_t size = ggml_nbytes(orig);
             read_buf.resize(size);
@@ -327,8 +368,8 @@ static void llama_adapter_lora_init_impl(struct llama_model & model, const char
     LLAMA_LOG_INFO("%s: loaded %zu tensors from lora file\n", __func__, adapter.ab_map.size()*2);
 }
 
-struct llama_adapter_lora * llama_adapter_lora_init(struct llama_model * model, const char * path_lora) {
-    struct llama_adapter_lora * adapter = new llama_adapter_lora();
+llama_adapter_lora * llama_adapter_lora_init(llama_model * model, const char * path_lora) {
+    llama_adapter_lora * adapter = new llama_adapter_lora();
 
     try {
         llama_adapter_lora_init_impl(*model, path_lora, *adapter);
@@ -342,6 +383,6 @@ struct llama_adapter_lora * llama_adapter_lora_init(struct llama_model * model,
     return nullptr;
 }
 
-void llama_adapter_lora_free(struct llama_adapter_lora * adapter) {
+void llama_adapter_lora_free(llama_adapter_lora * adapter) {
     delete adapter;
 }

examples/talk-llama/llama-adapter.h

@@ -15,11 +15,11 @@
 //
 
 struct llama_adapter_cvec {
-    struct ggml_tensor * tensor_for(int il) const;
+    ggml_tensor * tensor_for(int il) const;
 
-    struct ggml_tensor * apply_to(struct ggml_context * ctx, struct ggml_tensor * cur, int  il) const;
+    ggml_tensor * apply_to(ggml_context * ctx, ggml_tensor * cur, int  il) const;
 
-    int32_t apply(
+    bool apply(
             const llama_model & model,
             const float * data,
             size_t len,
@@ -36,7 +36,7 @@ private:
     std::vector<ggml_context_ptr> ctxs;
     std::vector<ggml_backend_buffer_ptr> bufs;
 
-    std::vector<struct ggml_tensor *> tensors; // per layer
+    std::vector<ggml_tensor *> tensors; // per layer
 };
 
 //
@@ -44,8 +44,8 @@ private:
 //
 
 struct llama_adapter_lora_weight {
-    struct ggml_tensor * a = nullptr;
-    struct ggml_tensor * b = nullptr;
+    ggml_tensor * a = nullptr;
+    ggml_tensor * b = nullptr;
 
     // get actual scale based on rank and alpha
     float get_scale(float alpha, float adapter_scale) const {
@@ -55,12 +55,12 @@ struct llama_adapter_lora_weight {
     }
 
     llama_adapter_lora_weight() = default;
-    llama_adapter_lora_weight(struct ggml_tensor * a, struct ggml_tensor * b) : a(a), b(b) {}
+    llama_adapter_lora_weight(ggml_tensor * a, ggml_tensor * b) : a(a), b(b) {}
 };
 
 struct llama_adapter_lora {
     // map tensor name to lora_a_b
-    std::unordered_map<std::string, struct llama_adapter_lora_weight> ab_map;
+    std::unordered_map<std::string, llama_adapter_lora_weight> ab_map;
 
     std::vector<ggml_context_ptr> ctxs;
     std::vector<ggml_backend_buffer_ptr> bufs;
@@ -70,5 +70,7 @@ struct llama_adapter_lora {
     llama_adapter_lora() = default;
     ~llama_adapter_lora() = default;
 
-    llama_adapter_lora_weight * get_weight(struct ggml_tensor * w);
+    llama_adapter_lora_weight * get_weight(ggml_tensor * w);
 };
+
+using llama_adapter_loras = std::unordered_map<llama_adapter_lora *, float>;

examples/talk-llama/llama-arch.cpp

@@ -6,6 +6,7 @@
 
 static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_LLAMA,            "llama"            },
+    { LLM_ARCH_LLAMA4,           "llama4"           },
     { LLM_ARCH_DECI,             "deci"             },
     { LLM_ARCH_FALCON,           "falcon"           },
     { LLM_ARCH_GROK,             "grok"             },
@@ -18,6 +19,8 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_REFACT,           "refact"           },
     { LLM_ARCH_BERT,             "bert"             },
     { LLM_ARCH_NOMIC_BERT,       "nomic-bert"       },
+    { LLM_ARCH_NOMIC_BERT_MOE,   "nomic-bert-moe"   },
+    { LLM_ARCH_NEO_BERT,         "neo-bert"         },
     { LLM_ARCH_JINA_BERT_V2,     "jina-bert-v2"     },
     { LLM_ARCH_BLOOM,            "bloom"            },
     { LLM_ARCH_STABLELM,         "stablelm"         },
@@ -25,6 +28,8 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_QWEN2,            "qwen2"            },
     { LLM_ARCH_QWEN2MOE,         "qwen2moe"         },
     { LLM_ARCH_QWEN2VL,          "qwen2vl"          },
+    { LLM_ARCH_QWEN3,            "qwen3"            },
+    { LLM_ARCH_QWEN3MOE,         "qwen3moe"         },
     { LLM_ARCH_PHI2,             "phi2"             },
     { LLM_ARCH_PHI3,             "phi3"             },
     { LLM_ARCH_PHIMOE,           "phimoe"           },
@@ -36,6 +41,8 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_MINICPM3,         "minicpm3"         },
     { LLM_ARCH_GEMMA,            "gemma"            },
     { LLM_ARCH_GEMMA2,           "gemma2"           },
+    { LLM_ARCH_GEMMA3,           "gemma3"           },
+    { LLM_ARCH_GEMMA3N,          "gemma3n"          },
     { LLM_ARCH_STARCODER2,       "starcoder2"       },
     { LLM_ARCH_MAMBA,            "mamba"            },
     { LLM_ARCH_XVERSE,           "xverse"           },
@@ -50,6 +57,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_DEEPSEEK,         "deepseek"         },
     { LLM_ARCH_DEEPSEEK2,        "deepseek2"        },
     { LLM_ARCH_CHATGLM,          "chatglm"          },
+    { LLM_ARCH_GLM4,             "glm4"             },
     { LLM_ARCH_BITNET,           "bitnet"           },
     { LLM_ARCH_T5,               "t5"               },
     { LLM_ARCH_T5ENCODER,        "t5encoder"        },
@@ -58,10 +66,17 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_EXAONE,           "exaone"           },
     { LLM_ARCH_RWKV6,            "rwkv6"            },
     { LLM_ARCH_RWKV6QWEN2,       "rwkv6qwen2"       },
+    { LLM_ARCH_RWKV7,            "rwkv7"            },
+    { LLM_ARCH_ARWKV7,           "arwkv7"           },
     { LLM_ARCH_GRANITE,          "granite"          },
     { LLM_ARCH_GRANITE_MOE,      "granitemoe"       },
     { LLM_ARCH_CHAMELEON,        "chameleon"        },
     { LLM_ARCH_WAVTOKENIZER_DEC, "wavtokenizer-dec" },
+    { LLM_ARCH_PLM,              "plm"              },
+    { LLM_ARCH_BAILINGMOE,       "bailingmoe"       },
+    { LLM_ARCH_DOTS1,            "dots1"            },
+    { LLM_ARCH_ARCEE,            "arcee"            },
+    { LLM_ARCH_ERNIE4_5,         "ernie4_5"         },
     { LLM_ARCH_UNKNOWN,          "(unknown)"        },
 };
 
@@ -70,6 +85,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_GENERAL_ARCHITECTURE,         "general.architecture"                  },
     { LLM_KV_GENERAL_QUANTIZATION_VERSION, "general.quantization_version"          },
     { LLM_KV_GENERAL_ALIGNMENT,            "general.alignment"                     },
+    { LLM_KV_GENERAL_FILE_TYPE,            "general.file_type"                     },
     { LLM_KV_GENERAL_NAME,                 "general.name"                          },
     { LLM_KV_GENERAL_AUTHOR,               "general.author"                        },
     { LLM_KV_GENERAL_VERSION,              "general.version"                       },
@@ -96,6 +112,7 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_EXPERT_WEIGHTS_SCALE,              "%s.expert_weights_scale"              },
     { LLM_KV_EXPERT_WEIGHTS_NORM,               "%s.expert_weights_norm"               },
     { LLM_KV_EXPERT_GATING_FUNC,                "%s.expert_gating_func"                },
+    { LLM_KV_MOE_EVERY_N_LAYERS,                "%s.moe_every_n_layers"                },
     { LLM_KV_POOLING_TYPE,                      "%s.pooling_type"                      },
     { LLM_KV_LOGIT_SCALE,                       "%s.logit_scale"                       },
     { LLM_KV_DECODER_START_TOKEN_ID,            "%s.decoder_start_token_id"            },
@@ -108,23 +125,31 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_RESIDUAL_SCALE,                    "%s.residual_scale"                    },
     { LLM_KV_EMBEDDING_SCALE,                   "%s.embedding_scale"                   },
     { LLM_KV_TOKEN_SHIFT_COUNT,                 "%s.token_shift_count"                 },
+    { LLM_KV_INTERLEAVE_MOE_LAYER_STEP,         "%s.interleave_moe_layer_step"         },
 
-    { LLM_KV_ATTENTION_HEAD_COUNT,             "%s.attention.head_count"             },
-    { LLM_KV_ATTENTION_HEAD_COUNT_KV,          "%s.attention.head_count_kv"          },
-    { LLM_KV_ATTENTION_MAX_ALIBI_BIAS,         "%s.attention.max_alibi_bias"         },
-    { LLM_KV_ATTENTION_CLAMP_KQV,              "%s.attention.clamp_kqv"              },
-    { LLM_KV_ATTENTION_KEY_LENGTH,             "%s.attention.key_length"             },
-    { LLM_KV_ATTENTION_VALUE_LENGTH,           "%s.attention.value_length"           },
-    { LLM_KV_ATTENTION_LAYERNORM_EPS,          "%s.attention.layer_norm_epsilon"     },
-    { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,      "%s.attention.layer_norm_rms_epsilon" },
-    { LLM_KV_ATTENTION_GROUPNORM_EPS,          "%s.attention.group_norm_epsilon"     },
-    { LLM_KV_ATTENTION_GROUPNORM_GROUPS,       "%s.attention.group_norm_groups"      },
-    { LLM_KV_ATTENTION_CAUSAL,                 "%s.attention.causal"                 },
-    { LLM_KV_ATTENTION_Q_LORA_RANK,            "%s.attention.q_lora_rank"            },
-    { LLM_KV_ATTENTION_KV_LORA_RANK,           "%s.attention.kv_lora_rank"           },
-    { LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT, "%s.attention.relative_buckets_count" },
-    { LLM_KV_ATTENTION_SLIDING_WINDOW,         "%s.attention.sliding_window"         },
-    { LLM_KV_ATTENTION_SCALE,                  "%s.attention.scale"                  },
+    { LLM_KV_ATTENTION_HEAD_COUNT,                   "%s.attention.head_count"                   },
+    { LLM_KV_ATTENTION_HEAD_COUNT_KV,                "%s.attention.head_count_kv"                },
+    { LLM_KV_ATTENTION_MAX_ALIBI_BIAS,               "%s.attention.max_alibi_bias"               },
+    { LLM_KV_ATTENTION_CLAMP_KQV,                    "%s.attention.clamp_kqv"                    },
+    { LLM_KV_ATTENTION_KEY_LENGTH,                   "%s.attention.key_length"                   },
+    { LLM_KV_ATTENTION_VALUE_LENGTH,                 "%s.attention.value_length"                 },
+    { LLM_KV_ATTENTION_LAYERNORM_EPS,                "%s.attention.layer_norm_epsilon"           },
+    { LLM_KV_ATTENTION_LAYERNORM_RMS_EPS,            "%s.attention.layer_norm_rms_epsilon"       },
+    { LLM_KV_ATTENTION_GROUPNORM_EPS,                "%s.attention.group_norm_epsilon"           },
+    { LLM_KV_ATTENTION_GROUPNORM_GROUPS,             "%s.attention.group_norm_groups"            },
+    { LLM_KV_ATTENTION_CAUSAL,                       "%s.attention.causal"                       },
+    { LLM_KV_ATTENTION_Q_LORA_RANK,                  "%s.attention.q_lora_rank"                  },
+    { LLM_KV_ATTENTION_KV_LORA_RANK,                 "%s.attention.kv_lora_rank"                 },
+    { LLM_KV_ATTENTION_DECAY_LORA_RANK,              "%s.attention.decay_lora_rank"              },
+    { LLM_KV_ATTENTION_ICLR_LORA_RANK,               "%s.attention.iclr_lora_rank"               },
+    { LLM_KV_ATTENTION_VALUE_RESIDUAL_MIX_LORA_RANK, "%s.attention.value_residual_mix_lora_rank" },
+    { LLM_KV_ATTENTION_GATE_LORA_RANK,               "%s.attention.gate_lora_rank"               },
+    { LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT,       "%s.attention.relative_buckets_count"       },
+    { LLM_KV_ATTENTION_SLIDING_WINDOW,               "%s.attention.sliding_window"               },
+    { LLM_KV_ATTENTION_SCALE,                        "%s.attention.scale"                        },
+    { LLM_KV_ATTENTION_KEY_LENGTH_MLA,               "%s.attention.key_length_mla"               },
+    { LLM_KV_ATTENTION_VALUE_LENGTH_MLA,             "%s.attention.value_length_mla"             },
+    { LLM_KV_ATTENTION_LAYER_INDICES,                "%s.attention.layer_indices"                },
 
     { LLM_KV_ROPE_DIMENSION_COUNT,      "%s.rope.dimension_count"                 },
     { LLM_KV_ROPE_DIMENSION_SECTIONS,   "%s.rope.dimension_sections"              },
@@ -155,6 +180,8 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_CONVNEXT_EMBEDDING_LENGTH, "%s.convnext.embedding_length" },
     { LLM_KV_CONVNEXT_BLOCK_COUNT,      "%s.convnext.block_count"      },
 
+    { LLM_KV_CLASSIFIER_OUTPUT_LABELS, "%s.classifier.output_labels" },
+
     { LLM_KV_TOKENIZER_MODEL,                "tokenizer.ggml.model"                    },
     { LLM_KV_TOKENIZER_PRE,                  "tokenizer.ggml.pre"                      },
     { LLM_KV_TOKENIZER_LIST,                 "tokenizer.ggml.tokens"                   },
@@ -173,13 +200,13 @@ static const std::map<llm_kv, const char *> LLM_KV_NAMES = {
     { LLM_KV_TOKENIZER_MASK_ID,              "tokenizer.ggml.mask_token_id"            },
     { LLM_KV_TOKENIZER_ADD_BOS,              "tokenizer.ggml.add_bos_token"            },
     { LLM_KV_TOKENIZER_ADD_EOS,              "tokenizer.ggml.add_eos_token"            },
+    { LLM_KV_TOKENIZER_ADD_SEP,              "tokenizer.ggml.add_sep_token"            },
     { LLM_KV_TOKENIZER_ADD_PREFIX,           "tokenizer.ggml.add_space_prefix"         },
     { LLM_KV_TOKENIZER_REMOVE_EXTRA_WS,      "tokenizer.ggml.remove_extra_whitespaces" },
     { LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP, "tokenizer.ggml.precompiled_charsmap"     },
     { LLM_KV_TOKENIZER_HF_JSON,              "tokenizer.huggingface.json"              },
     { LLM_KV_TOKENIZER_RWKV,                 "tokenizer.rwkv.world"                    },
     { LLM_KV_TOKENIZER_CHAT_TEMPLATE,        "tokenizer.chat_template"                 },
-    { LLM_KV_TOKENIZER_CHAT_TEMPLATE_N,      "tokenizer.chat_template.%s"              },
     { LLM_KV_TOKENIZER_FIM_PRE_ID,           "tokenizer.ggml.fim_pre_token_id"         },
     { LLM_KV_TOKENIZER_FIM_SUF_ID,           "tokenizer.ggml.fim_suf_token_id"         },
     { LLM_KV_TOKENIZER_FIM_MID_ID,           "tokenizer.ggml.fim_mid_token_id"         },
@@ -223,6 +250,53 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_UP_EXPS,     "blk.%d.ffn_up_exps" },
         },
     },
+    {
+        LLM_ARCH_ARCEE,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ROPE_FREQS,      "rope_freqs" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_ROT_EMBD,   "blk.%d.attn_rot_embd" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+        },
+    },
+    {
+        LLM_ARCH_LLAMA4,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ROPE_FREQS,      "rope_freqs" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_ROT_EMBD,   "blk.%d.attn_rot_embd" },
+            { LLM_TENSOR_FFN_GATE_INP,    "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_GATE_EXP,    "blk.%d.ffn_gate.%d" },
+            { LLM_TENSOR_FFN_DOWN_EXP,    "blk.%d.ffn_down.%d" },
+            { LLM_TENSOR_FFN_UP_EXP,      "blk.%d.ffn_up.%d" },
+            { LLM_TENSOR_FFN_GATE_EXPS,   "blk.%d.ffn_gate_exps" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,   "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,     "blk.%d.ffn_up_exps" },
+            { LLM_TENSOR_FFN_GATE_SHEXP,  "blk.%d.ffn_gate_shexp" },
+            { LLM_TENSOR_FFN_DOWN_SHEXP,  "blk.%d.ffn_down_shexp" },
+            { LLM_TENSOR_FFN_UP_SHEXP,    "blk.%d.ffn_up_shexp" },
+        },
+    },
     {
         LLM_ARCH_DECI,
         {
@@ -400,6 +474,7 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_TOKEN_TYPES,     "token_types" },
             { LLM_TENSOR_POS_EMBD,        "position_embd" },
             { LLM_TENSOR_ATTN_OUT_NORM,   "blk.%d.attn_output_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
             { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
             { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
             { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
@@ -426,6 +501,39 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_NOMIC_BERT_MOE,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_TOKEN_EMBD_NORM, "token_embd_norm" },
+            { LLM_TENSOR_TOKEN_TYPES,     "token_types" },
+            { LLM_TENSOR_ATTN_OUT_NORM,   "blk.%d.attn_output_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_LAYER_OUT_NORM,  "blk.%d.layer_output_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_GATE_INP,    "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,   "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,     "blk.%d.ffn_up_exps" },
+        },
+    },
+    {
+        LLM_ARCH_NEO_BERT,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_QKV,        "blk.%d.attn_qkv" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_ENC_OUTPUT_NORM, "enc.output_norm" },
+            { LLM_TENSOR_CLS,             "cls" },
+            { LLM_TENSOR_CLS_OUT,         "cls.output" },
+        },
+    },
     {
         LLM_ARCH_JINA_BERT_V2,
         {
@@ -554,6 +662,45 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_UP_SHEXP,       "blk.%d.ffn_up_shexp" },
         },
     },
+    {
+        LLM_ARCH_QWEN3,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_Q_NORM,     "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_K_NORM,     "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+        },
+    },
+    {
+        LLM_ARCH_QWEN3MOE,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_OUTPUT,             "output" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_Q_NORM,        "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K,             "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_K_NORM,        "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_V,             "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE_INP,       "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_GATE_EXPS,      "blk.%d.ffn_gate_exps" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,      "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,        "blk.%d.ffn_up_exps" },
+        },
+    },
     {
         LLM_ARCH_PHI2,
         {
@@ -766,6 +913,63 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
         },
     },
+    {
+        LLM_ARCH_GEMMA3,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_Q_NORM,     "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_K_NORM,     "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+        },
+    },
+    {
+        LLM_ARCH_GEMMA3N,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,           "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,          "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,            "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,               "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_Q_NORM,          "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K,               "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_K_NORM,          "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_V,               "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,             "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_POST_NORM,       "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_NORM,             "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,             "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,             "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,               "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_POST_NORM,        "blk.%d.post_ffw_norm" },
+            { LLM_TENSOR_PER_LAYER_TOKEN_EMBD, "per_layer_token_embd" },
+            { LLM_TENSOR_PER_LAYER_MODEL_PROJ, "per_layer_model_proj" },
+            { LLM_TENSOR_PER_LAYER_PROJ_NORM,  "per_layer_proj_norm" },
+            { LLM_TENSOR_ALTUP_UNEMBD_PROJ,    "altup_unembd_proj" },
+            { LLM_TENSOR_ALTUP_PROJ,           "altup_proj" },
+            { LLM_TENSOR_PER_LAYER_INP_GATE,   "blk.%d.inp_gate" },
+            { LLM_TENSOR_PER_LAYER_PROJ,       "blk.%d.proj" },
+            { LLM_TENSOR_PER_LAYER_POST_NORM,  "blk.%d.post_norm" },
+            { LLM_TENSOR_ALTUP_CORRECT_COEF,   "blk.%d.altup_correct_coef" },
+            { LLM_TENSOR_ALTUP_CORRECT_SCALE,  "blk.%d.altup_correct_scale" },
+            { LLM_TENSOR_ALTUP_PREDICT_COEF,   "blk.%d.altup_predict_coef" },
+            { LLM_TENSOR_ALTUP_ROUTER,         "blk.%d.altup_router" },
+            { LLM_TENSOR_ALTUP_ROUTER_NORM,    "blk.%d.altup_router_norm" },
+            { LLM_TENSOR_LAUREL_L,             "blk.%d.laurel_l" },
+            { LLM_TENSOR_LAUREL_R,             "blk.%d.laurel_r" },
+            { LLM_TENSOR_LAUREL_POST_NORM,     "blk.%d.laurel_post_norm" },
+        },
+    },
     {
         LLM_ARCH_STARCODER2,
         {
@@ -999,6 +1203,8 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_ATTN_Q_B,           "blk.%d.attn_q_b" },
             { LLM_TENSOR_ATTN_KV_A_MQA,      "blk.%d.attn_kv_a_mqa" },
             { LLM_TENSOR_ATTN_KV_B,          "blk.%d.attn_kv_b" },
+            { LLM_TENSOR_ATTN_K_B,           "blk.%d.attn_k_b" },
+            { LLM_TENSOR_ATTN_V_B,           "blk.%d.attn_v_b" },
             { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
             { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
             { LLM_TENSOR_FFN_GATE,           "blk.%d.ffn_gate" },
@@ -1015,6 +1221,22 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_EXP_PROBS_B,    "blk.%d.exp_probs_b" },
         },
     },
+    {
+        LLM_ARCH_PLM,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_KV_A_MQA,      "blk.%d.attn_kv_a_mqa" },
+            { LLM_TENSOR_ATTN_KV_A_NORM,     "blk.%d.attn_kv_a_norm" },
+            { LLM_TENSOR_ATTN_KV_B,          "blk.%d.attn_kv_b" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_DOWN,           "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,             "blk.%d.ffn_up" },
+        },
+    },
     {
         LLM_ARCH_CHATGLM,
         {
@@ -1033,6 +1255,25 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
         },
     },
+    {
+        LLM_ARCH_GLM4,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_ROPE_FREQS,      "rope_freqs" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_OUTPUT,          "output" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+        },
+    },
     {
         LLM_ARCH_BITNET,
         {
@@ -1217,6 +1458,74 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_UP,                    "blk.%d.ffn_up" },
         },
     },
+    {
+        LLM_ARCH_RWKV7,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,                "token_embd" },
+            { LLM_TENSOR_TOKEN_EMBD_NORM,           "token_embd_norm" },
+            { LLM_TENSOR_OUTPUT_NORM,               "output_norm" },
+            { LLM_TENSOR_OUTPUT,                    "output" },
+            { LLM_TENSOR_ATTN_NORM,                 "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_NORM_2,               "blk.%d.attn_norm_2" },
+            { LLM_TENSOR_TIME_MIX_W0,               "blk.%d.time_mix_w0" },
+            { LLM_TENSOR_TIME_MIX_W1,               "blk.%d.time_mix_w1" },
+            { LLM_TENSOR_TIME_MIX_W2,               "blk.%d.time_mix_w2" },
+            { LLM_TENSOR_TIME_MIX_A0,               "blk.%d.time_mix_a0" },
+            { LLM_TENSOR_TIME_MIX_A1,               "blk.%d.time_mix_a1" },
+            { LLM_TENSOR_TIME_MIX_A2,               "blk.%d.time_mix_a2" },
+            { LLM_TENSOR_TIME_MIX_V0,               "blk.%d.time_mix_v0" },
+            { LLM_TENSOR_TIME_MIX_V1,               "blk.%d.time_mix_v1" },
+            { LLM_TENSOR_TIME_MIX_V2,               "blk.%d.time_mix_v2" },
+            { LLM_TENSOR_TIME_MIX_G1,               "blk.%d.time_mix_g1" },
+            { LLM_TENSOR_TIME_MIX_G2,               "blk.%d.time_mix_g2" },
+            { LLM_TENSOR_TIME_MIX_K_K,              "blk.%d.time_mix_k_k" },
+            { LLM_TENSOR_TIME_MIX_K_A,              "blk.%d.time_mix_k_a" },
+            { LLM_TENSOR_TIME_MIX_R_K,              "blk.%d.time_mix_r_k" },
+            { LLM_TENSOR_TIME_MIX_LERP_FUSED,       "blk.%d.time_mix_lerp_fused" },
+            { LLM_TENSOR_TIME_MIX_KEY,              "blk.%d.time_mix_key" },
+            { LLM_TENSOR_TIME_MIX_VALUE,            "blk.%d.time_mix_value" },
+            { LLM_TENSOR_TIME_MIX_RECEPTANCE,       "blk.%d.time_mix_receptance" },
+            { LLM_TENSOR_TIME_MIX_LN,               "blk.%d.time_mix_ln" },
+            { LLM_TENSOR_TIME_MIX_OUTPUT,           "blk.%d.time_mix_output" },
+            { LLM_TENSOR_CHANNEL_MIX_LERP_K,        "blk.%d.channel_mix_lerp_k" },
+            { LLM_TENSOR_CHANNEL_MIX_KEY,           "blk.%d.channel_mix_key" },
+            { LLM_TENSOR_CHANNEL_MIX_VALUE,         "blk.%d.channel_mix_value" },
+        },
+    },
+    {
+        LLM_ARCH_ARWKV7,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,                "token_embd" },
+            { LLM_TENSOR_TOKEN_EMBD_NORM,           "token_embd_norm" },
+            { LLM_TENSOR_OUTPUT_NORM,               "output_norm" },
+            { LLM_TENSOR_OUTPUT,                    "output" },
+            { LLM_TENSOR_ATTN_NORM,                 "blk.%d.attn_norm" },
+            { LLM_TENSOR_TIME_MIX_W0,               "blk.%d.time_mix_w0" },
+            { LLM_TENSOR_TIME_MIX_W1,               "blk.%d.time_mix_w1" },
+            { LLM_TENSOR_TIME_MIX_W2,               "blk.%d.time_mix_w2" },
+            { LLM_TENSOR_TIME_MIX_A0,               "blk.%d.time_mix_a0" },
+            { LLM_TENSOR_TIME_MIX_A1,               "blk.%d.time_mix_a1" },
+            { LLM_TENSOR_TIME_MIX_A2,               "blk.%d.time_mix_a2" },
+            { LLM_TENSOR_TIME_MIX_V0,               "blk.%d.time_mix_v0" },
+            { LLM_TENSOR_TIME_MIX_V1,               "blk.%d.time_mix_v1" },
+            { LLM_TENSOR_TIME_MIX_V2,               "blk.%d.time_mix_v2" },
+            { LLM_TENSOR_TIME_MIX_G1,               "blk.%d.time_mix_g1" },
+            { LLM_TENSOR_TIME_MIX_G2,               "blk.%d.time_mix_g2" },
+            { LLM_TENSOR_TIME_MIX_K_K,              "blk.%d.time_mix_k_k" },
+            { LLM_TENSOR_TIME_MIX_K_A,              "blk.%d.time_mix_k_a" },
+            { LLM_TENSOR_TIME_MIX_R_K,              "blk.%d.time_mix_r_k" },
+            { LLM_TENSOR_TIME_MIX_LERP_FUSED,       "blk.%d.time_mix_lerp_fused" },
+            { LLM_TENSOR_TIME_MIX_KEY,              "blk.%d.time_mix_key" },
+            { LLM_TENSOR_TIME_MIX_VALUE,            "blk.%d.time_mix_value" },
+            { LLM_TENSOR_TIME_MIX_RECEPTANCE,       "blk.%d.time_mix_receptance" },
+            { LLM_TENSOR_TIME_MIX_LN,               "blk.%d.time_mix_ln" },
+            { LLM_TENSOR_TIME_MIX_OUTPUT,           "blk.%d.time_mix_output" },
+            { LLM_TENSOR_FFN_NORM,                  "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,                  "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,                  "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,                    "blk.%d.ffn_up" },
+        },
+    },
     {
         LLM_ARCH_GRANITE,
         {
@@ -1250,6 +1559,9 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_GATE_EXPS,   "blk.%d.ffn_gate_exps" },
             { LLM_TENSOR_FFN_DOWN_EXPS,   "blk.%d.ffn_down_exps" },
             { LLM_TENSOR_FFN_UP_EXPS,     "blk.%d.ffn_up_exps" },
+            { LLM_TENSOR_FFN_GATE_SHEXP,  "blk.%d.ffn_gate_shexp" },
+            { LLM_TENSOR_FFN_DOWN_SHEXP,  "blk.%d.ffn_down_shexp" },
+            { LLM_TENSOR_FFN_UP_SHEXP,    "blk.%d.ffn_up_shexp" },
         },
     },
     {
@@ -1296,6 +1608,74 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_POS_NET_ATTN_OUT,  "posnet.%d.attn_output" },
         },
     },
+    {
+        LLM_ARCH_BAILINGMOE,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_OUTPUT,             "output" },
+            { LLM_TENSOR_ROPE_FREQS,         "rope_freqs" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,             "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,             "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_GATE_INP,       "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE_EXPS,      "blk.%d.ffn_gate_exps" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,      "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,        "blk.%d.ffn_up_exps" },
+            { LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" },
+            { LLM_TENSOR_FFN_GATE_SHEXP,     "blk.%d.ffn_gate_shexp" },
+            { LLM_TENSOR_FFN_DOWN_SHEXP,     "blk.%d.ffn_down_shexp" },
+            { LLM_TENSOR_FFN_UP_SHEXP,       "blk.%d.ffn_up_shexp" },
+        },
+    },
+    {
+        LLM_ARCH_DOTS1,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_OUTPUT,             "output" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_Q_NORM,        "blk.%d.attn_q_norm" },
+            { LLM_TENSOR_ATTN_K,             "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_K_NORM,        "blk.%d.attn_k_norm" },
+            { LLM_TENSOR_ATTN_V,             "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,           "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_UP,             "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_DOWN,           "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_GATE_INP,       "blk.%d.ffn_gate_inp" },
+            { LLM_TENSOR_FFN_GATE_EXPS,      "blk.%d.ffn_gate_exps" },
+            { LLM_TENSOR_FFN_DOWN_EXPS,      "blk.%d.ffn_down_exps" },
+            { LLM_TENSOR_FFN_UP_EXPS,        "blk.%d.ffn_up_exps" },
+            { LLM_TENSOR_FFN_GATE_INP_SHEXP, "blk.%d.ffn_gate_inp_shexp" },
+            { LLM_TENSOR_FFN_GATE_SHEXP,     "blk.%d.ffn_gate_shexp" },
+            { LLM_TENSOR_FFN_DOWN_SHEXP,     "blk.%d.ffn_down_shexp" },
+            { LLM_TENSOR_FFN_UP_SHEXP,       "blk.%d.ffn_up_shexp" },
+            { LLM_TENSOR_FFN_EXP_PROBS_B,    "blk.%d.exp_probs_b" },
+        }
+    },
+    {
+        LLM_ARCH_ERNIE4_5,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,         "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,        "output_norm" },
+            { LLM_TENSOR_OUTPUT,             "output" },
+            { LLM_TENSOR_ATTN_NORM,          "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,             "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,             "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,             "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,           "blk.%d.attn_output" },
+            { LLM_TENSOR_FFN_NORM,           "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,           "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,           "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,             "blk.%d.ffn_up" },
+        },
+    },
     {
         LLM_ARCH_UNKNOWN,
         {
@@ -1333,23 +1713,8 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
     {LLM_TENSOR_ATTN_Q_B,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_ATTN_KV_A_MQA,              {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_ATTN_KV_B,                  {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_DEC_ATTN_Q,                 {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_DEC_ATTN_K,                 {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_Q,                     {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_K,                     {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_V,                     {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_QKV,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_OUT,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_GATE,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_DOWN,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_UP,                     {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_DOWN_SHEXP,             {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_GATE_SHEXP,             {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_FFN_UP_SHEXP,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_Q_A,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_Q_B,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_KV_A_MQA,              {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
-    {LLM_TENSOR_ATTN_KV_B,                  {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ATTN_K_B,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ATTN_V_B,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_DEC_ATTN_Q,                 {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_DEC_ATTN_K,                 {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_DEC_ATTN_V,                 {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
@@ -1376,6 +1741,12 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
     {LLM_TENSOR_SSM_OUT,                    {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_TIME_MIX_W1,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_TIME_MIX_W2,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_A1,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_A2,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_V1,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_V2,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_G1,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_TIME_MIX_G2,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_TIME_MIX_DECAY_W1,          {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_TIME_MIX_DECAY_W2,          {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
     {LLM_TENSOR_TIME_MIX_KEY,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
@@ -1394,6 +1765,9 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
     {LLM_TENSOR_TIME_MIX_LN,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
     {LLM_TENSOR_CHANNEL_MIX_LERP_K,         {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
     {LLM_TENSOR_CHANNEL_MIX_LERP_R,         {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_TIME_MIX_K_K,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_TIME_MIX_K_A,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_TIME_MIX_R_K,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
     {LLM_TENSOR_TIME_MIX_LERP_W,            {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
     {LLM_TENSOR_TIME_MIX_LERP_K,            {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
     {LLM_TENSOR_TIME_MIX_LERP_V,            {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
@@ -1401,6 +1775,9 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
     {LLM_TENSOR_TIME_MIX_LERP_G,            {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
     {LLM_TENSOR_TIME_MIX_LERP_FUSED,        {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
     {LLM_TENSOR_TIME_MIX_DECAY,             {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
+    {LLM_TENSOR_TIME_MIX_W0,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
+    {LLM_TENSOR_TIME_MIX_A0,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
+    {LLM_TENSOR_TIME_MIX_V0,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
     {LLM_TENSOR_TIME_MIX_FIRST,             {LLM_TENSOR_LAYER_REPEATING, GGML_OP_RWKV_WKV6}},
     {LLM_TENSOR_ATTN_NORM,                  {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
     {LLM_TENSOR_ATTN_NORM_2,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
@@ -1427,6 +1804,23 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
     {LLM_TENSOR_FFN_GATE_EXPS,              {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}},
     {LLM_TENSOR_FFN_UP_EXPS,                {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT_ID}},
     {LLM_TENSOR_FFN_EXP_PROBS_B,            {LLM_TENSOR_LAYER_REPEATING, GGML_OP_ADD}},
+    // altup / laurel (gemma 3n)
+    {LLM_TENSOR_PER_LAYER_TOKEN_EMBD,       {LLM_TENSOR_LAYER_OUTPUT,    GGML_OP_GET_ROWS}},
+    {LLM_TENSOR_PER_LAYER_MODEL_PROJ,       {LLM_TENSOR_LAYER_OUTPUT,    GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_PER_LAYER_PROJ_NORM,        {LLM_TENSOR_LAYER_OUTPUT,    GGML_OP_MUL}},
+    {LLM_TENSOR_ALTUP_PROJ,                 {LLM_TENSOR_LAYER_OUTPUT,    GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ALTUP_UNEMBD_PROJ,          {LLM_TENSOR_LAYER_OUTPUT,    GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_PER_LAYER_INP_GATE,         {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_PER_LAYER_PROJ,             {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_PER_LAYER_POST_NORM,        {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_ALTUP_CORRECT_COEF,         {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ALTUP_CORRECT_SCALE,        {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_ALTUP_PREDICT_COEF,         {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ALTUP_ROUTER,               {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_ALTUP_ROUTER_NORM,          {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
+    {LLM_TENSOR_LAUREL_L,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_LAUREL_R,                   {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL_MAT}},
+    {LLM_TENSOR_LAUREL_POST_NORM,           {LLM_TENSOR_LAYER_REPEATING, GGML_OP_MUL}},
     // this tensor is loaded for T5, but never used
     {LLM_TENSOR_DEC_CROSS_ATTN_REL_B,       {LLM_TENSOR_LAYER_REPEATING, GGML_OP_NONE}},
     {LLM_TENSOR_CONV1D,                     {LLM_TENSOR_LAYER_INPUT,     GGML_OP_IM2COL}},
@@ -1450,8 +1844,14 @@ static const std::map<llm_tensor, llm_tensor_info> LLM_TENSOR_INFOS = {
 LLM_KV::LLM_KV(llm_arch arch, const char * suffix) : arch(arch), suffix(suffix) {}
 
 std::string LLM_KV::operator()(llm_kv kv) const {
-    return suffix ? ::format(LLM_KV_NAMES.at(kv), LLM_ARCH_NAMES.at(arch), suffix)
-        : ::format(LLM_KV_NAMES.at(kv), LLM_ARCH_NAMES.at(arch));
+    std::string name = ::format(LLM_KV_NAMES.at(kv), LLM_ARCH_NAMES.at(arch));
+
+    if (suffix != nullptr) {
+        name += ".";
+        name += suffix;
+    }
+
+    return name;
 }
 
 std::string LLM_TN_IMPL::str() const {
@@ -1490,3 +1890,25 @@ llm_arch llm_arch_from_string(const std::string & name) {
 const llm_tensor_info & llm_tensor_info_for(llm_tensor tensor) {
     return LLM_TENSOR_INFOS.at(tensor);
 }
+
+bool llm_arch_is_recurrent(const llm_arch & arch) {
+    switch (arch) {
+        case LLM_ARCH_MAMBA:
+        case LLM_ARCH_RWKV6:
+        case LLM_ARCH_RWKV6QWEN2:
+        case LLM_ARCH_RWKV7:
+        case LLM_ARCH_ARWKV7:
+            return true;
+        default:
+            return false;
+    }
+}
+
+bool llm_arch_is_hybrid(const llm_arch & arch) {
+    // TODO: There are currently no hybrid models! Once there are, this will be
+    //  the place to identify them
+    switch (arch) {
+        default:
+            return false;
+    }
+}

examples/talk-llama/llama-arch.h

@@ -10,6 +10,7 @@
 
 enum llm_arch {
     LLM_ARCH_LLAMA,
+    LLM_ARCH_LLAMA4,
     LLM_ARCH_DECI,
     LLM_ARCH_FALCON,
     LLM_ARCH_BAICHUAN,
@@ -22,6 +23,8 @@ enum llm_arch {
     LLM_ARCH_REFACT,
     LLM_ARCH_BERT,
     LLM_ARCH_NOMIC_BERT,
+    LLM_ARCH_NOMIC_BERT_MOE,
+    LLM_ARCH_NEO_BERT,
     LLM_ARCH_JINA_BERT_V2,
     LLM_ARCH_BLOOM,
     LLM_ARCH_STABLELM,
@@ -29,6 +32,8 @@ enum llm_arch {
     LLM_ARCH_QWEN2,
     LLM_ARCH_QWEN2MOE,
     LLM_ARCH_QWEN2VL,
+    LLM_ARCH_QWEN3,
+    LLM_ARCH_QWEN3MOE,
     LLM_ARCH_PHI2,
     LLM_ARCH_PHI3,
     LLM_ARCH_PHIMOE,
@@ -40,6 +45,8 @@ enum llm_arch {
     LLM_ARCH_MINICPM3,
     LLM_ARCH_GEMMA,
     LLM_ARCH_GEMMA2,
+    LLM_ARCH_GEMMA3,
+    LLM_ARCH_GEMMA3N,
     LLM_ARCH_STARCODER2,
     LLM_ARCH_MAMBA,
     LLM_ARCH_XVERSE,
@@ -54,6 +61,7 @@ enum llm_arch {
     LLM_ARCH_DEEPSEEK,
     LLM_ARCH_DEEPSEEK2,
     LLM_ARCH_CHATGLM,
+    LLM_ARCH_GLM4,
     LLM_ARCH_BITNET,
     LLM_ARCH_T5,
     LLM_ARCH_T5ENCODER,
@@ -62,10 +70,17 @@ enum llm_arch {
     LLM_ARCH_EXAONE,
     LLM_ARCH_RWKV6,
     LLM_ARCH_RWKV6QWEN2,
+    LLM_ARCH_RWKV7,
+    LLM_ARCH_ARWKV7,
     LLM_ARCH_GRANITE,
     LLM_ARCH_GRANITE_MOE,
     LLM_ARCH_CHAMELEON,
     LLM_ARCH_WAVTOKENIZER_DEC,
+    LLM_ARCH_PLM,
+    LLM_ARCH_BAILINGMOE,
+    LLM_ARCH_DOTS1,
+    LLM_ARCH_ARCEE,
+    LLM_ARCH_ERNIE4_5,
     LLM_ARCH_UNKNOWN,
 };
 
@@ -74,6 +89,7 @@ enum llm_kv {
     LLM_KV_GENERAL_ARCHITECTURE,
     LLM_KV_GENERAL_QUANTIZATION_VERSION,
     LLM_KV_GENERAL_ALIGNMENT,
+    LLM_KV_GENERAL_FILE_TYPE,
     LLM_KV_GENERAL_NAME,
     LLM_KV_GENERAL_AUTHOR,
     LLM_KV_GENERAL_VERSION,
@@ -100,6 +116,7 @@ enum llm_kv {
     LLM_KV_EXPERT_WEIGHTS_SCALE,
     LLM_KV_EXPERT_WEIGHTS_NORM,
     LLM_KV_EXPERT_GATING_FUNC,
+    LLM_KV_MOE_EVERY_N_LAYERS,
     LLM_KV_POOLING_TYPE,
     LLM_KV_LOGIT_SCALE,
     LLM_KV_DECODER_START_TOKEN_ID,
@@ -112,6 +129,7 @@ enum llm_kv {
     LLM_KV_RESIDUAL_SCALE,
     LLM_KV_EMBEDDING_SCALE,
     LLM_KV_TOKEN_SHIFT_COUNT,
+    LLM_KV_INTERLEAVE_MOE_LAYER_STEP,
 
     LLM_KV_ATTENTION_HEAD_COUNT,
     LLM_KV_ATTENTION_HEAD_COUNT_KV,
@@ -126,9 +144,16 @@ enum llm_kv {
     LLM_KV_ATTENTION_CAUSAL,
     LLM_KV_ATTENTION_Q_LORA_RANK,
     LLM_KV_ATTENTION_KV_LORA_RANK,
+    LLM_KV_ATTENTION_DECAY_LORA_RANK,
+    LLM_KV_ATTENTION_ICLR_LORA_RANK,
+    LLM_KV_ATTENTION_VALUE_RESIDUAL_MIX_LORA_RANK,
+    LLM_KV_ATTENTION_GATE_LORA_RANK,
     LLM_KV_ATTENTION_RELATIVE_BUCKETS_COUNT,
     LLM_KV_ATTENTION_SLIDING_WINDOW,
     LLM_KV_ATTENTION_SCALE,
+    LLM_KV_ATTENTION_KEY_LENGTH_MLA,
+    LLM_KV_ATTENTION_VALUE_LENGTH_MLA,
+    LLM_KV_ATTENTION_LAYER_INDICES,
 
     LLM_KV_ROPE_DIMENSION_COUNT,
     LLM_KV_ROPE_DIMENSION_SECTIONS,
@@ -171,13 +196,13 @@ enum llm_kv {
     LLM_KV_TOKENIZER_MASK_ID,
     LLM_KV_TOKENIZER_ADD_BOS,
     LLM_KV_TOKENIZER_ADD_EOS,
+    LLM_KV_TOKENIZER_ADD_SEP,
     LLM_KV_TOKENIZER_ADD_PREFIX,
     LLM_KV_TOKENIZER_REMOVE_EXTRA_WS,
     LLM_KV_TOKENIZER_PRECOMPILED_CHARSMAP,
     LLM_KV_TOKENIZER_HF_JSON,
     LLM_KV_TOKENIZER_RWKV,
     LLM_KV_TOKENIZER_CHAT_TEMPLATE,
-    LLM_KV_TOKENIZER_CHAT_TEMPLATE_N,
     LLM_KV_TOKENIZER_FIM_PRE_ID,
     LLM_KV_TOKENIZER_FIM_SUF_ID,
     LLM_KV_TOKENIZER_FIM_MID_ID,
@@ -194,6 +219,8 @@ enum llm_kv {
     LLM_KV_CONVNEXT_EMBEDDING_LENGTH,
     LLM_KV_CONVNEXT_BLOCK_COUNT,
 
+    LLM_KV_CLASSIFIER_OUTPUT_LABELS,
+
     // deprecated:
     LLM_KV_TOKENIZER_PREFIX_ID,
     LLM_KV_TOKENIZER_SUFFIX_ID,
@@ -242,6 +269,24 @@ enum llm_tensor {
     LLM_TENSOR_ATTN_Q_NORM,
     LLM_TENSOR_ATTN_K_NORM,
     LLM_TENSOR_LAYER_OUT_NORM,
+    LLM_TENSOR_POST_ATTN_NORM,
+    LLM_TENSOR_POST_MLP_NORM,
+    LLM_TENSOR_PER_LAYER_TOKEN_EMBD, // gemma3n
+    LLM_TENSOR_PER_LAYER_MODEL_PROJ, // gemma3n
+    LLM_TENSOR_PER_LAYER_INP_GATE,   // gemma3n
+    LLM_TENSOR_PER_LAYER_PROJ,       // gemma3n
+    LLM_TENSOR_PER_LAYER_PROJ_NORM,  // gemma3n
+    LLM_TENSOR_PER_LAYER_POST_NORM,  // gemma3n
+    LLM_TENSOR_ALTUP_PROJ,           // gemma3n
+    LLM_TENSOR_ALTUP_UNEMBD_PROJ,    // gemma3n
+    LLM_TENSOR_ALTUP_CORRECT_COEF,   // gemma3n
+    LLM_TENSOR_ALTUP_CORRECT_SCALE,  // gemma3n
+    LLM_TENSOR_ALTUP_PREDICT_COEF,   // gemma3n
+    LLM_TENSOR_ALTUP_ROUTER,         // gemma3n
+    LLM_TENSOR_ALTUP_ROUTER_NORM,    // gemma3n
+    LLM_TENSOR_LAUREL_L,             // gemma3n
+    LLM_TENSOR_LAUREL_R,             // gemma3n
+    LLM_TENSOR_LAUREL_POST_NORM,     // gemma3n
     LLM_TENSOR_SSM_IN,
     LLM_TENSOR_SSM_CONV1D,
     LLM_TENSOR_SSM_X,
@@ -249,8 +294,20 @@ enum llm_tensor {
     LLM_TENSOR_SSM_A,
     LLM_TENSOR_SSM_D,
     LLM_TENSOR_SSM_OUT,
+    LLM_TENSOR_TIME_MIX_W0,
     LLM_TENSOR_TIME_MIX_W1,
     LLM_TENSOR_TIME_MIX_W2,
+    LLM_TENSOR_TIME_MIX_A0,
+    LLM_TENSOR_TIME_MIX_A1,
+    LLM_TENSOR_TIME_MIX_A2,
+    LLM_TENSOR_TIME_MIX_V0,
+    LLM_TENSOR_TIME_MIX_V1,
+    LLM_TENSOR_TIME_MIX_V2,
+    LLM_TENSOR_TIME_MIX_G1,
+    LLM_TENSOR_TIME_MIX_G2,
+    LLM_TENSOR_TIME_MIX_K_K,
+    LLM_TENSOR_TIME_MIX_K_A,
+    LLM_TENSOR_TIME_MIX_R_K,
     LLM_TENSOR_TIME_MIX_LERP_X,
     LLM_TENSOR_TIME_MIX_LERP_W,
     LLM_TENSOR_TIME_MIX_LERP_K,
@@ -277,6 +334,8 @@ enum llm_tensor {
     LLM_TENSOR_ATTN_Q_B,
     LLM_TENSOR_ATTN_KV_A_MQA,
     LLM_TENSOR_ATTN_KV_B,
+    LLM_TENSOR_ATTN_K_B,
+    LLM_TENSOR_ATTN_V_B,
     LLM_TENSOR_ATTN_Q_A_NORM,
     LLM_TENSOR_ATTN_KV_A_NORM,
     LLM_TENSOR_ATTN_SUB_NORM,
@@ -400,3 +459,6 @@ const char * llm_arch_name(llm_arch arch);
 llm_arch llm_arch_from_string(const std::string & name);
 
 const llm_tensor_info & llm_tensor_info_for(llm_tensor tensor);
+
+bool llm_arch_is_recurrent(const llm_arch & arch);
+bool llm_arch_is_hybrid   (const llm_arch & arch);