ggml : try to improve threading

.github/workflows/bindings.yml

@@ -1,22 +0,0 @@
-name: Bindings Tests
-on:
-  push:
-    paths:
-      - bindings/go/**
-      - whisper.h
-  pull_request:
-    paths:
-      - bindings/go/**
-      - whisper.h
-
-jobs:
-  ubuntu-latest:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/setup-go@v3
-        with:
-          go-version: '^1.19'
-      - uses: actions/checkout@v1
-      - run: |
-          cd bindings/go
-          make test

.github/workflows/build.yml

@@ -1,5 +1,5 @@
 name: CI
-on: [push, pull_request]
+on: [push]
 
 jobs:
     ubuntu-latest:
@@ -235,33 +235,3 @@ jobs:
               with:
                 name: whisper-blas-bin-${{ matrix.arch }}
                 path: build/bin/${{ matrix.build }}
-
-  emscripten:
-    runs-on: ubuntu-latest
-
-    strategy:
-      matrix:
-        build: [Release]
-
-    steps:
-      - name: Clone
-        uses: actions/checkout@v1
-
-      - name: Dependencies
-        run: |
-          wget -q https://github.com/emscripten-core/emsdk/archive/master.tar.gz
-          tar -xvf master.tar.gz
-          emsdk-master/emsdk update
-          emsdk-master/emsdk install latest
-          emsdk-master/emsdk activate latest
-
-      - name: Configure
-        run: echo "tmp"
-
-      - name: Build
-        run: |
-          pushd emsdk-master
-          source ./emsdk_env.sh
-          popd
-          emcmake cmake . -DCMAKE_BUILD_TYPE=${{ matrix.build }}
-          make

.gitignore

@@ -1,5 +1,4 @@
 *.o
-*.a
 .cache/
 .vs/
 .vscode/
@@ -9,7 +8,6 @@ build/
 build-em/
 build-debug/
 build-release/
-build-static/
 build-sanitize-addr/
 build-sanitize-thread/
 
@@ -19,9 +17,7 @@ build-sanitize-thread/
 /talk
 /bench
 
-arm_neon.h
 sync.sh
-libwhisper.a
 libwhisper.so
 compile_commands.json
 

CMakeLists.txt

@@ -1,16 +1,15 @@
 cmake_minimum_required (VERSION 3.0)
 
-project(whisper.cpp VERSION 1.2.0)
+project(whisper.cpp VERSION 1.0.4)
-
-# Add path to modules
-list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/cmake/")
 
+set(CMAKE_EXPORT_COMPILE_COMMANDS "on")
 set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
+set(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib")
 
 if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
     set(WHISPER_STANDALONE ON)
-    include(GitVars)
+    include(cmake/GitVars.cmake)
-    include(BuildTypes)
+    include(cmake/BuildTypes.cmake)
 
     # configure project version
     if (EXISTS "${CMAKE_SOURCE_DIR}/bindings/ios/Makefile-tmpl")
@@ -53,7 +52,6 @@ if (APPLE)
     option(WHISPER_NO_ACCELERATE       "whisper: disable Accelerate framework" OFF)
     option(WHISPER_NO_AVX              "whisper: disable AVX" OFF)
     option(WHISPER_NO_AVX2             "whisper: disable AVX2" OFF)
-    option(WHISPER_NO_FMA              "whisper: disable FMA" OFF)
 else()
     option(WHISPER_SUPPORT_OPENBLAS    "whisper: support for OpenBLAS" OFF)
 endif()
@@ -84,6 +82,9 @@ endif()
 
 # dependencies
 
+set(CMAKE_C_STANDARD   11)
+set(CMAKE_CXX_STANDARD 11)
+
 find_package(Threads REQUIRED)
 
 # on APPLE - include Accelerate framework
@@ -130,7 +131,6 @@ if (WHISPER_ALL_WARNINGS)
             -Wcast-qual                     \
             -Wstrict-prototypes             \
             -Wpointer-arith                 \
-            -Wno-unused-function            \
         ")
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} \
             -Wall                           \
@@ -157,7 +157,6 @@ else()
     if (MSVC)
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX2")
         set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} /arch:AVX2")
-        set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /arch:AVX2")
     else()
         if (EMSCRIPTEN)
             set(CMAKE_C_FLAGS   "${CMAKE_C_FLAGS}   -pthread")
@@ -169,10 +168,7 @@ else()
             if(NOT WHISPER_NO_AVX2)
                 set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mavx2")
             endif()
-            if(NOT WHISPER_NO_FMA)
+            set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mfma -mf16c")
-                set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mfma")
-            endif()
-            set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -mf16c")
         endif()
     endif()
 endif()
@@ -194,8 +190,6 @@ add_library(${TARGET}
     whisper.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_include_directories(${TARGET} PUBLIC
     .
     )
@@ -229,7 +223,6 @@ target_compile_definitions(${TARGET} PUBLIC
 install(TARGETS ${TARGET}
     LIBRARY DESTINATION lib
     ARCHIVE DESTINATION lib/static
-    RUNTIME DESTINATION bin
     )
 
 #

Makefile

@@ -10,9 +10,6 @@ ifndef UNAME_M
 UNAME_M := $(shell uname -m)
 endif
 
-CCV := $(shell $(CC) --version | head -n 1)
-CXXV := $(shell $(CXX) --version | head -n 1)
-
 # Mac OS + Arm can report x86_64
 # ref: https://github.com/ggerganov/whisper.cpp/issues/66#issuecomment-1282546789
 ifeq ($(UNAME_S),Darwin)
@@ -56,13 +53,10 @@ endif
 # Architecture specific
 # TODO: probably these flags need to be tweaked on some architectures
 #       feel free to update the Makefile for your architecture and send a pull request or issue
-ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686))
+ifeq ($(UNAME_M),x86_64)
 	ifeq ($(UNAME_S),Darwin)
-		CFLAGS += -mf16c
+		CFLAGS += -mfma -mf16c
 		AVX1_M := $(shell sysctl machdep.cpu.features)
-		ifneq (,$(findstring FMA,$(AVX1_M)))
-			CFLAGS += -mfma
-		endif
 		ifneq (,$(findstring AVX1.0,$(AVX1_M)))
 			CFLAGS += -mavx
 		endif
@@ -87,10 +81,6 @@ ifeq ($(UNAME_M),$(filter $(UNAME_M),x86_64 i686))
 		ifneq (,$(findstring f16c,$(F16C_M)))
 			CFLAGS += -mf16c
 		endif
-		SSE3_M := $(shell grep "sse3 " /proc/cpuinfo)
-		ifneq (,$(findstring sse3,$(SSE3_M)))
-			CFLAGS += -msse3
-		endif
 	else ifeq ($(UNAME_S),Haiku)
 		AVX1_M := $(shell sysinfo -cpu | grep "AVX ")
 		ifneq (,$(findstring avx,$(AVX1_M)))
@@ -115,15 +105,11 @@ endif
 ifeq ($(UNAME_M),amd64)
 	CFLAGS += -mavx -mavx2 -mfma -mf16c
 endif
-ifneq ($(filter ppc64%,$(UNAME_M)),)
+ifeq ($(UNAME_M),ppc64le)
 	POWER9_M := $(shell grep "POWER9" /proc/cpuinfo)
 	ifneq (,$(findstring POWER9,$(POWER9_M)))
 		CFLAGS += -mpower9-vector
 	endif
-	# Require c++23's std::byteswap for big-endian support.
-	ifeq ($(UNAME_M),ppc64)
-		CXXFLAGS += -std=c++23 -DGGML_BIG_ENDIAN
-	endif
 endif
 ifndef WHISPER_NO_ACCELERATE
 	# Mac M1 - include Accelerate framework
@@ -155,21 +141,6 @@ ifneq ($(filter armv8%,$(UNAME_M)),)
 	CFLAGS += -mfp16-format=ieee -mno-unaligned-access
 endif
 
-#
-# Print build information
-#
-
-$(info I whisper.cpp build info: )
-$(info I UNAME_S:  $(UNAME_S))
-$(info I UNAME_P:  $(UNAME_P))
-$(info I UNAME_M:  $(UNAME_M))
-$(info I CFLAGS:   $(CFLAGS))
-$(info I CXXFLAGS: $(CXXFLAGS))
-$(info I LDFLAGS:  $(LDFLAGS))
-$(info I CC:       $(CCV))
-$(info I CXX:      $(CXXV))
-$(info )
-
 default: main
 
 #

README.md

@@ -4,16 +4,15 @@
 [![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)
 [![npm](https://img.shields.io/npm/v/whisper.cpp.svg)](https://www.npmjs.com/package/whisper.cpp/)
 
-Stable: [v1.2.0](https://github.com/ggerganov/whisper.cpp/releases/tag/v1.2.0) / [Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
+[Roadmap | F.A.Q.](https://github.com/ggerganov/whisper.cpp/discussions/126)
 
 High-performance inference of [OpenAI's Whisper](https://github.com/openai/whisper) automatic speech recognition (ASR) model:
 
 - Plain C/C++ implementation without dependencies
 - Apple silicon first-class citizen - optimized via Arm Neon and Accelerate framework
 - AVX intrinsics support for x86 architectures
-- VSX intrinsics support for POWER architectures
 - Mixed F16 / F32 precision
-- Low memory usage (Flash Attention)
+- Low memory usage (Flash Attention + Flash Forward)
 - Zero memory allocations at runtime
 - Runs on the CPU
 - [C-style API](https://github.com/ggerganov/whisper.cpp/blob/master/whisper.h)
@@ -71,7 +70,7 @@ Now build the [main](examples/main) example and transcribe an audio file like th
 make
 
 # transcribe an audio file
-./main -f samples/jfk.wav
+./main -f input.wav
 ```
 
 ---
@@ -97,31 +96,20 @@ options:
   -d  N,    --duration N    [0      ] duration of audio to process in milliseconds
   -mc N,    --max-context N [-1     ] maximum number of text context tokens to store
   -ml N,    --max-len N     [0      ] maximum segment length in characters
-  -bo N,     --best-of N         [5      ] number of best candidates to keep
-  -bs N,     --beam-size N       [-1     ] beam size for beam search
   -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
   -su,      --speed-up      [false  ] speed up audio by x2 (reduced accuracy)
   -tr,      --translate     [false  ] translate from source language to english
-  -di,       --diarize           [false  ] stereo audio diarization
-  -nf,       --no-fallback       [false  ] do not use temperature fallback while decoding
   -otxt,    --output-txt    [false  ] output result in a text file
   -ovtt,    --output-vtt    [false  ] output result in a vtt file
   -osrt,    --output-srt    [false  ] output result in a srt file
   -owts,    --output-words  [false  ] output script for generating karaoke video
-  -ocsv,     --output-csv        [false  ] output result in a CSV file
-  -of FNAME, --output-file FNAME [       ] output file path (without file extension)
   -ps,      --print-special [false  ] print special tokens
   -pc,      --print-colors  [false  ] print colors
-  -pp,       --print-progress    [false  ] print progress
   -nt,      --no-timestamps [true   ] do not print timestamps
-  -l LANG,   --language LANG     [en     ] spoken language ('auto' for auto-detect)
+  -l LANG,  --language LANG [en     ] spoken language
-             --prompt PROMPT     [       ] initial prompt
   -m FNAME, --model FNAME   [models/ggml-base.en.bin] model path
   -f FNAME, --file FNAME    [       ] input WAV file path
 
-
 bash ./models/download-ggml-model.sh base.en
 Downloading ggml model base.en ...
 ggml-base.en.bin               100%[========================>] 141.11M  6.34MB/s    in 24s
@@ -139,8 +127,7 @@ Running base.en on all samples in ./samples ...
 [+] Running base.en on samples/jfk.wav ... (run 'ffplay samples/jfk.wav' to listen)
 ----------------------------------------------
 
-whisper_init_from_file: loading model from 'models/ggml-base.en.bin'
+whisper_model_load: loading model from 'models/ggml-base.en.bin'
-whisper_model_load: loading model
 whisper_model_load: n_vocab       = 51864
 whisper_model_load: n_audio_ctx   = 1500
 whisper_model_load: n_audio_state = 512
@@ -153,14 +140,13 @@ whisper_model_load: n_text_layer  = 6
 whisper_model_load: n_mels        = 80
 whisper_model_load: f16           = 1
 whisper_model_load: type          = 2
-whisper_model_load: mem required  =  215.00 MB (+    6.00 MB per decoder)
-whisper_model_load: kv self size  =    5.25 MB
-whisper_model_load: kv cross size =   17.58 MB
 whisper_model_load: adding 1607 extra tokens
-whisper_model_load: model ctx     =  140.60 MB
+whisper_model_load: mem_required  =  506.00 MB
+whisper_model_load: ggml ctx size =  140.60 MB
+whisper_model_load: memory size   =   22.83 MB
 whisper_model_load: model size    =  140.54 MB
 
-system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
+system_info: n_threads = 4 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 1 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 |
 
 main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
 
@@ -168,13 +154,12 @@ main: processing 'samples/jfk.wav' (176000 samples, 11.0 sec), 4 threads, 1 proc
 [00:00:00.000 --> 00:00:11.000]   And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
 
 
-whisper_print_timings:     fallbacks =   0 p /   0 h
+whisper_print_timings:     load time =   105.91 ms
-whisper_print_timings:     load time =   113.81 ms
+whisper_print_timings:      mel time =    24.62 ms
-whisper_print_timings:      mel time =    15.40 ms
+whisper_print_timings:   sample time =     3.63 ms
-whisper_print_timings:   sample time =    11.58 ms /    27 runs (    0.43 ms per run)
+whisper_print_timings:   encode time =   324.71 ms / 54.12 ms per layer
-whisper_print_timings:   encode time =   266.60 ms /     1 runs (  266.60 ms per run)
+whisper_print_timings:   decode time =    83.58 ms / 13.93 ms per layer
-whisper_print_timings:   decode time =    66.11 ms /    27 runs (    2.45 ms per run)
+whisper_print_timings:    total time =   542.81 ms
-whisper_print_timings:    total time =   476.31 ms
 ```
 
 The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`.
@@ -217,16 +202,26 @@ make large
 
 | Model  | Disk   | Mem     | SHA                                        |
 | ---    | ---    | ---     | ---                                        |
-| tiny   |  75 MB | ~125 MB | `bd577a113a864445d4c299885e0cb97d4ba92b5f` |
+| tiny   |  75 MB | ~390 MB | `bd577a113a864445d4c299885e0cb97d4ba92b5f` |
-| base   | 142 MB | ~210 MB | `465707469ff3a37a2b9b8d8f89f2f99de7299dac` |
+| base   | 142 MB | ~500 MB | `465707469ff3a37a2b9b8d8f89f2f99de7299dac` |
-| small  | 466 MB | ~600 MB | `55356645c2b361a969dfd0ef2c5a50d530afd8d5` |
+| small  | 466 MB | ~1.0 GB | `55356645c2b361a969dfd0ef2c5a50d530afd8d5` |
-| medium | 1.5 GB | ~1.7 GB | `fd9727b6e1217c2f614f9b698455c4ffd82463b4` |
+| medium | 1.5 GB | ~2.6 GB | `fd9727b6e1217c2f614f9b698455c4ffd82463b4` |
-| large  | 2.9 GB | ~3.3 GB | `0f4c8e34f21cf1a914c59d8b3ce882345ad349d6` |
+| large  | 2.9 GB | ~4.7 GB | `0f4c8e34f21cf1a914c59d8b3ce882345ad349d6` |
 
 ## Limitations
 
 - Inference only
-- No GPU support (yet)
+- No GPU support
+- Very basic greedy sampling scheme - always pick up the token with highest probability.
+  This should be similar to the [GreedyDecoder](https://github.com/openai/whisper/blob/main/whisper/decoding.py#L249-L274)
+  from the original python implementation, so in order to make a fair comparison between the 2 implementations, make sure
+  to run the python code with the following parameters:
+
+  ```
+  whisper --best_of None --beam_size None ...
+  ```
+
+  In the future, `whisper.cpp` will support more sampling strategies.
 
 ## Another example
 
@@ -239,8 +234,7 @@ in about half a minute on a MacBook M1 Pro, using `medium.en` model:
 ```java
 $ ./main -m models/ggml-medium.en.bin -f samples/gb1.wav -t 8
 
-whisper_init_from_file: loading model from 'models/ggml-medium.en.bin'
+whisper_model_load: loading model from 'models/ggml-medium.en.bin'
-whisper_model_load: loading model
 whisper_model_load: n_vocab       = 51864
 whisper_model_load: n_audio_ctx   = 1500
 whisper_model_load: n_audio_state = 1024
@@ -253,60 +247,55 @@ whisper_model_load: n_text_layer  = 24
 whisper_model_load: n_mels        = 80
 whisper_model_load: f16           = 1
 whisper_model_load: type          = 4
-whisper_model_load: mem required  = 1720.00 MB (+   43.00 MB per decoder)
+whisper_model_load: mem_required  = 2610.00 MB
-whisper_model_load: kv self size  =   42.00 MB
-whisper_model_load: kv cross size =  140.62 MB
 whisper_model_load: adding 1607 extra tokens
-whisper_model_load: model ctx     = 1462.35 MB
+whisper_model_load: ggml ctx size = 1644.97 MB
+whisper_model_load: memory size =   182.62 MB
 whisper_model_load: model size  =  1462.12 MB
 
-system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | FMA = 0 | NEON = 1 | ARM_FMA = 1 | F16C = 0 | FP16_VA = 1 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 0 | VSX = 0 |
+main: processing 'samples/gb1.wav' (3179750 samples, 198.7 sec), 8 threads, lang = en, task = transcribe, timestamps = 1 ...
 
-main: processing 'samples/gb1.wav' (3179750 samples, 198.7 sec), 8 threads, 1 processors, lang = en, task = transcribe, timestamps = 1 ...
+[00:00.000 --> 00:08.000]   My fellow Americans, this day has brought terrible news and great sadness to our country.
+[00:08.000 --> 00:17.000]   At nine o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
+[00:17.000 --> 00:23.000]   A short time later, debris was seen falling from the skies above Texas.
+[00:23.000 --> 00:29.000]   The Columbia's lost. There are no survivors.
+[00:29.000 --> 00:32.000]   On board was a crew of seven.
+[00:32.000 --> 00:39.000]   Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark,
+[00:39.000 --> 00:48.000]   Captain David Brown, Commander William McCool, Dr. Kultna Shavla, and Ilan Ramon,
+[00:48.000 --> 00:52.000]   a colonel in the Israeli Air Force.
+[00:52.000 --> 00:58.000]   These men and women assumed great risk in the service to all humanity.
+[00:58.000 --> 01:03.000]   In an age when space flight has come to seem almost routine,
+[01:03.000 --> 01:07.000]   it is easy to overlook the dangers of travel by rocket
+[01:07.000 --> 01:12.000]   and the difficulties of navigating the fierce outer atmosphere of the Earth.
+[01:12.000 --> 01:18.000]   These astronauts knew the dangers, and they faced them willingly,
+[01:18.000 --> 01:23.000]   knowing they had a high and noble purpose in life.
+[01:23.000 --> 01:31.000]   Because of their courage and daring and idealism, we will miss them all the more.
+[01:31.000 --> 01:36.000]   All Americans today are thinking as well of the families of these men and women
+[01:36.000 --> 01:40.000]   who have been given this sudden shock and grief.
+[01:40.000 --> 01:45.000]   You're not alone. Our entire nation grieves with you,
+[01:45.000 --> 01:52.000]   and those you love will always have the respect and gratitude of this country.
+[01:52.000 --> 01:56.000]   The cause in which they died will continue.
+[01:56.000 --> 02:04.000]   Mankind is led into the darkness beyond our world by the inspiration of discovery
+[02:04.000 --> 02:11.000]   and the longing to understand. Our journey into space will go on.
+[02:11.000 --> 02:16.000]   In the skies today, we saw destruction and tragedy.
+[02:16.000 --> 02:22.000]   Yet farther than we can see, there is comfort and hope.
+[02:22.000 --> 02:29.000]   In the words of the prophet Isaiah, "Lift your eyes and look to the heavens
+[02:29.000 --> 02:35.000]   who created all these. He who brings out the starry hosts one by one
+[02:35.000 --> 02:39.000]   and calls them each by name."
+[02:39.000 --> 02:46.000]   Because of His great power and mighty strength, not one of them is missing.
+[02:46.000 --> 02:55.000]   The same Creator who names the stars also knows the names of the seven souls we mourn today.
+[02:55.000 --> 03:01.000]   The crew of the shuttle Columbia did not return safely to earth,
+[03:01.000 --> 03:05.000]   yet we can pray that all are safely home.
+[03:05.000 --> 03:13.000]   May God bless the grieving families, and may God continue to bless America.
+[03:13.000 --> 03:41.000]   Audio
 
 
-[00:00:00.000 --> 00:00:08.000]   My fellow Americans, this day has brought terrible news and great sadness to our country.
+whisper_print_timings:     load time =   575.92 ms
-[00:00:08.000 --> 00:00:17.000]   At nine o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
+whisper_print_timings:      mel time =   230.60 ms
-[00:00:17.000 --> 00:00:23.000]   A short time later, debris was seen falling from the skies above Texas.
+whisper_print_timings:   sample time =    73.19 ms
-[00:00:23.000 --> 00:00:29.000]   The Columbia's lost. There are no survivors.
+whisper_print_timings:   encode time = 19552.61 ms / 814.69 ms per layer
-[00:00:29.000 --> 00:00:32.000]   On board was a crew of seven.
+whisper_print_timings:   decode time = 13249.96 ms / 552.08 ms per layer
-[00:00:32.000 --> 00:00:39.000]   Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark,
+whisper_print_timings:    total time = 33686.27 ms
-[00:00:39.000 --> 00:00:48.000]   Captain David Brown, Commander William McCool, Dr. Kultna Shavla, and Ilan Ramon,
-[00:00:48.000 --> 00:00:52.000]   a colonel in the Israeli Air Force.
-[00:00:52.000 --> 00:00:58.000]   These men and women assumed great risk in the service to all humanity.
-[00:00:58.000 --> 00:01:03.000]   In an age when space flight has come to seem almost routine,
-[00:01:03.000 --> 00:01:07.000]   it is easy to overlook the dangers of travel by rocket
-[00:01:07.000 --> 00:01:12.000]   and the difficulties of navigating the fierce outer atmosphere of the Earth.
-[00:01:12.000 --> 00:01:18.000]   These astronauts knew the dangers, and they faced them willingly,
-[00:01:18.000 --> 00:01:23.000]   knowing they had a high and noble purpose in life.
-[00:01:23.000 --> 00:01:31.000]   Because of their courage and daring and idealism, we will miss them all the more.
-[00:01:31.000 --> 00:01:36.000]   All Americans today are thinking as well of the families of these men and women
-[00:01:36.000 --> 00:01:40.000]   who have been given this sudden shock and grief.
-[00:01:40.000 --> 00:01:45.000]   You're not alone. Our entire nation grieves with you,
-[00:01:45.000 --> 00:01:52.000]   and those you love will always have the respect and gratitude of this country.
-[00:01:52.000 --> 00:01:56.000]   The cause in which they died will continue.
-[00:01:56.000 --> 00:02:04.000]   Mankind is led into the darkness beyond our world by the inspiration of discovery
-[00:02:04.000 --> 00:02:11.000]   and the longing to understand. Our journey into space will go on.
-[00:02:11.000 --> 00:02:16.000]   In the skies today, we saw destruction and tragedy.
-[00:02:16.000 --> 00:02:22.000]   Yet farther than we can see, there is comfort and hope.
-[00:02:22.000 --> 00:02:29.000]   In the words of the prophet Isaiah, "Lift your eyes and look to the heavens
-[00:02:29.000 --> 00:02:35.000]   who created all these. He who brings out the starry hosts one by one
-[00:02:35.000 --> 00:02:39.000]   and calls them each by name."
-[00:02:39.000 --> 00:02:46.000]   Because of His great power and mighty strength, not one of them is missing.
-[00:02:46.000 --> 00:02:55.000]   The same Creator who names the stars also knows the names of the seven souls we mourn today.
-[00:02:55.000 --> 00:03:01.000]   The crew of the shuttle Columbia did not return safely to earth,
-[00:03:01.000 --> 00:03:05.000]   yet we can pray that all are safely home.
-[00:03:05.000 --> 00:03:13.000]   May God bless the grieving families, and may God continue to bless America.
-[00:03:13.000 --> 00:03:19.000]   [Silence]
-
-
-whisper_print_timings:     fallbacks =   1 p /   0 h
-whisper_print_timings:     load time =   569.03 ms
-whisper_print_timings:      mel time =   146.85 ms
-whisper_print_timings:   sample time =   238.66 ms /   553 runs (    0.43 ms per run)
-whisper_print_timings:   encode time = 18665.10 ms /     9 runs ( 2073.90 ms per run)
-whisper_print_timings:   decode time = 13090.93 ms /   549 runs (   23.85 ms per run)
-whisper_print_timings:    total time = 32733.52 ms
 ```
 </details>
 
@@ -317,7 +306,6 @@ The [stream](examples/stream) tool samples the audio every half a second and run
 More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
 
 ```java
-make stream
 ./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
 ```
 

bindings/go/.gitignore

@@ -1,2 +1,3 @@
 build
 models
+go.sum

bindings/go/Makefile

@@ -1,27 +1,28 @@
-BUILD_DIR := build
+CMAKE := $(shell which cmake)
-MODELS_DIR := models
+BUILD_DIR := "build"
+MODELS_DIR := "models"
 EXAMPLES_DIR := $(wildcard examples/*)
-INCLUDE_PATH := $(abspath ../..)
+C_INCLUDE_PATH := "../.."
-LIBRARY_PATH := $(abspath ../..)
 
 all: clean whisper examples
 
 whisper: mkdir
 	@echo Build whisper
-	@${MAKE} -C ../.. libwhisper.a
+	@${CMAKE} -S ../.. -B ${BUILD_DIR} -D BUILD_SHARED_LIBS=off -D WHISPER_NO_AVX2=on
+	@${CMAKE} --build ${BUILD_DIR} --target whisper
 
 test: model-small whisper modtidy
-	@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go test -v .
+	@go test -v .
-	@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go test -v ./pkg/whisper/...
+	@go test -v ./pkg/whisper/...
 
 examples: $(EXAMPLES_DIR)
 
 model-small: mkdir examples/go-model-download
-	@${BUILD_DIR}/go-model-download -out models ggml-small.en.bin
+	@${BUILD_DIR}/go-model-download -out models small.en
 
 $(EXAMPLES_DIR): mkdir whisper modtidy
 	@echo Build example $(notdir $@)
-	@C_INCLUDE_PATH=${INCLUDE_PATH} LIBRARY_PATH=${LIBRARY_PATH} go build ${BUILD_FLAGS} -o ${BUILD_DIR}/$(notdir $@) ./$@
+	@go build ${BUILD_FLAGS} -o ${BUILD_DIR}/$(notdir $@) ./$@
 
 mkdir:
 	@echo Mkdir ${BUILD_DIR}

bindings/go/README.md

@@ -74,27 +74,4 @@ And you can then test a model against samples with the following command:
 ./build/go-whisper -model models/ggml-tiny.en.bin samples/jfk.wav 
 ```
 
-## Using the bindings
-
-To use the bindings in your own software,
-
-  1. Import `github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper` (or `github.com/ggerganov/whisper.cpp/bindings/go` into your package;
-  2. Compile `libwhisper.a` (you can use `make whisper` in the `bindings/go` directory);
-  3. Link your go binary against whisper by setting the environment variables `C_INCLUDE_PATH` and `LIBRARY_PATH`
-     to point to the `whisper.h` file directory and `libwhisper.a` file directory respectively.
-
-Look at the `Makefile` in the `bindings/go` directory for an example.
-
-The API Documentation:
-
-  * https://pkg.go.dev/github.com/ggerganov/whisper.cpp/bindings/go
-  * https://pkg.go.dev/github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper
-
-Getting help:
-
-  * Follow the discussion for the go bindings [here](https://github.com/ggerganov/whisper.cpp/discussions/312)
-
-## License
-
-The license for the Go bindings is the same as the license for the rest of the whisper.cpp project, which is the MIT License. See the `LICENSE` file for more details.
 

bindings/go/examples/go-model-download/main.go

@@ -17,14 +17,15 @@ import (
 // CONSTANTS
 
 const (
-	srcUrl  = "https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main" // The location of the models
+	srcUrl        = "https://huggingface.co/"                           // The location of the models
+	srcPathPrefix = "/datasets/ggerganov/whisper.cpp/resolve/main/ggml" // Filename prefix
 	srcExt        = ".bin"                                              // Filename extension
 	bufSize       = 1024 * 64                                           // Size of the buffer used for downloading the model
 )
 
 var (
 	// The models which will be downloaded, if no model is specified as an argument
-	modelNames = []string{"ggml-tiny.en", "ggml-tiny", "ggml-base.en", "ggml-base", "ggml-small.en", "ggml-small", "ggml-medium.en", "ggml-medium", "ggml-large-v1", "ggml-large"}
+	modelNames = []string{"tiny.en", "tiny", "base.en", "base", "small.en", "small", "medium.en", "medium", "large-v1", "large"}
 )
 
 var (
@@ -122,14 +123,11 @@ func GetModels() []string {
 
 // URLForModel returns the URL for the given model on huggingface.co
 func URLForModel(model string) (string, error) {
-	if filepath.Ext(model) != srcExt {
-		model += srcExt
-	}
 	url, err := url.Parse(srcUrl)
 	if err != nil {
 		return "", err
 	} else {
-		url.Path = filepath.Join(url.Path, model)
+		url.Path = srcPathPrefix + "-" + model + srcExt
 	}
 	return url.String(), nil
 }

bindings/go/examples/go-whisper/color.go

@@ -1,22 +0,0 @@
-package main
-
-import "fmt"
-
-///////////////////////////////////////////////////////////////////////////////
-// CONSTANTS
-
-const (
-	Reset     = "\033[0m"
-	RGBPrefix = "\033[38;5;" // followed by RGB values in decimal format separated by colons
-	RGBSuffix = "m"
-)
-
-///////////////////////////////////////////////////////////////////////////////
-// PUBLIC METHODS
-
-// Colorize text with RGB values, from 0 to 23
-func Colorize(text string, v int) string {
-	// https://en.wikipedia.org/wiki/ANSI_escape_code#8-bit
-	// Grayscale colors are in the range 232-255
-	return RGBPrefix + fmt.Sprint(v%24+232) + RGBSuffix + text + Reset
-}

bindings/go/examples/go-whisper/flags.go

@@ -2,12 +2,6 @@ package main
 
 import (
 	"flag"
-	"fmt"
-	"strings"
-	"time"
-
-	// Packages
-	whisper "github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
 )
 
 ///////////////////////////////////////////////////////////////////////////////
@@ -48,26 +42,6 @@ func (flags *Flags) GetLanguage() string {
 	return flags.Lookup("language").Value.String()
 }
 
-func (flags *Flags) IsTranslate() bool {
-	return flags.Lookup("translate").Value.(flag.Getter).Get().(bool)
-}
-
-func (flags *Flags) GetOffset() time.Duration {
-	return flags.Lookup("offset").Value.(flag.Getter).Get().(time.Duration)
-}
-
-func (flags *Flags) GetDuration() time.Duration {
-	return flags.Lookup("duration").Value.(flag.Getter).Get().(time.Duration)
-}
-
-func (flags *Flags) GetThreads() uint {
-	return flags.Lookup("threads").Value.(flag.Getter).Get().(uint)
-}
-
-func (flags *Flags) GetOut() string {
-	return strings.ToLower(flags.Lookup("out").Value.String())
-}
-
 func (flags *Flags) IsSpeedup() bool {
 	return flags.Lookup("speedup").Value.String() == "true"
 }
@@ -76,81 +50,12 @@ func (flags *Flags) IsTokens() bool {
 	return flags.Lookup("tokens").Value.String() == "true"
 }
 
-func (flags *Flags) IsColorize() bool {
-	return flags.Lookup("colorize").Value.String() == "true"
-}
-
-func (flags *Flags) GetMaxLen() uint {
-	return flags.Lookup("max-len").Value.(flag.Getter).Get().(uint)
-}
-
-func (flags *Flags) GetMaxTokens() uint {
-	return flags.Lookup("max-tokens").Value.(flag.Getter).Get().(uint)
-}
-
-func (flags *Flags) GetWordThreshold() float32 {
-	return float32(flags.Lookup("word-thold").Value.(flag.Getter).Get().(float64))
-}
-
-func (flags *Flags) SetParams(context whisper.Context) error {
-	if lang := flags.GetLanguage(); lang != "" && lang != "auto" {
-		fmt.Fprintf(flags.Output(), "Setting language to %q\n", lang)
-		if err := context.SetLanguage(lang); err != nil {
-			return err
-		}
-	}
-	if flags.IsTranslate() && context.IsMultilingual() {
-		fmt.Fprintf(flags.Output(), "Setting translate to true\n")
-		context.SetTranslate(true)
-	}
-	if offset := flags.GetOffset(); offset != 0 {
-		fmt.Fprintf(flags.Output(), "Setting offset to %v\n", offset)
-		context.SetOffset(offset)
-	}
-	if duration := flags.GetDuration(); duration != 0 {
-		fmt.Fprintf(flags.Output(), "Setting duration to %v\n", duration)
-		context.SetDuration(duration)
-	}
-	if flags.IsSpeedup() {
-		fmt.Fprintf(flags.Output(), "Setting speedup to true\n")
-		context.SetSpeedup(true)
-	}
-	if threads := flags.GetThreads(); threads != 0 {
-		fmt.Fprintf(flags.Output(), "Setting threads to %d\n", threads)
-		context.SetThreads(threads)
-	}
-	if max_len := flags.GetMaxLen(); max_len != 0 {
-		fmt.Fprintf(flags.Output(), "Setting max_segment_length to %d\n", max_len)
-		context.SetMaxSegmentLength(max_len)
-	}
-	if max_tokens := flags.GetMaxTokens(); max_tokens != 0 {
-		fmt.Fprintf(flags.Output(), "Setting max_tokens to %d\n", max_tokens)
-		context.SetMaxTokensPerSegment(max_tokens)
-	}
-	if word_threshold := flags.GetWordThreshold(); word_threshold != 0 {
-		fmt.Fprintf(flags.Output(), "Setting word_threshold to %f\n", word_threshold)
-		context.SetTokenThreshold(word_threshold)
-	}
-
-	// Return success
-	return nil
-}
-
 ///////////////////////////////////////////////////////////////////////////////
 // PRIVATE METHODS
 
 func registerFlags(flag *Flags) {
 	flag.String("model", "", "Path to the model file")
-	flag.String("language", "", "Spoken language")
+	flag.String("language", "", "Language")
-	flag.Bool("translate", false, "Translate from source language to english")
-	flag.Duration("offset", 0, "Time offset")
-	flag.Duration("duration", 0, "Duration of audio to process")
-	flag.Uint("threads", 0, "Number of threads to use")
 	flag.Bool("speedup", false, "Enable speedup")
-	flag.Uint("max-len", 0, "Maximum segment length in characters")
-	flag.Uint("max-tokens", 0, "Maximum tokens per segment")
-	flag.Float64("word-thold", 0, "Maximum segment score")
 	flag.Bool("tokens", false, "Display tokens")
-	flag.Bool("colorize", false, "Colorize tokens")
-	flag.String("out", "", "Output format (srt, none or leave as empty string)")
 }

bindings/go/examples/go-whisper/main.go

@@ -35,7 +35,8 @@ func main() {
 
 	// Process files
 	for _, filename := range flags.Args() {
-		if err := Process(model, filename, flags); err != nil {
+		fmt.Println("Processing", filename)
+		if err := Process(model, filename, flags.GetLanguage(), flags.IsSpeedup(), flags.IsTokens()); err != nil {
 			fmt.Fprintln(os.Stderr, err)
 			continue
 		}

bindings/go/examples/go-whisper/process.go

@@ -11,7 +11,7 @@ import (
 	wav "github.com/go-audio/wav"
 )
 
-func Process(model whisper.Model, path string, flags *Flags) error {
+func Process(model whisper.Model, path string, lang string, speedup, tokens bool) error {
 	var data []float32
 
 	// Create processing context
@@ -20,22 +20,14 @@ func Process(model whisper.Model, path string, flags *Flags) error {
 		return err
 	}
 
-	// Set the parameters
-	if err := flags.SetParams(context); err != nil {
-		return err
-	}
-
-	fmt.Printf("\n%s\n", context.SystemInfo())
-
 	// Open the file
-	fmt.Fprintf(flags.Output(), "Loading %q\n", path)
 	fh, err := os.Open(path)
 	if err != nil {
 		return err
 	}
 	defer fh.Close()
 
-	// Decode the WAV file - load the full buffer
+	// Decode the WAV file
 	dec := wav.NewDecoder(fh)
 	if buf, err := dec.FullPCMBuffer(); err != nil {
 		return err
@@ -47,86 +39,42 @@ func Process(model whisper.Model, path string, flags *Flags) error {
 		data = buf.AsFloat32Buffer().Data
 	}
 
-	// Segment callback when -tokens is specified
+	// Set the parameters
 	var cb whisper.SegmentCallback
-	if flags.IsTokens() {
+	if lang != "" {
+		if err := context.SetLanguage(lang); err != nil {
+			return err
+		}
+	}
+	if speedup {
+		context.SetSpeedup(true)
+	}
+	if tokens {
 		cb = func(segment whisper.Segment) {
-			fmt.Fprintf(flags.Output(), "%02d [%6s->%6s] ", segment.Num, segment.Start.Truncate(time.Millisecond), segment.End.Truncate(time.Millisecond))
+			fmt.Printf("%02d [%6s->%6s] ", segment.Num, segment.Start.Truncate(time.Millisecond), segment.End.Truncate(time.Millisecond))
 			for _, token := range segment.Tokens {
-				if flags.IsColorize() && context.IsText(token) {
+				fmt.Printf("%q ", token.Text)
-					fmt.Fprint(flags.Output(), Colorize(token.Text, int(token.P*24.0)), " ")
-				} else {
-					fmt.Fprint(flags.Output(), token.Text, " ")
 			}
-			}
+			fmt.Println("")
-			fmt.Fprintln(flags.Output(), "")
-			fmt.Fprintln(flags.Output(), "")
 		}
 	}
 
 	// Process the data
-	fmt.Fprintf(flags.Output(), "  ...processing %q\n", path)
-	context.ResetTimings()
 	if err := context.Process(data, cb); err != nil {
 		return err
 	}
 
-	context.PrintTimings()
-
 	// Print out the results
-	switch {
-	case flags.GetOut() == "srt":
-		return OutputSRT(os.Stdout, context)
-	case flags.GetOut() == "none":
-		return nil
-	default:
-		return Output(os.Stdout, context, flags.IsColorize())
-	}
-}
-
-// Output text as SRT file
-func OutputSRT(w io.Writer, context whisper.Context) error {
-	n := 1
 	for {
 		segment, err := context.NextSegment()
 		if err == io.EOF {
-			return nil
+			break
 		} else if err != nil {
 			return err
 		}
-		fmt.Fprintln(w, n)
+		fmt.Printf("[%6s->%6s] %s\n", segment.Start.Truncate(time.Millisecond), segment.End.Truncate(time.Millisecond), segment.Text)
-		fmt.Fprintln(w, srtTimestamp(segment.Start), " --> ", srtTimestamp(segment.End))
-		fmt.Fprintln(w, segment.Text)
-		fmt.Fprintln(w, "")
-		n++
-	}
 	}
 
-// Output text to terminal
+	// Return success
-func Output(w io.Writer, context whisper.Context, colorize bool) error {
-	for {
-		segment, err := context.NextSegment()
-		if err == io.EOF {
 	return nil
-		} else if err != nil {
-			return err
-		}
-		fmt.Fprintf(w, "[%6s->%6s]", segment.Start.Truncate(time.Millisecond), segment.End.Truncate(time.Millisecond))
-		if colorize {
-			for _, token := range segment.Tokens {
-				if !context.IsText(token) {
-					continue
-				}
-				fmt.Fprint(w, " ", Colorize(token.Text, int(token.P*24.0)))
-			}
-			fmt.Fprint(w, "\n")
-		} else {
-			fmt.Fprintln(w, " ", segment.Text)
-		}
-	}
-}
-
-// Return srtTimestamp
-func srtTimestamp(t time.Duration) string {
-	return fmt.Sprintf("%02d:%02d:%02d,%03d", t/time.Hour, (t%time.Hour)/time.Minute, (t%time.Minute)/time.Second, (t%time.Second)/time.Millisecond)
 }

bindings/go/go.sum

@@ -1,23 +0,0 @@
-github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
-github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
-github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
-github.com/go-audio/audio v1.0.0 h1:zS9vebldgbQqktK4H0lUqWrG8P0NxCJVqcj7ZpNnwd4=
-github.com/go-audio/audio v1.0.0/go.mod h1:6uAu0+H2lHkwdGsAY+j2wHPNPpPoeg5AaEFh9FlA+Zs=
-github.com/go-audio/riff v1.0.0 h1:d8iCGbDvox9BfLagY94fBynxSPHO80LmZCaOsmKxokA=
-github.com/go-audio/riff v1.0.0/go.mod h1:l3cQwc85y79NQFCRB7TiPoNiaijp6q8Z0Uv38rVG498=
-github.com/go-audio/wav v1.1.0 h1:jQgLtbqBzY7G+BM8fXF7AHUk1uHUviWS4X39d5rsL2g=
-github.com/go-audio/wav v1.1.0/go.mod h1:mpe9qfwbScEbkd8uybLuIpTgHyrISw/OTuvjUW2iGtE=
-github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
-github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
-github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+wExME=
-github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSSt89Yw=
-github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
-github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
-github.com/stretchr/testify v1.8.0/go.mod h1:yNjHg4UonilssWZ8iaSj1OCr/vHnekPRkoO+kdMU+MU=
-github.com/stretchr/testify v1.8.1 h1:w7B6lhMri9wdJUVmEZPGGhZzrYTPvgJArz7wNPgYKsk=
-github.com/stretchr/testify v1.8.1/go.mod h1:w2LPCIKwWwSfY2zedu0+kehJoqGctiVI29o6fzry7u4=
-gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
-gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
-gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
-gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
-gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=

bindings/go/params.go

@@ -1,5 +1,8 @@
 package whisper
 
+// This file defines the whisper_token, whisper_token_data and whisper_full_params
+// structures, which are used by the whisper_full() function.
+
 import (
 	"fmt"
 )
@@ -47,12 +50,7 @@ func (p *Params) SetSpeedup(v bool) {
 	p.speed_up = toBool(v)
 }
 
-// Set language id
 func (p *Params) SetLanguage(lang int) error {
-	if lang == -1 {
-		p.language = nil
-		return nil
-	}
 	str := C.whisper_lang_str(C.int(lang))
 	if str == nil {
 		return ErrInvalidLanguage
@@ -62,7 +60,6 @@ func (p *Params) SetLanguage(lang int) error {
 	return nil
 }
 
-// Get language id
 func (p *Params) Language() int {
 	if p.language == nil {
 		return -1
@@ -70,46 +67,18 @@ func (p *Params) Language() int {
 	return int(C.whisper_lang_id(p.language))
 }
 
-// Threads available
-func (p *Params) Threads() int {
-	return int(p.n_threads)
-}
-
-// Set number of threads to use
 func (p *Params) SetThreads(threads int) {
 	p.n_threads = C.int(threads)
 }
 
-// Set start offset in ms
 func (p *Params) SetOffset(offset_ms int) {
 	p.offset_ms = C.int(offset_ms)
 }
 
-// Set audio duration to process in ms
 func (p *Params) SetDuration(duration_ms int) {
 	p.duration_ms = C.int(duration_ms)
 }
 
-// Set timestamp token probability threshold (~0.01)
-func (p *Params) SetTokenThreshold(t float32) {
-	p.thold_pt = C.float(t)
-}
-
-// Set timestamp token sum probability threshold (~0.01)
-func (p *Params) SetTokenSumThreshold(t float32) {
-	p.thold_ptsum = C.float(t)
-}
-
-// Set max segment length in characters
-func (p *Params) SetMaxSegmentLength(n int) {
-	p.max_len = C.int(n)
-}
-
-// Set max tokens per segment (0 = no limit)
-func (p *Params) SetMaxTokensPerSegment(n int) {
-	p.max_tokens = C.int(n)
-}
-
 ///////////////////////////////////////////////////////////////////////////////
 // PRIVATE METHODS
 

bindings/go/pkg/whisper/consts.go

@@ -15,7 +15,6 @@ var (
 	ErrInternalAppError    = errors.New("internal application error")
 	ErrProcessingFailed    = errors.New("processing failed")
 	ErrUnsupportedLanguage = errors.New("unsupported language")
-	ErrModelNotMultilingual = errors.New("model is not multilingual")
 )
 
 ///////////////////////////////////////////////////////////////////////////////

bindings/go/pkg/whisper/context.go

@@ -1,9 +1,7 @@
 package whisper
 
 import (
-	"fmt"
 	"io"
-	"runtime"
 	"strings"
 	"time"
 
@@ -26,7 +24,7 @@ var _ Context = (*context)(nil)
 ///////////////////////////////////////////////////////////////////////////////
 // LIFECYCLE
 
-func newContext(model *model, params whisper.Params) (Context, error) {
+func NewContext(model *model, params whisper.Params) (Context, error) {
 	context := new(context)
 	context.model = model
 	context.params = params
@@ -43,13 +41,7 @@ func (context *context) SetLanguage(lang string) error {
 	if context.model.ctx == nil {
 		return ErrInternalAppError
 	}
-	if !context.model.IsMultilingual() {
+	if id := context.model.ctx.Whisper_lang_id(lang); id < 0 {
-		return ErrModelNotMultilingual
-	}
-
-	if lang == "auto" {
-		context.params.SetLanguage(-1)
-	} else if id := context.model.ctx.Whisper_lang_id(lang); id < 0 {
 		return ErrUnsupportedLanguage
 	} else if err := context.params.SetLanguage(id); err != nil {
 		return err
@@ -58,94 +50,16 @@ func (context *context) SetLanguage(lang string) error {
 	return nil
 }
 
-func (context *context) IsMultilingual() bool {
-	return context.model.IsMultilingual()
-}
-
 // Get language
 func (context *context) Language() string {
-	id := context.params.Language()
-	if id == -1 {
-		return "auto"
-	}
 	return whisper.Whisper_lang_str(context.params.Language())
 }
 
-// Set translate flag
-func (context *context) SetTranslate(v bool) {
-	context.params.SetTranslate(v)
-}
-
 // Set speedup flag
 func (context *context) SetSpeedup(v bool) {
 	context.params.SetSpeedup(v)
 }
 
-// Set number of threads to use
-func (context *context) SetThreads(v uint) {
-	context.params.SetThreads(int(v))
-}
-
-// Set time offset
-func (context *context) SetOffset(v time.Duration) {
-	context.params.SetOffset(int(v.Milliseconds()))
-}
-
-// Set duration of audio to process
-func (context *context) SetDuration(v time.Duration) {
-	context.params.SetOffset(int(v.Milliseconds()))
-}
-
-// Set timestamp token probability threshold (~0.01)
-func (context *context) SetTokenThreshold(t float32) {
-	context.params.SetTokenThreshold(t)
-}
-
-// Set timestamp token sum probability threshold (~0.01)
-func (context *context) SetTokenSumThreshold(t float32) {
-	context.params.SetTokenSumThreshold(t)
-}
-
-// Set max segment length in characters
-func (context *context) SetMaxSegmentLength(n uint) {
-	context.params.SetMaxSegmentLength(int(n))
-}
-
-// Set max tokens per segment (0 = no limit)
-func (context *context) SetMaxTokensPerSegment(n uint) {
-	context.params.SetMaxTokensPerSegment(int(n))
-}
-
-// ResetTimings resets the mode timings. Should be called before processing
-func (context *context) ResetTimings() {
-	context.model.ctx.Whisper_reset_timings()
-}
-
-// PrintTimings prints the model timings to stdout.
-func (context *context) PrintTimings() {
-	context.model.ctx.Whisper_print_timings()
-}
-
-// SystemInfo returns the system information
-func (context *context) SystemInfo() string {
-	return fmt.Sprintf("system_info: n_threads = %d / %d | %s\n",
-		context.params.Threads(),
-		runtime.NumCPU(),
-		whisper.Whisper_print_system_info(),
-	)
-}
-
-// Use mel data at offset_ms to try and auto-detect the spoken language
-// Make sure to call whisper_pcm_to_mel() or whisper_set_mel() first.
-// Returns the probabilities of all languages.
-func (context *context) WhisperLangAutoDetect(offset_ms int, n_threads int) ([]float32, error) {
-	langProbs, err := context.model.ctx.Whisper_lang_auto_detect(offset_ms, n_threads)
-	if err != nil {
-		return nil, err
-	}
-	return langProbs, nil
-}
-
 // Process new sample data and return any errors
 func (context *context) Process(data []float32, cb SegmentCallback) error {
 	if context.model.ctx == nil {
@@ -205,65 +119,6 @@ func (context *context) NextSegment() (Segment, error) {
 	return result, nil
 }
 
-// Test for text tokens
-func (context *context) IsText(t Token) bool {
-	switch {
-	case context.IsBEG(t):
-		return false
-	case context.IsSOT(t):
-		return false
-	case whisper.Token(t.Id) >= context.model.ctx.Whisper_token_eot():
-		return false
-	case context.IsPREV(t):
-		return false
-	case context.IsSOLM(t):
-		return false
-	case context.IsNOT(t):
-		return false
-	default:
-		return true
-	}
-}
-
-// Test for "begin" token
-func (context *context) IsBEG(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_beg()
-}
-
-// Test for "start of transcription" token
-func (context *context) IsSOT(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_sot()
-}
-
-// Test for "end of transcription" token
-func (context *context) IsEOT(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_eot()
-}
-
-// Test for "start of prev" token
-func (context *context) IsPREV(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_prev()
-}
-
-// Test for "start of lm" token
-func (context *context) IsSOLM(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_solm()
-}
-
-// Test for "No timestamps" token
-func (context *context) IsNOT(t Token) bool {
-	return whisper.Token(t.Id) == context.model.ctx.Whisper_token_not()
-}
-
-// Test for token associated with a specific language
-func (context *context) IsLANG(t Token, lang string) bool {
-	if id := context.model.ctx.Whisper_lang_id(lang); id >= 0 {
-		return whisper.Token(t.Id) == context.model.ctx.Whisper_token_lang(id)
-	} else {
-		return false
-	}
-}
-
 ///////////////////////////////////////////////////////////////////////////////
 // PRIVATE METHODS
 

bindings/go/pkg/whisper/interface.go

@@ -20,28 +20,15 @@ type Model interface {
 	// Return a new speech-to-text context.
 	NewContext() (Context, error)
 
-	// Return true if the model is multilingual.
-	IsMultilingual() bool
-
 	// Return all languages supported.
 	Languages() []string
 }
 
 // Context is the speach recognition context.
 type Context interface {
-	SetLanguage(string) error // Set the language to use for speech recognition, use "auto" for auto detect language.
+	SetLanguage(string) error // Set the language to use for speech recognition.
-	SetTranslate(bool)        // Set translate flag
-	IsMultilingual() bool     // Return true if the model is multilingual.
 	Language() string         // Get language
-
-	SetOffset(time.Duration)      // Set offset
-	SetDuration(time.Duration)    // Set duration
-	SetThreads(uint)              // Set number of threads to use
 	SetSpeedup(bool)          // Set speedup flag
-	SetTokenThreshold(float32)    // Set timestamp token probability threshold
-	SetTokenSumThreshold(float32) // Set timestamp token sum probability threshold
-	SetMaxSegmentLength(uint)     // Set max segment length in characters
-	SetMaxTokensPerSegment(uint)  // Set max tokens per segment (0 = no limit)
 
 	// Process mono audio data and return any errors.
 	// If defined, newly generated segments are passed to the
@@ -51,21 +38,6 @@ type Context interface {
 	// After process is called, return segments until the end of the stream
 	// is reached, when io.EOF is returned.
 	NextSegment() (Segment, error)
-
-	IsBEG(Token) bool          // Test for "begin" token
-	IsSOT(Token) bool          // Test for "start of transcription" token
-	IsEOT(Token) bool          // Test for "end of transcription" token
-	IsPREV(Token) bool         // Test for "start of prev" token
-	IsSOLM(Token) bool         // Test for "start of lm" token
-	IsNOT(Token) bool          // Test for "No timestamps" token
-	IsLANG(Token, string) bool // Test for token associated with a specific language
-	IsText(Token) bool         // Test for text token
-
-	// Timings
-	PrintTimings()
-	ResetTimings()
-
-	SystemInfo() string
 }
 
 // Segment is the text result of a speech recognition.

bindings/go/pkg/whisper/model.go

@@ -23,7 +23,7 @@ var _ Model = (*model)(nil)
 ///////////////////////////////////////////////////////////////////////////////
 // LIFECYCLE
 
-func New(path string) (Model, error) {
+func New(path string) (*model, error) {
 	model := new(model)
 	if _, err := os.Stat(path); err != nil {
 		return nil, err
@@ -64,11 +64,6 @@ func (model *model) String() string {
 ///////////////////////////////////////////////////////////////////////////////
 // PUBLIC METHODS
 
-// Return true if model is multilingual (language and translation options are supported)
-func (model *model) IsMultilingual() bool {
-	return model.ctx.Whisper_is_multilingual() != 0
-}
-
 // Return all recognized languages. Initially it is set to auto-detect
 func (model *model) Languages() []string {
 	result := make([]string, 0, whisper.Whisper_lang_max_id())
@@ -96,5 +91,5 @@ func (model *model) NewContext() (Context, error) {
 	params.SetThreads(runtime.NumCPU())
 
 	// Return new context
-	return newContext(model, params)
+	return NewContext(model, params)
 }

bindings/go/whisper.go

@@ -9,7 +9,8 @@ import (
 // CGO
 
 /*
-#cgo LDFLAGS: -lwhisper -lm -lstdc++
+#cgo CFLAGS: -I${SRCDIR}/../..
+#cgo LDFLAGS: -L${SRCDIR}/build -lwhisper -lm -lstdc++
 #cgo darwin LDFLAGS: -framework Accelerate
 #include <whisper.h>
 #include <stdlib.h>
@@ -91,7 +92,7 @@ var (
 func Whisper_init(path string) *Context {
 	cPath := C.CString(path)
 	defer C.free(unsafe.Pointer(cPath))
-	if ctx := C.whisper_init_from_file(cPath); ctx != nil {
+	if ctx := C.whisper_init(cPath); ctx != nil {
 		return (*Context)(ctx)
 	} else {
 		return nil
@@ -147,6 +148,16 @@ func (ctx *Context) Whisper_decode(tokens []Token, past, threads int) error {
 	}
 }
 
+// whisper_sample_best() returns the token with the highest probability
+func (ctx *Context) Whisper_sample_best() TokenData {
+	return TokenData(C.whisper_sample_best((*C.struct_whisper_context)(ctx)))
+}
+
+// whisper_sample_timestamp() returns the most probable timestamp token
+func (ctx *Context) Whisper_sample_timestamp(is_initial bool) TokenData {
+	return TokenData(C.whisper_sample_timestamp((*C.struct_whisper_context)(ctx), C.bool(is_initial)))
+}
+
 // Convert the provided text into tokens. The tokens pointer must be large enough to hold the resulting tokens.
 // Returns the number of tokens on success
 func (ctx *Context) Whisper_tokenize(text string, tokens []Token) (int, error) {
@@ -160,10 +171,6 @@ func (ctx *Context) Whisper_tokenize(text string, tokens []Token) (int, error) {
 }
 
 // Return the id of the specified language, returns -1 if not found
-// Examples:
-//
-//	"de" -> 2
-//	"german" -> 2
 func (ctx *Context) Whisper_lang_id(lang string) int {
 	return int(C.whisper_lang_id(C.CString(lang)))
 }
@@ -204,10 +211,6 @@ func (ctx *Context) Whisper_n_text_ctx() int {
 	return int(C.whisper_n_text_ctx((*C.struct_whisper_context)(ctx)))
 }
 
-func (ctx *Context) Whisper_n_audio_ctx() int {
-	return int(C.whisper_n_audio_ctx((*C.struct_whisper_context)(ctx)))
-}
-
 func (ctx *Context) Whisper_is_multilingual() int {
 	return int(C.whisper_is_multilingual((*C.struct_whisper_context)(ctx)))
 }

bindings/go/whisper_test.go

@@ -50,10 +50,7 @@ func Test_Whisper_001(t *testing.T) {
 	ctx := whisper.Whisper_init(ModelPath)
 	assert.NotNil(ctx)
 	defer ctx.Whisper_free()
-	params := ctx.Whisper_full_default_params(whisper.SAMPLING_GREEDY)
+	assert.NoError(ctx.Whisper_full(ctx.Whisper_full_default_params(whisper.SAMPLING_GREEDY), buf.AsFloat32Buffer().Data, nil, nil))
-	data := buf.AsFloat32Buffer().Data
-	err = ctx.Whisper_full(params, data, nil, nil)
-	assert.NoError(err)
 
 	// Print out tokens
 	num_segments := ctx.Whisper_full_n_segments()

bindings/javascript/emscripten.cpp

@@ -20,7 +20,7 @@ struct whisper_context * g_context;
 EMSCRIPTEN_BINDINGS(whisper) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         if (g_context == nullptr) {
-            g_context = whisper_init_from_file(path_model.c_str());
+            g_context = whisper_init(path_model.c_str());
             if (g_context != nullptr) {
                 return true;
             } else {

bindings/javascript/package.json

@@ -1,6 +1,6 @@
 {
   "name": "whisper.cpp",
-  "version": "1.2.0",
+  "version": "1.0.4",
   "description": "Whisper speech recognition",
   "main": "whisper.js",
   "scripts": {

cmake/DefaultTargetOptions.cmake

@@ -1,17 +0,0 @@
-# Set the default compile features and properties for a target.
-
-if (NOT TARGET)
-    message(FATAL_ERROR "TARGET not set before including DefaultTargetOptions")
-endif()
-
-target_compile_features(${TARGET}
-    PRIVATE
-        cxx_std_11
-    )
-
-set_target_properties(${TARGET}
-    PROPERTIES
-        EXPORT_COMPILE_COMMANDS ON
-        RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin"
-        INSTALL_RPATH "${CMAKE_INSTALL_PREFIX}/lib"
-)

examples/CMakeLists.txt

@@ -24,8 +24,6 @@ if (EMSCRIPTEN)
     add_subdirectory(command.wasm)
     add_subdirectory(talk.wasm)
     add_subdirectory(bench.wasm)
-elseif(CMAKE_JS_VERSION)
-    add_subdirectory(addon.node)
 else()
     add_subdirectory(main)
     add_subdirectory(stream)

examples/addon.node/.gitignore

@@ -1,3 +0,0 @@
-.idea
-node_modules
-build

examples/addon.node/CMakeLists.txt

@@ -1,26 +0,0 @@
-set(TARGET whisper-addon)
-
-# Base settings
-#==================================================================
-# env var supported by cmake-js
-add_definitions(-DNAPI_VERSION=4)
-include_directories(${CMAKE_JS_INC})
-#==================================================================
-
-add_library(${TARGET} SHARED ${CMAKE_JS_SRC} addon.cpp)
-set_target_properties(${TARGET} PROPERTIES PREFIX "" SUFFIX ".node")
-
-include(DefaultTargetOptions)
-
-# Include N-API wrappers
-#==================================================================
-execute_process(COMMAND node -p "require('node-addon-api').include"
-        WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
-        OUTPUT_VARIABLE NODE_ADDON_API_DIR
-        )
-string(REPLACE "\n" "" NODE_ADDON_API_DIR ${NODE_ADDON_API_DIR})
-string(REPLACE "\"" "" NODE_ADDON_API_DIR ${NODE_ADDON_API_DIR})
-target_include_directories(${TARGET} PRIVATE ${NODE_ADDON_API_DIR})
-#==================================================================
-
-target_link_libraries(${TARGET} ${CMAKE_JS_LIB} whisper ${CMAKE_THREAD_LIBS_INIT})

examples/addon.node/README.md

@@ -1,37 +0,0 @@
-# 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.
-
-## Install
-
-```shell
-npm install
-```
-
-## Compile
-
-Make sure it is in the project root directory and compiled with make-js.
-
-```shell
-npx cmake-js compile -T whisper-addon
-```
-
-For Electron addon and cmake-js options, you can see [cmake-js](https://github.com/cmake-js/cmake-js) and make very few configuration changes.
-
-> Such as appointing special cmake path:
-> ```shell
-> npx cmake-js compile -c 'xxx/cmake' -T whisper-addon
-> ```
-
-## Run
-
-```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.
-
-Other parameters can also be specified in the node environment.

examples/addon.node/addon.cpp

@@ -1,421 +0,0 @@
-#include <string>
-#include <thread>
-#include <vector>
-#include <cmath>
-
-#include "napi.h"
-
-#define DR_WAV_IMPLEMENTATION
-#include "dr_wav.h"
-
-#include "whisper.h"
-
-struct whisper_params {
-    int32_t n_threads    = std::min(4, (int32_t) std::thread::hardware_concurrency());
-    int32_t n_processors = 1;
-    int32_t offset_t_ms  = 0;
-    int32_t offset_n     = 0;
-    int32_t duration_ms  = 0;
-    int32_t max_context  = -1;
-    int32_t max_len      = 0;
-    int32_t best_of      = 5;
-    int32_t beam_size    = -1;
-
-    float word_thold    = 0.01f;
-    float entropy_thold = 2.4f;
-    float logprob_thold = -1.0f;
-
-    bool speed_up       = false;
-    bool translate      = false;
-    bool diarize        = false;
-    bool output_txt     = false;
-    bool output_vtt     = false;
-    bool output_srt     = false;
-    bool output_wts     = false;
-    bool output_csv     = false;
-    bool print_special  = false;
-    bool print_colors   = false;
-    bool print_progress = false;
-    bool no_timestamps  = false;
-
-    std::string language = "en";
-    std::string prompt;
-    std::string model    = "../../ggml-large.bin";
-
-    std::vector<std::string> fname_inp = {};
-    std::vector<std::string> fname_outp = {};
-};
-
-struct whisper_print_user_data {
-    const whisper_params * params;
-
-    const std::vector<std::vector<float>> * pcmf32s;
-};
-
-//  500 -> 00:05.000
-// 6000 -> 01:00.000
-std::string to_timestamp(int64_t t, bool comma = false) {
-    int64_t msec = t * 10;
-    int64_t hr = msec / (1000 * 60 * 60);
-    msec = msec - hr * (1000 * 60 * 60);
-    int64_t min = msec / (1000 * 60);
-    msec = msec - min * (1000 * 60);
-    int64_t sec = msec / 1000;
-    msec = msec - sec * 1000;
-
-    char buf[32];
-    snprintf(buf, sizeof(buf), "%02d:%02d:%02d%s%03d", (int) hr, (int) min, (int) sec, comma ? "," : ".", (int) msec);
-
-    return std::string(buf);
-}
-
-int timestamp_to_sample(int64_t t, int n_samples) {
-    return std::max(0, std::min((int) n_samples - 1, (int) ((t*WHISPER_SAMPLE_RATE)/100)));
-}
-
-void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, void * user_data) {
-    const auto & params  = *((whisper_print_user_data *) user_data)->params;
-    const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
-
-    const int n_segments = whisper_full_n_segments(ctx);
-
-    std::string speaker = "";
-
-    int64_t t0;
-    int64_t t1;
-
-    // print the last n_new segments
-    const int s0 = n_segments - n_new;
-
-    if (s0 == 0) {
-        printf("\n");
-    }
-
-    for (int i = s0; i < n_segments; i++) {
-        if (!params.no_timestamps || params.diarize) {
-            t0 = whisper_full_get_segment_t0(ctx, i);
-            t1 = whisper_full_get_segment_t1(ctx, i);
-        }
-
-        if (!params.no_timestamps) {
-            printf("[%s --> %s]  ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
-        }
-
-        if (params.diarize && pcmf32s.size() == 2) {
-            const int64_t n_samples = pcmf32s[0].size();
-
-            const int64_t is0 = timestamp_to_sample(t0, n_samples);
-            const int64_t is1 = timestamp_to_sample(t1, n_samples);
-
-            double energy0 = 0.0f;
-            double energy1 = 0.0f;
-
-            for (int64_t j = is0; j < is1; j++) {
-                energy0 += fabs(pcmf32s[0][j]);
-                energy1 += fabs(pcmf32s[1][j]);
-            }
-
-            if (energy0 > 1.1*energy1) {
-                speaker = "(speaker 0)";
-            } else if (energy1 > 1.1*energy0) {
-                speaker = "(speaker 1)";
-            } else {
-                speaker = "(speaker ?)";
-            }
-
-            //printf("is0 = %lld, is1 = %lld, energy0 = %f, energy1 = %f, %s\n", is0, is1, energy0, energy1, speaker.c_str());
-        }
-
-        // colorful print bug
-        //
-        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) {
-            printf("\n");
-        }
-
-        fflush(stdout);
-    }
-}
-
-int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
-
-    if (params.fname_inp.empty()) {
-        fprintf(stderr, "error: no input files specified\n");
-        return 2;
-    }
-
-    if (params.language != "auto" && whisper_lang_id(params.language.c_str()) == -1) {
-        fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
-        exit(0);
-    }
-
-    // whisper init
-
-    struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
-
-    if (ctx == nullptr) {
-        fprintf(stderr, "error: failed to initialize whisper context\n");
-        return 3;
-    }
-
-    // initial prompt
-    std::vector<whisper_token> prompt_tokens;
-
-    if (!params.prompt.empty()) {
-        prompt_tokens.resize(1024);
-        prompt_tokens.resize(whisper_tokenize(ctx, params.prompt.c_str(), prompt_tokens.data(), prompt_tokens.size()));
-
-        fprintf(stderr, "\n");
-        fprintf(stderr, "initial prompt: '%s'\n", params.prompt.c_str());
-        fprintf(stderr, "initial tokens: [ ");
-        for (int i = 0; i < (int) prompt_tokens.size(); ++i) {
-            fprintf(stderr, "%d ", prompt_tokens[i]);
-        }
-        fprintf(stderr, "]\n");
-    }
-
-    for (int f = 0; f < (int) params.fname_inp.size(); ++f) {
-        const auto fname_inp = params.fname_inp[f];
-        const auto fname_outp = f < (int)params.fname_outp.size() && !params.fname_outp[f].empty() ? params.fname_outp[f] : params.fname_inp[f];
-
-        std::vector<float> pcmf32; // mono-channel F32 PCM
-        std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
-
-        // WAV input
-        {
-            drwav wav;
-            std::vector<uint8_t> wav_data; // used for pipe input from stdin
-
-            if (fname_inp == "-") {
-                {
-                    uint8_t buf[1024];
-                    while (true)
-                    {
-                        const size_t n = fread(buf, 1, sizeof(buf), stdin);
-                        if (n == 0) {
-                            break;
-                        }
-                        wav_data.insert(wav_data.end(), buf, buf + n);
-                    }
-                }
-
-                if (drwav_init_memory(&wav, wav_data.data(), wav_data.size(), nullptr) == false) {
-                    fprintf(stderr, "error: failed to open WAV file from stdin\n");
-                    return 4;
-                }
-
-                fprintf(stderr, "%s: read %zu bytes from stdin\n", __func__, wav_data.size());
-            }
-            else if (drwav_init_file(&wav, fname_inp.c_str(), nullptr) == false) {
-                fprintf(stderr, "error: failed to open '%s' as WAV file\n", fname_inp.c_str());
-                return 5;
-            }
-
-           if (wav.channels != 1 && wav.channels != 2) {
-               fprintf(stderr, "error: WAV file '%s' must be mono or stereo\n", fname_inp.c_str());
-               return 6;
-           }
-
-           if (params.diarize && wav.channels != 2 && params.no_timestamps == false) {
-               fprintf(stderr, "error: WAV file '%s' must be stereo for diarization and timestamps have to be enabled\n", fname_inp.c_str());
-               return 6;
-           }
-
-           if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
-               fprintf(stderr, "error: WAV file '%s' must be %i kHz\n", fname_inp.c_str(), WHISPER_SAMPLE_RATE/1000);
-               return 8;
-           }
-
-           if (wav.bitsPerSample != 16) {
-               fprintf(stderr, "error: WAV file '%s' must be 16-bit\n", fname_inp.c_str());
-               return 9;
-           }
-
-            const uint64_t n = wav_data.empty() ? wav.totalPCMFrameCount : wav_data.size()/(wav.channels*wav.bitsPerSample/8);
-
-            std::vector<int16_t> pcm16;
-            pcm16.resize(n*wav.channels);
-            drwav_read_pcm_frames_s16(&wav, n, pcm16.data());
-            drwav_uninit(&wav);
-
-            // convert to mono, float
-            pcmf32.resize(n);
-            if (wav.channels == 1) {
-                for (uint64_t i = 0; i < n; i++) {
-                    pcmf32[i] = float(pcm16[i])/32768.0f;
-                }
-            } else {
-                for (uint64_t i = 0; i < n; i++) {
-                    pcmf32[i] = float(pcm16[2*i] + pcm16[2*i + 1])/65536.0f;
-                }
-            }
-
-            if (params.diarize) {
-                // convert to stereo, float
-                pcmf32s.resize(2);
-
-                pcmf32s[0].resize(n);
-                pcmf32s[1].resize(n);
-                for (uint64_t i = 0; i < n; i++) {
-                    pcmf32s[0][i] = float(pcm16[2*i])/32768.0f;
-                    pcmf32s[1][i] = float(pcm16[2*i + 1])/32768.0f;
-                }
-            }
-        }
-
-        // print system information
-        {
-            fprintf(stderr, "\n");
-            fprintf(stderr, "system_info: n_threads = %d / %d | %s\n",
-                    params.n_threads*params.n_processors, std::thread::hardware_concurrency(), whisper_print_system_info());
-        }
-
-        // print some info about the processing
-        {
-            fprintf(stderr, "\n");
-            if (!whisper_is_multilingual(ctx)) {
-                if (params.language != "en" || params.translate) {
-                    params.language = "en";
-                    params.translate = false;
-                    fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
-                }
-            }
-            fprintf(stderr, "%s: processing '%s' (%d samples, %.1f sec), %d threads, %d processors, lang = %s, task = %s, timestamps = %d ...\n",
-                    __func__, fname_inp.c_str(), int(pcmf32.size()), float(pcmf32.size())/WHISPER_SAMPLE_RATE,
-                    params.n_threads, params.n_processors,
-                    params.language.c_str(),
-                    params.translate ? "translate" : "transcribe",
-                    params.no_timestamps ? 0 : 1);
-
-            fprintf(stderr, "\n");
-        }
-
-        // run the inference
-        {
-            whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
-
-            wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
-
-            wparams.print_realtime   = false;
-            wparams.print_progress   = params.print_progress;
-            wparams.print_timestamps = !params.no_timestamps;
-            wparams.print_special    = params.print_special;
-            wparams.translate        = params.translate;
-            wparams.language         = params.language.c_str();
-            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;
-            wparams.duration_ms      = params.duration_ms;
-
-            wparams.token_timestamps = params.output_wts || params.max_len > 0;
-            wparams.thold_pt         = params.word_thold;
-            wparams.entropy_thold    = params.entropy_thold;
-            wparams.logprob_thold    = params.logprob_thold;
-            wparams.max_len          = params.output_wts && params.max_len == 0 ? 60 : params.max_len;
-
-            wparams.speed_up         = params.speed_up;
-
-            wparams.greedy.best_of        = params.best_of;
-            wparams.beam_search.beam_size = params.beam_size;
-
-            wparams.prompt_tokens     = prompt_tokens.empty() ? nullptr : prompt_tokens.data();
-            wparams.prompt_n_tokens   = prompt_tokens.empty() ? 0       : prompt_tokens.size();
-
-            whisper_print_user_data user_data = { &params, &pcmf32s };
-
-            // this callback is called on each new segment
-            if (!wparams.print_realtime) {
-                wparams.new_segment_callback           = whisper_print_segment_callback;
-                wparams.new_segment_callback_user_data = &user_data;
-            }
-
-            // example for abort mechanism
-            // in this example, 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*/, void * user_data) {
-                    bool is_aborted = *(bool*)user_data;
-                    return !is_aborted;
-                };
-                wparams.encoder_begin_callback_user_data = &is_aborted;
-            }
-
-            if (whisper_full_parallel(ctx, wparams, pcmf32.data(), pcmf32.size(), params.n_processors) != 0) {
-                fprintf(stderr, "failed to process audio\n");
-                return 10;
-            }
-        }
-    }
-
-    const int n_segments = whisper_full_n_segments(ctx);
-    result.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, true));
-        result[i].emplace_back(to_timestamp(t1, true));
-        result[i].emplace_back(text);
-    }
-
-    whisper_print_timings(ctx);
-    whisper_free(ctx);
-
-    return 0;
-}
-
-Napi::Object whisper(const Napi::CallbackInfo& info) {
-    Napi::Env env = info.Env();
-    if (info.Length() <= 0 || !info[0].IsObject()) {
-        Napi::TypeError::New(env, "object expected").ThrowAsJavaScriptException();
-    }
-    whisper_params params;
-    std::vector<std::vector<std::string>> result;
-
-    Napi::Object whisper_params = info[0].As<Napi::Object>();
-    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>();
-
-    params.language = language;
-    params.model = model;
-    params.fname_inp.emplace_back(input);
-
-    // run model
-    run(params, result);
-
-    fprintf(stderr, "RESULT:\n");
-    for (auto sentence:result) {
-        fprintf(stderr, "t0: %s, t1: %s, content: %s \n",
-                sentence[0].c_str(), sentence[1].c_str(), sentence[2].c_str());
-    }
-
-    Napi::Object res = Napi::Array::New(env, result.size());
-    for (u_int32_t i = 0; i < result.size(); ++i) {
-        Napi::Object tmp = Napi::Array::New(env, 3);
-        for (u_int32_t j = 0; j < 3; ++j) {
-            tmp[j] = Napi::String::New(env, result[i][j]);
-        }
-        res[i] = tmp;
-    }
-
-    return res;
-}
-
-
-Napi::Object Init(Napi::Env env, Napi::Object exports) {
-    exports.Set(
-            Napi::String::New(env, "whisper"),
-            Napi::Function::New(env, whisper)
-    );
-    return exports;
-}
-
-NODE_API_MODULE(whisper, Init);

examples/addon.node/index.js

@@ -1,27 +0,0 @@
-const path = require('path');
-const { whisper } = require(path.join(__dirname, '../../build/Release/whisper-addon'));
-
-const whisperParams = {
-    language: 'en',
-    model: path.join(__dirname, '../../models/ggml-base.en.bin'),
-    fname_inp: '',
-};
-
-const arguments = process.argv.slice(2);
-const params = Object.fromEntries(
-    arguments.reduce((pre, item) => {
-        if (item.startsWith("--")) {
-            return [...pre, item.slice(2).split("=")];
-        }
-        return pre;
-    }, []),
-);
-
-for (const key in params) {
-    if (whisperParams.hasOwnProperty(key)) {
-        whisperParams[key] = params[key];
-    }
-}
-
-console.log('whisperParams =', whisperParams);
-console.log(whisper(whisperParams));

examples/addon.node/package.json

@@ -1,12 +0,0 @@
-{
-  "name": "whisper-addon",
-  "version": "0.0.0",
-  "description": "",
-  "main": "index.js",
-  "author": "Qanhe Chen",
-  "license": "MIT",
-  "devDependencies": {
-    "cmake-js": "^7.1.1",
-    "node-addon-api": "^5.0.0"
-  }
-}

examples/bench.wasm/CMakeLists.txt

@@ -8,8 +8,6 @@ add_executable(${TARGET}
     emscripten.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE
     whisper
     )

examples/bench.wasm/emscripten.cpp

@@ -28,11 +28,6 @@ void bench_main(size_t index) {
         return;
     }
 
-    {
-        fprintf(stderr, "\n");
-        fprintf(stderr, "system_info: n_threads = %d / %d | %s\n", n_threads, std::thread::hardware_concurrency(), whisper_print_system_info());
-    }
-
     if (int ret = whisper_encode(ctx, 0, n_threads) != 0) {
         fprintf(stderr, "error: failed to encode model: %d\n", ret);
         return;
@@ -57,7 +52,7 @@ EMSCRIPTEN_BINDINGS(bench) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         for (size_t i = 0; i < g_contexts.size(); ++i) {
             if (g_contexts[i] == nullptr) {
-                g_contexts[i] = whisper_init_from_file(path_model.c_str());
+                g_contexts[i] = whisper_init(path_model.c_str());
                 if (g_contexts[i] != nullptr) {
                     if (g_worker.joinable()) {
                         g_worker.join();

examples/bench/CMakeLists.txt

@@ -1,6 +1,3 @@
 set(TARGET bench)
 add_executable(${TARGET} bench.cpp)
-
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE whisper ${CMAKE_THREAD_LIBS_INIT})

examples/bench/bench.cpp

@@ -7,7 +7,6 @@
 // command-line parameters
 struct whisper_params {
     int32_t n_threads = std::min(4, (int32_t) std::thread::hardware_concurrency());
-    int32_t what = 0; // what to benchmark: 0 - whisper ecoder, 1 - memcpy, 2 - ggml_mul_mat
 
     std::string model = "models/ggml-base.en.bin";
 };
@@ -24,7 +23,6 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
         }
         else if (arg == "-t" || arg == "--threads") { params.n_threads = std::stoi(argv[++i]); }
         else if (arg == "-m" || arg == "--model")   { params.model     = argv[++i]; }
-        else if (arg == "-w" || arg == "--what")    { params.what     = atoi(argv[++i]); }
         else {
             fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
             whisper_print_usage(argc, argv, params);
@@ -43,17 +41,19 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
     fprintf(stderr, "  -h,       --help        [default] show this help message and exit\n");
     fprintf(stderr, "  -t N,     --threads N   [%-7d] number of threads to use during computation\n", params.n_threads);
     fprintf(stderr, "  -m FNAME, --model FNAME [%-7s] model path\n",                                  params.model.c_str());
-    fprintf(stderr, "  -w N,     --what N      [%-7d] what to benchmark:\n",                          params.what);
-    fprintf(stderr, "                           %-7s  0 - whisper encoder\n",                         "");
-    fprintf(stderr, "                           %-7s  1 - memcpy\n",                                  "");
-    fprintf(stderr, "                           %-7s  2 - ggml_mul_mat\n",                            "");
     fprintf(stderr, "\n");
 }
 
-int whisper_bench_encoder(const whisper_params & params) {
+int main(int argc, char ** argv) {
+    whisper_params params;
+
+    if (whisper_params_parse(argc, argv, params) == false) {
+        return 1;
+    }
+
     // whisper init
 
-    struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
+    struct whisper_context * ctx = whisper_init(params.model.c_str());
 
     {
         fprintf(stderr, "\n");
@@ -92,22 +92,3 @@ int whisper_bench_encoder(const whisper_params & params) {
 
     return 0;
 }
-
-int main(int argc, char ** argv) {
-    whisper_params params;
-
-    if (whisper_params_parse(argc, argv, params) == false) {
-        return 1;
-    }
-
-    int ret = -1;
-
-    switch (params.what) {
-        case 0: ret = whisper_bench_encoder(params);                break;
-        case 1: ret = whisper_bench_memcpy(params.n_threads);       break;
-        case 2: ret = whisper_bench_ggml_mul_mat(params.n_threads); break;
-        default: fprintf(stderr, "error: unknown benchmark: %d\n", params.what); break;
-    }
-
-    return ret;
-}

examples/command.wasm/CMakeLists.txt

@@ -8,8 +8,6 @@ add_executable(${TARGET}
     emscripten.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE
     whisper
     )

examples/command.wasm/emscripten.cpp

@@ -324,7 +324,7 @@ EMSCRIPTEN_BINDINGS(command) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         for (size_t i = 0; i < g_contexts.size(); ++i) {
             if (g_contexts[i] == nullptr) {
-                g_contexts[i] = whisper_init_from_file(path_model.c_str());
+                g_contexts[i] = whisper_init(path_model.c_str());
                 if (g_contexts[i] != nullptr) {
                     g_running = true;
                     if (g_worker.joinable()) {

examples/command/CMakeLists.txt

@@ -2,9 +2,6 @@ if (WHISPER_SUPPORT_SDL2)
     # command
     set(TARGET command)
     add_executable(${TARGET} command.cpp)
-
-    include(DefaultTargetOptions)
-
     target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
     target_link_libraries(${TARGET} PRIVATE whisper ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
 endif ()

examples/command/README.md

@@ -9,19 +9,7 @@ More info is available in [issue #171](https://github.com/ggerganov/whisper.cpp/
 
 # On Raspberry Pi, use tiny or base models + "-ac 768" for better performance
 ./command -m ./models/ggml-tiny.en.bin -ac 768 -t 3 -c 0
-```
 
-https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
-
-Web version: [examples/command.wasm](/examples/command.wasm)
-
-## Guided mode
-
-"Guided mode" allows you to specify a list of commands (i.e. strings) and the transcription will be guided to classify your command into one from the list. This can be useful in situations where a device is listening only for a small subset of commands.
-
-Initial tests show that this approach might be extremely efficient in terms of performance, since it integrates very well with the "partial Encoder" idea from #137.
-
-```bash
 # Run in guided mode, the list of allowed commands is in commands.txt
 ./command -m ./models/ggml-base.en.bin -cmd ./examples/command/commands.txt
 
@@ -29,8 +17,9 @@ Initial tests show that this approach might be extremely efficient in terms of p
 ./command -m ./models/ggml-tiny.en.bin -cmd ./examples/command/commands.txt -ac 128 -t 3 -c 0
 ```
 
-https://user-images.githubusercontent.com/1991296/207435352-8fc4ed3f-bde5-4555-9b8b-aeeb76bee969.mp4
+https://user-images.githubusercontent.com/1991296/204038393-2f846eae-c255-4099-a76d-5735c25c49da.mp4
 
+Web version: [examples/command.wasm](/examples/command.wasm)
 
 ## Building
 

examples/command/command.cpp

@@ -11,7 +11,6 @@
 #include <SDL.h>
 #include <SDL_audio.h>
 
-#include <sstream>
 #include <cassert>
 #include <cstdio>
 #include <fstream>
@@ -26,7 +25,7 @@
 struct whisper_params {
     int32_t n_threads  = std::min(4, (int32_t) std::thread::hardware_concurrency());
     int32_t prompt_ms  = 5000;
-    int32_t command_ms = 8000;
+    int32_t command_ms = 4000;
     int32_t capture_id = -1;
     int32_t max_tokens = 32;
     int32_t audio_ctx  = 0;
@@ -44,7 +43,6 @@ struct whisper_params {
     std::string model     = "models/ggml-base.en.bin";
     std::string fname_out;
     std::string commands;
-    std::string prompt;
 };
 
 void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
@@ -73,7 +71,6 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
         else if (arg == "-m"   || arg == "--model")         { params.model         = argv[++i]; }
         else if (arg == "-f"   || arg == "--file")          { params.fname_out     = argv[++i]; }
         else if (arg == "-cmd" || arg == "--commands")      { params.commands      = argv[++i]; }
-        else if (arg == "-p"   || arg == "--prompt")        { params.prompt        = argv[++i]; }
         else {
             fprintf(stderr, "error: unknown argument: %s\n", arg.c_str());
             whisper_print_usage(argc, argv, params);
@@ -106,7 +103,6 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
     fprintf(stderr, "  -m FNAME,   --model FNAME    [%-7s] model path\n",                                  params.model.c_str());
     fprintf(stderr, "  -f FNAME,   --file FNAME     [%-7s] text output file name\n",                       params.fname_out.c_str());
     fprintf(stderr, "  -cmd FNAME, --commands FNAME [%-7s] text file with allowed commands\n",             params.commands.c_str());
-    fprintf(stderr, "  -p,         --prompt         [%-7s] the required activation prompt\n",              params.prompt.c_str());
     fprintf(stderr, "\n");
 }
 
@@ -514,52 +510,86 @@ std::vector<std::string> read_allowed_commands(const std::string & fname) {
     return allowed_commands;
 }
 
-std::vector<std::string> get_words(const std::string &txt) {
+int main(int argc, char ** argv) {
-    std::vector<std::string> words;
+    whisper_params params;
 
-    std::istringstream iss(txt);
+    if (whisper_params_parse(argc, argv, params) == false) {
-    std::string word;
+        return 1;
-    while (iss >> word) {
-        words.push_back(word);
     }
 
-    return words;
+    if (whisper_lang_id(params.language.c_str()) == -1) {
+        fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
+        whisper_print_usage(argc, argv, params);
+        exit(0);
     }
 
-// returns true if no exit event was received
+    // whisper init
-bool process_sdl_events() {
+
-    SDL_Event event;
+    struct whisper_context * ctx = whisper_init(params.model.c_str());
-    while (SDL_PollEvent(&event)) {
+
-        switch (event.type) {
+    // print some info about the processing
-            case SDL_QUIT:
     {
-                    return false;
+        fprintf(stderr, "\n");
-                } break;
+        if (!whisper_is_multilingual(ctx)) {
-            default:
+            if (params.language != "en" || params.translate) {
-                break;
+                params.language = "en";
+                params.translate = false;
+                fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
             }
         }
+        fprintf(stderr, "%s: processing, %d threads, lang = %s, task = %s, timestamps = %d ...\n",
+                __func__,
+                params.n_threads,
+                params.language.c_str(),
+                params.translate ? "translate" : "transcribe",
+                params.no_timestamps ? 0 : 1);
+
+        fprintf(stderr, "\n");
+    }
 
-    return true;
+    // init audio
+
+    audio_async audio(30*1000);
+    if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
+        fprintf(stderr, "%s: audio.init() failed!\n", __func__);
+        return 1;
     }
 
-// command-list mode
+    audio.resume();
-// guide the transcription to match the most likely command from a provided list
+
-int process_command_list(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
+    // wait for 1 second to avoid any buffered noise
+    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
+    audio.clear();
+
+    int max_len = 0;
+
+    bool is_running  = true;
+    bool have_prompt = false;
+    bool ask_prompt  = true;
+
+    float prob0 = 0.0f;
+    float prob  = 0.0f;
+
+    std::vector<float> pcmf32_cur;
+    std::vector<float> pcmf32_prompt;
+
+    std::vector<std::string> allowed_commands;
+    std::vector<std::vector<whisper_token>> allowed_tokens;
+
+    std::string k_prompt;
+    std::vector<whisper_token> k_tokens;
+
+    if (!params.commands.empty()) {
         fprintf(stderr, "\n");
         fprintf(stderr, "%s: guided mode\n", __func__);
 
-    std::vector<std::string> allowed_commands = read_allowed_commands(params.commands);
+        allowed_commands = read_allowed_commands(params.commands);
 
         if (allowed_commands.empty()) {
             fprintf(stderr, "%s: error: failed to read allowed commands from '%s'\n", __func__, params.commands.c_str());
             return 2;
         }
 
-    int max_len = 0;
-
-    std::vector<std::vector<whisper_token>> allowed_tokens;
-
         for (const auto & cmd : allowed_commands) {
             whisper_token tokens[1024];
             allowed_tokens.emplace_back();
@@ -593,7 +623,7 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
             fprintf(stderr, " ]\n");
         }
 
-    std::string  k_prompt = "select one from the available words: ";
+        k_prompt = "select one from the available words: ";
         for (int i = 0; i < (int) allowed_commands.size(); ++i) {
             if (i > 0) {
                 k_prompt += ", ";
@@ -603,7 +633,6 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
         k_prompt += ". selected word: ";
 
         // tokenize prompt
-    std::vector<whisper_token> k_tokens;
         {
             k_tokens.resize(1024);
             const int n = whisper_tokenize(ctx, k_prompt.c_str(), k_tokens.data(), 1024);
@@ -626,239 +655,41 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
         fprintf(stderr, "%s: listening for a command ...\n", __func__);
         fprintf(stderr, "\n");
 
-    bool is_running  = true;
-
-    std::vector<float> pcmf32_cur;
-    std::vector<float> pcmf32_prompt;
-
-    // main loop
-    while (is_running) {
-        // handle Ctrl + C
-        is_running = process_sdl_events();
-
-        // delay
-        std::this_thread::sleep_for(std::chrono::milliseconds(100));
-
-        audio.get(2000, pcmf32_cur);
-
-        if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
-            fprintf(stdout, "%s: Speech detected! Processing ...\n", __func__);
-
-            const auto t_start = std::chrono::high_resolution_clock::now();
-
-            whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
-
-            wparams.print_progress   = false;
-            wparams.print_special    = params.print_special;
-            wparams.print_realtime   = false;
-            wparams.print_timestamps = !params.no_timestamps;
-            wparams.translate        = params.translate;
-            wparams.no_context       = true;
-            wparams.single_segment   = true;
-            wparams.max_tokens       = 1;
-            wparams.language         = params.language.c_str();
-            wparams.n_threads        = params.n_threads;
-
-            wparams.audio_ctx        = params.audio_ctx;
-            wparams.speed_up         = params.speed_up;
-
-            wparams.prompt_tokens    = k_tokens.data();
-            wparams.prompt_n_tokens  = k_tokens.size();
-
-            // run the transformer and a single decoding pass
-            if (whisper_full(ctx, wparams, pcmf32_cur.data(), pcmf32_cur.size()) != 0) {
-                fprintf(stderr, "%s: ERROR: whisper_full() failed\n", __func__);
-                break;
-            }
-
-            // estimate command probability
-            // NOTE: not optimal
-            {
-                const auto * logits = whisper_get_logits(ctx);
-
-                std::vector<float> probs(whisper_n_vocab(ctx), 0.0f);
-
-                // compute probs from logits via softmax
-                {
-                    float max = -1e9;
-                    for (int i = 0; i < (int) probs.size(); ++i) {
-                        max = std::max(max, logits[i]);
-                    }
-
-                    float sum = 0.0f;
-                    for (int i = 0; i < (int) probs.size(); ++i) {
-                        probs[i] = expf(logits[i] - max);
-                        sum += probs[i];
-                    }
-
-                    for (int i = 0; i < (int) probs.size(); ++i) {
-                        probs[i] /= sum;
-                    }
-                }
-
-                std::vector<std::pair<float, int>> probs_id;
-
-                double psum = 0.0;
-                for (int i = 0; i < (int) allowed_commands.size(); ++i) {
-                    probs_id.emplace_back(probs[allowed_tokens[i][0]], i);
-                    for (int j = 1; j < (int) allowed_tokens[i].size(); ++j) {
-                        probs_id.back().first += probs[allowed_tokens[i][j]];
-                    }
-                    probs_id.back().first /= allowed_tokens[i].size();
-                    psum += probs_id.back().first;
-                }
-
-                // normalize
-                for (auto & p : probs_id) {
-                    p.first /= psum;
-                }
-
-                // sort descending
-                {
-                    using pair_type = decltype(probs_id)::value_type;
-                    std::sort(probs_id.begin(), probs_id.end(), [](const pair_type & a, const pair_type & b) {
-                        return a.first > b.first;
-                    });
-                }
-
-                // print the commands and the respective probabilities
-                {
-                    fprintf(stdout, "\n");
-                    for (const auto & cmd : probs_id) {
-                        fprintf(stdout, "%s: %s%-*s%s = %f | ", __func__, "\033[1m", max_len, allowed_commands[cmd.second].c_str(), "\033[0m", cmd.first);
-                        for (int token : allowed_tokens[cmd.second]) {
-                            fprintf(stdout, "'%4s' %f ", whisper_token_to_str(ctx, token), probs[token]);
-                        }
-                        fprintf(stdout, "\n");
-                    }
-                }
-
-                // best command
-                {
-                    const auto t_end = std::chrono::high_resolution_clock::now();
-
-                    const float prob = probs_id[0].first;
-                    const int index = probs_id[0].second;
-
-                    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,
-                            (int) std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count());
-                    fprintf(stdout, "\n");
-                }
-            }
-
-            audio.clear();
-        }
-    }
-
-    return 0;
-}
-
-// always-prompt mode
-// transcribe the voice into text after valid prompt
-int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
-    bool is_running = true;
-    bool ask_prompt = true;
-
-    float prob = 0.0f;
-
-    std::vector<float> pcmf32_cur;
-
-    const std::string k_prompt = params.prompt;
-
-    const int k_prompt_length = get_words(k_prompt).size();
-
-    fprintf(stderr, "\n");
-    fprintf(stderr, "%s: always-prompt mode\n", __func__);
-
-    // main loop
-    while (is_running) {
-        // handle Ctrl + C
-        is_running = process_sdl_events();
-
-        // delay
-        std::this_thread::sleep_for(std::chrono::milliseconds(100));
-
-        if (ask_prompt) {
-            fprintf(stdout, "\n");
-            fprintf(stdout, "%s: The prompt is: '%s%s%s'\n", __func__, "\033[1m", k_prompt.c_str(), "\033[0m");
-            fprintf(stdout, "\n");
-
-            ask_prompt = false;
-        }
-
-        {
-            audio.get(2000, pcmf32_cur);
-
-            if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
-                fprintf(stdout, "%s: Speech detected! Processing ...\n", __func__);
-
-                int64_t t_ms = 0;
-
-                // detect the commands
-                audio.get(params.command_ms, pcmf32_cur);
-
-                const auto txt = ::trim(::transcribe(ctx, params, pcmf32_cur, prob, t_ms));
-
-                const auto words = get_words(txt);
-
-                std::string prompt;
-                std::string command;
-
-                for (int i = 0; i < (int) words.size(); ++i) {
-                    if (i < k_prompt_length) {
-                        prompt += words[i] + " ";
     } else {
-                        command += words[i] + " ";
-                    }
-                }
-
-                const float sim = similarity(prompt, k_prompt);
-
-                //debug
-                //fprintf(stdout, "command size: %i\n", command_length);
-
-                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);
-                }
-
-                fprintf(stdout, "\n");
-
-                audio.clear();
-            }
-        }
-    }
-
-    return 0;
-}
-
-// general-purpose mode
-// freely transcribe the voice into text
-int process_general_transcription(struct whisper_context * ctx, audio_async &audio, const whisper_params &params) {
-    bool is_running  = true;
-    bool have_prompt = false;
-    bool ask_prompt  = true;
-
-    float prob0 = 0.0f;
-    float prob  = 0.0f;
-
-    std::vector<float> pcmf32_cur;
-    std::vector<float> pcmf32_prompt;
-
-    const std::string k_prompt = "Ok Whisper, start listening for commands.";
-
         fprintf(stderr, "\n");
         fprintf(stderr, "%s: general-purpose mode\n", __func__);
 
+        k_prompt = "Ok Whisper, start listening for commands.";
+    }
+
     // main loop
     while (is_running) {
         // handle Ctrl + C
-        is_running = process_sdl_events();
+        {
+            SDL_Event event;
+            while (SDL_PollEvent(&event)) {
+                switch (event.type) {
+                    case SDL_QUIT:
+                        {
+                            is_running = false;
+                        } break;
+                    default:
+                        break;
+                }
+            }
+
+            if (!is_running) {
+                break;
+            }
+        }
 
         // delay
         std::this_thread::sleep_for(std::chrono::milliseconds(100));
 
+        if (allowed_commands.empty()) {
+            // general-purpose mode
+            // freely transcribe the voice into text
+
             if (ask_prompt) {
                 fprintf(stdout, "\n");
                 fprintf(stdout, "%s: Say the following phrase: '%s%s%s'\n", __func__, "\033[1m", k_prompt.c_str(), "\033[0m");
@@ -868,13 +699,13 @@ int process_general_transcription(struct whisper_context * ctx, audio_async &aud
             }
 
             {
+                int64_t t_ms = 0;
+
                 audio.get(2000, pcmf32_cur);
 
                 if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
                     fprintf(stdout, "%s: Speech detected! Processing ...\n", __func__);
 
-                int64_t t_ms = 0;
-
                     if (!have_prompt) {
                         // wait for activation phrase
                         audio.get(params.prompt_ms, pcmf32_cur);
@@ -936,70 +767,94 @@ int process_general_transcription(struct whisper_context * ctx, audio_async &aud
                     audio.clear();
                 }
             }
-    }
-
-    return 0;
-}
-
-int main(int argc, char ** argv) {
-    whisper_params params;
-
-    if (whisper_params_parse(argc, argv, params) == false) {
-        return 1;
-    }
-
-    if (whisper_lang_id(params.language.c_str()) == -1) {
-        fprintf(stderr, "error: unknown language '%s'\n", params.language.c_str());
-        whisper_print_usage(argc, argv, params);
-        exit(0);
-    }
-
-    // whisper init
-
-    struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
-
-    // print some info about the processing
-    {
-        fprintf(stderr, "\n");
-        if (!whisper_is_multilingual(ctx)) {
-            if (params.language != "en" || params.translate) {
-                params.language = "en";
-                params.translate = false;
-                fprintf(stderr, "%s: WARNING: model is not multilingual, ignoring language and translation options\n", __func__);
-            }
-        }
-        fprintf(stderr, "%s: processing, %d threads, lang = %s, task = %s, timestamps = %d ...\n",
-                __func__,
-                params.n_threads,
-                params.language.c_str(),
-                params.translate ? "translate" : "transcribe",
-                params.no_timestamps ? 0 : 1);
-
-        fprintf(stderr, "\n");
-    }
-
-    // init audio
-
-    audio_async audio(30*1000);
-    if (!audio.init(params.capture_id, WHISPER_SAMPLE_RATE)) {
-        fprintf(stderr, "%s: audio.init() failed!\n", __func__);
-        return 1;
-    }
-
-    audio.resume();
-
-    // wait for 1 second to avoid any buffered noise
-    std::this_thread::sleep_for(std::chrono::milliseconds(1000));
-    audio.clear();
-
-    int  ret_val = 0;
-
-    if (!params.commands.empty()) {
-        ret_val = process_command_list(ctx, audio, params);
-    } else if (!params.prompt.empty()) {
-        ret_val = always_prompt_transcription(ctx, audio, params);
         } else {
-        ret_val = process_general_transcription(ctx, audio, params);
+            // command-list mode
+            // guide the transcription to match the most likely command from a provided list
+
+            audio.get(2000, pcmf32_cur);
+
+            if (vad_simple(pcmf32_cur, WHISPER_SAMPLE_RATE, 1000, params.vad_thold, params.freq_thold, params.print_energy)) {
+                fprintf(stdout, "%s: Speech detected! Processing ...\n", __func__);
+
+                const auto t_start = std::chrono::high_resolution_clock::now();
+
+                whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
+
+                wparams.print_progress   = false;
+                wparams.print_special    = params.print_special;
+                wparams.print_realtime   = false;
+                wparams.print_timestamps = !params.no_timestamps;
+                wparams.translate        = params.translate;
+                wparams.no_context       = true;
+                wparams.single_segment   = true;
+                wparams.max_tokens       = 1;
+                wparams.language         = params.language.c_str();
+                wparams.n_threads        = params.n_threads;
+
+                wparams.audio_ctx        = params.audio_ctx;
+                wparams.speed_up         = params.speed_up;
+
+                wparams.prompt_tokens    = k_tokens.data();
+                wparams.prompt_n_tokens  = k_tokens.size();
+
+                // run the transformer and a single decoding pass
+                if (whisper_full(ctx, wparams, pcmf32_cur.data(), pcmf32_cur.size()) != 0) {
+                    fprintf(stderr, "%s: ERROR: whisper_full() failed\n", __func__);
+                    break;
+                }
+
+                const auto * probs = whisper_get_probs(ctx);
+                std::vector<std::pair<float, int>> probs_id;
+
+                double psum = 0.0;
+                for (int i = 0; i < (int) allowed_commands.size(); ++i) {
+                    probs_id.emplace_back(probs[allowed_tokens[i][0]], i);
+                    for (int j = 1; j < (int) allowed_tokens[i].size(); ++j) {
+                        probs_id.back().first += probs[allowed_tokens[i][j]];
+                    }
+                    probs_id.back().first /= allowed_tokens[i].size();
+                    psum += probs_id.back().first;
+                }
+
+                // normalize
+                for (auto & p : probs_id) {
+                    p.first /= psum;
+                }
+
+                // sort descending
+                {
+                    using pair_type = decltype(probs_id)::value_type;
+                    std::sort(probs_id.begin(), probs_id.end(), [](const pair_type & a, const pair_type & b) {
+                        return a.first > b.first;
+                    });
+                }
+
+                // print the commands and the respective probabilities
+                {
+                    fprintf(stdout, "\n");
+                    for (const auto & cmd : probs_id) {
+                        fprintf(stdout, "%s: %s%-*s%s = %f | ", __func__, "\033[1m", max_len, allowed_commands[cmd.second].c_str(), "\033[0m", cmd.first);
+                        for (int i = 0; i < (int) allowed_tokens[cmd.second].size(); ++i) {
+                            fprintf(stdout, "'%4s' %f ", whisper_token_to_str(ctx, allowed_tokens[cmd.second][i]), probs[allowed_tokens[cmd.second][i]]);
+                        }
+                        fprintf(stdout, "\n");
+                    }
+                }
+
+                // best command
+                {
+                    const auto t_end = std::chrono::high_resolution_clock::now();
+
+                    fprintf(stdout, "\n");
+                    fprintf(stdout, "%s: detected command: %s%s%s | p = %f | t = %d ms\n", __func__,
+                            "\033[1m", allowed_commands[probs_id[0].second].c_str(), "\033[0m", probs_id[0].first,
+                            (int) std::chrono::duration_cast<std::chrono::milliseconds>(t_end - t_start).count());
+                    fprintf(stdout, "\n");
+                }
+
+                audio.clear();
+            }
+        }
     }
 
     audio.pause();
@@ -1007,5 +862,5 @@ int main(int argc, char ** argv) {
     whisper_print_timings(ctx);
     whisper_free(ctx);
 
-    return ret_val;
+    return 0;
 }

examples/helpers.js

@@ -8,7 +8,7 @@ function convertTypedArray(src, type) {
 
 var printTextarea = (function() {
     var element = document.getElementById('output');
-    if (element) element.value = ''; // clear browser cache
+    if (element) element.alue = ''; // clear browser cache
     return function(text) {
         if (arguments.length > 1) text = Array.prototype.slice.call(arguments).join(' ');
         console.log(text);
@@ -88,15 +88,11 @@ async function fetchRemote(url, cbProgress, cbPrint) {
 // - check if the data is already in the IndexedDB
 // - if not, fetch it from the remote URL and store it in the IndexedDB
 function loadRemote(url, dst, size_mb, cbProgress, cbReady, cbCancel, cbPrint) {
-    if (!navigator.storage || !navigator.storage.estimate) {
-        cbPrint('loadRemote: navigator.storage.estimate() is not supported');
-    } else {
     // query the storage quota and print it
     navigator.storage.estimate().then(function (estimate) {
         cbPrint('loadRemote: storage quota: ' + estimate.quota + ' bytes');
         cbPrint('loadRemote: storage usage: ' + estimate.usage + ' bytes');
     });
-    }
 
     // check if the data is already in the IndexedDB
     var rq = indexedDB.open(dbName, dbVersion);

examples/livestream.sh

@@ -100,7 +100,7 @@ while [ $running -eq 1 ]; do
         err=$(cat /tmp/whisper-live.err | wc -l)
     done
 
-    ./main -t 8 -m ./models/ggml-${model}.bin -f /tmp/whisper-live.wav --no-timestamps -otxt 2> /tmp/whispererr | tail -n 1
+    ./main -t 8 -m ./models/ggml-base.en.bin -f /tmp/whisper-live.wav --no-timestamps -otxt 2> /tmp/whispererr | tail -n 1
 
     while [ $SECONDS -lt $((($i+1)*$step_s)) ]; do
         sleep 1

examples/main/CMakeLists.txt

@@ -1,6 +1,3 @@
 set(TARGET main)
 add_executable(${TARGET} main.cpp)
-
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE whisper ${CMAKE_THREAD_LIBS_INIT})

examples/main/README.md

@@ -17,27 +17,17 @@ options:
   -d  N,    --duration N    [0      ] duration of audio to process in milliseconds
   -mc N,    --max-context N [-1     ] maximum number of text context tokens to store
   -ml N,    --max-len N     [0      ] maximum segment length in characters
-  -bo N,     --best-of N         [5      ] number of best candidates to keep
-  -bs N,     --beam-size N       [-1     ] beam size for beam search
   -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
   -su,      --speed-up      [false  ] speed up audio by x2 (reduced accuracy)
   -tr,      --translate     [false  ] translate from source language to english
-  -di,       --diarize           [false  ] stereo audio diarization
-  -nf,       --no-fallback       [false  ] do not use temperature fallback while decoding
   -otxt,    --output-txt    [false  ] output result in a text file
   -ovtt,    --output-vtt    [false  ] output result in a vtt file
   -osrt,    --output-srt    [false  ] output result in a srt file
   -owts,    --output-words  [false  ] output script for generating karaoke video
-  -ocsv,     --output-csv        [false  ] output result in a CSV file
-  -of FNAME, --output-file FNAME [       ] output file path (without file extension)
   -ps,      --print-special [false  ] print special tokens
   -pc,      --print-colors  [false  ] print colors
-  -pp,       --print-progress    [false  ] print progress
   -nt,      --no-timestamps [true   ] do not print timestamps
-  -l LANG,   --language LANG     [en     ] spoken language ('auto' for auto-detect)
+  -l LANG,  --language LANG [en     ] spoken language
-             --prompt PROMPT     [       ] initial prompt
   -m FNAME, --model FNAME   [models/ggml-base.en.bin] model path
   -f FNAME, --file FNAME    [       ] input WAV file path
 ```

examples/main/main.cpp

@@ -59,22 +59,16 @@ struct whisper_params {
     int32_t duration_ms  = 0;
     int32_t max_context  = -1;
     int32_t max_len      = 0;
-    int32_t best_of      =  5;
-    int32_t beam_size    = -1;
 
     float word_thold = 0.01f;
-    float entropy_thold =  2.40f;
-    float logprob_thold = -1.00f;
 
     bool speed_up       = false;
     bool translate      = false;
     bool diarize        = false;
-    bool no_fallback    = false;
     bool output_txt     = false;
     bool output_vtt     = false;
     bool output_srt     = false;
     bool output_wts     = false;
-    bool output_csv     = false;
     bool print_special  = false;
     bool print_colors   = false;
     bool print_progress = false;
@@ -85,7 +79,6 @@ struct whisper_params {
     std::string model    = "models/ggml-base.en.bin";
 
     std::vector<std::string> fname_inp = {};
-    std::vector<std::string> fname_outp = {};
 };
 
 void whisper_print_usage(int argc, char ** argv, const whisper_params & params);
@@ -110,21 +103,14 @@ bool whisper_params_parse(int argc, char ** argv, whisper_params & params) {
         else if (arg == "-d"    || arg == "--duration")       { params.duration_ms    = std::stoi(argv[++i]); }
         else if (arg == "-mc"   || arg == "--max-context")    { params.max_context    = std::stoi(argv[++i]); }
         else if (arg == "-ml"   || arg == "--max-len")        { params.max_len        = std::stoi(argv[++i]); }
-        else if (arg == "-bo"   || arg == "--best-of")        { params.best_of        = std::stoi(argv[++i]); }
-        else if (arg == "-bs"   || arg == "--beam-size")      { params.beam_size      = std::stoi(argv[++i]); }
         else if (arg == "-wt"   || arg == "--word-thold")     { params.word_thold     = std::stof(argv[++i]); }
-        else if (arg == "-et"   || arg == "--entropy-thold")  { params.entropy_thold  = std::stof(argv[++i]); }
-        else if (arg == "-lpt"  || arg == "--logprob-thold")  { params.logprob_thold  = std::stof(argv[++i]); }
         else if (arg == "-su"   || arg == "--speed-up")       { params.speed_up       = true; }
         else if (arg == "-tr"   || arg == "--translate")      { params.translate      = true; }
         else if (arg == "-di"   || arg == "--diarize")        { params.diarize        = true; }
-        else if (arg == "-nf"   || arg == "--no-fallback")    { params.no_fallback    = true; }
         else if (arg == "-otxt" || arg == "--output-txt")     { params.output_txt     = true; }
         else if (arg == "-ovtt" || arg == "--output-vtt")     { params.output_vtt     = true; }
         else if (arg == "-osrt" || arg == "--output-srt")     { params.output_srt     = true; }
         else if (arg == "-owts" || arg == "--output-words")   { params.output_wts     = true; }
-        else if (arg == "-ocsv" || arg == "--output-csv")     { params.output_csv     = true; }
-        else if (arg == "-of"   || arg == "--output-file")    { params.fname_outp.emplace_back(argv[++i]); }
         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 == "-pp"   || arg == "--print-progress") { params.print_progress = true; }
@@ -156,21 +142,14 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
     fprintf(stderr, "  -d  N,    --duration N     [%-7d] duration of audio to process in milliseconds\n",   params.duration_ms);
     fprintf(stderr, "  -mc N,    --max-context N  [%-7d] maximum number of text context tokens to store\n", params.max_context);
     fprintf(stderr, "  -ml N,    --max-len N      [%-7d] maximum segment length in characters\n",           params.max_len);
-    fprintf(stderr, "  -bo N,     --best-of N         [%-7d] number of best candidates to keep\n",              params.best_of);
-    fprintf(stderr, "  -bs N,     --beam-size N       [%-7d] beam size for beam search\n",                      params.beam_size);
     fprintf(stderr, "  -wt N,    --word-thold N   [%-7.2f] word timestamp probability threshold\n",         params.word_thold);
-    fprintf(stderr, "  -et N,     --entropy-thold N   [%-7.2f] entropy threshold for decoder fail\n",           params.entropy_thold);
-    fprintf(stderr, "  -lpt N,    --logprob-thold N   [%-7.2f] log probability threshold for decoder fail\n",   params.logprob_thold);
     fprintf(stderr, "  -su,      --speed-up       [%-7s] speed up audio by x2 (reduced accuracy)\n",        params.speed_up ? "true" : "false");
     fprintf(stderr, "  -tr,      --translate      [%-7s] translate from source language to english\n",      params.translate ? "true" : "false");
     fprintf(stderr, "  -di,      --diarize        [%-7s] stereo audio diarization\n",                       params.diarize ? "true" : "false");
-    fprintf(stderr, "  -nf,       --no-fallback       [%-7s] do not use temperature fallback while decoding\n", params.no_fallback ? "true" : "false");
     fprintf(stderr, "  -otxt,    --output-txt     [%-7s] output result in a text file\n",                   params.output_txt ? "true" : "false");
     fprintf(stderr, "  -ovtt,    --output-vtt     [%-7s] output result in a vtt file\n",                    params.output_vtt ? "true" : "false");
     fprintf(stderr, "  -osrt,    --output-srt     [%-7s] output result in a srt file\n",                    params.output_srt ? "true" : "false");
     fprintf(stderr, "  -owts,    --output-words   [%-7s] output script for generating karaoke video\n",     params.output_wts ? "true" : "false");
-    fprintf(stderr, "  -ocsv,     --output-csv        [%-7s] output result in a CSV file\n",                    params.output_csv ? "true" : "false");
-    fprintf(stderr, "  -of FNAME, --output-file FNAME [%-7s] output file path (without file extension)\n",      "");
     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, "  -pp,      --print-progress [%-7s] print progress\n",                                 params.print_progress ? "true" : "false");
@@ -194,27 +173,40 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
 
     const int n_segments = whisper_full_n_segments(ctx);
 
-    std::string speaker = "";
-
-    int64_t t0;
-    int64_t t1;
-
     // print the last n_new segments
     const int s0 = n_segments - n_new;
-
     if (s0 == 0) {
         printf("\n");
     }
 
     for (int i = s0; i < n_segments; i++) {
-        if (!params.no_timestamps || params.diarize) {
+        if (params.no_timestamps) {
-            t0 = whisper_full_get_segment_t0(ctx, i);
+            if (params.print_colors) {
-            t1 = whisper_full_get_segment_t1(ctx, i);
+                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;
+                        }
                     }
 
-        if (!params.no_timestamps) {
+                    const char * text = whisper_full_get_token_text(ctx, i, j);
-            printf("[%s --> %s]  ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
+                    const float  p    = whisper_full_get_token_p   (ctx, i, j);
+
+                    const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
+
+                    printf("%s%s%s", k_colors[col].c_str(), text, "\033[0m");
                 }
+            } else {
+                const char * text = whisper_full_get_segment_text(ctx, i);
+                printf("%s", text);
+            }
+            fflush(stdout);
+        } else {
+            const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
+            const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
+
+            std::string speaker;
 
             if (params.diarize && pcmf32s.size() == 2) {
                 const int64_t n_samples = pcmf32s[0].size();
@@ -242,6 +234,7 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
             }
 
             if (params.print_colors) {
+                printf("[%s --> %s]  ", to_timestamp(t0).c_str(), to_timestamp(t1).c_str());
                 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);
@@ -253,22 +246,17 @@ void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, voi
                     const char * text = whisper_full_get_token_text(ctx, i, j);
                     const float  p    = whisper_full_get_token_p   (ctx, i, j);
 
-                const int col = std::max(0, std::min((int) k_colors.size() - 1, (int) (std::pow(p, 3)*float(k_colors.size()))));
+                    const int col = std::max(0, std::min((int) k_colors.size(), (int) (std::pow(p, 3)*float(k_colors.size()))));
 
                     printf("%s%s%s%s", speaker.c_str(), k_colors[col].c_str(), text, "\033[0m");
                 }
+                printf("\n");
             } else {
                 const char * text = whisper_full_get_segment_text(ctx, i);
 
-            printf("%s%s", speaker.c_str(), text);
+                printf("[%s --> %s]  %s%s\n", to_timestamp(t0).c_str(), to_timestamp(t1).c_str(), speaker.c_str(), text);
             }
-
-        // with timestamps or speakers: each segment on new line
-        if (!params.no_timestamps || params.diarize) {
-            printf("\n");
         }
-
-        fflush(stdout);
     }
 }
 
@@ -337,28 +325,6 @@ bool output_srt(struct whisper_context * ctx, const char * fname, const whisper_
     return true;
 }
 
-bool output_csv(struct whisper_context * ctx, const char * fname) {
-    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);
-
-    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);
-        const int64_t t0 = whisper_full_get_segment_t0(ctx, i);
-        const int64_t t1 = whisper_full_get_segment_t1(ctx, i);
-
-        //need to multiply times returned from whisper_full_get_segment_t{0,1}() by 10 to get milliseconds.
-        fout << 10 * t0 << ", " << 10 * t1 << ", \"" << text    << "\"\n";
-    }
-
-    return true;
-}
-
 // karaoke video generation
 // outputs a bash script that uses ffmpeg to generate a video with the subtitles
 // TODO: font parameter adjustments
@@ -492,7 +458,7 @@ int main(int argc, char ** argv) {
 
     // whisper init
 
-    struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
+    struct whisper_context * ctx = whisper_init(params.model.c_str());
 
     if (ctx == nullptr) {
         fprintf(stderr, "error: failed to initialize whisper context\n");
@@ -517,7 +483,6 @@ 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_outp = f < (int) params.fname_outp.size() && !params.fname_outp[f].empty() ? params.fname_outp[f] : params.fname_inp[f];
 
         std::vector<float> pcmf32; // mono-channel F32 PCM
         std::vector<std::vector<float>> pcmf32s; // stereo-channel F32 PCM
@@ -563,7 +528,7 @@ int main(int argc, char ** argv) {
             }
 
             if (wav.sampleRate != WHISPER_SAMPLE_RATE) {
-                fprintf(stderr, "%s: WAV file '%s' must be %i kHz\n", argv[0], fname_inp.c_str(), WHISPER_SAMPLE_RATE/1000);
+                fprintf(stderr, "%s: WAV file '%s' must be 16 kHz\n", argv[0], fname_inp.c_str());
                 return 8;
             }
 
@@ -635,8 +600,6 @@ int main(int argc, char ** argv) {
         {
             whisper_full_params wparams = whisper_full_default_params(WHISPER_SAMPLING_GREEDY);
 
-            wparams.strategy = params.beam_size > 1 ? WHISPER_SAMPLING_BEAM_SEARCH : WHISPER_SAMPLING_GREEDY;
-
             wparams.print_realtime   = false;
             wparams.print_progress   = params.print_progress;
             wparams.print_timestamps = !params.no_timestamps;
@@ -657,13 +620,6 @@ int main(int argc, char ** argv) {
             wparams.prompt_tokens    = prompt_tokens.empty() ? nullptr : prompt_tokens.data();
             wparams.prompt_n_tokens  = prompt_tokens.empty() ? 0       : prompt_tokens.size();
 
-            wparams.greedy.best_of        = params.best_of;
-            wparams.beam_search.beam_size = params.beam_size;
-
-            wparams.temperature_inc  = params.no_fallback ? 0.0f : wparams.temperature_inc;
-            wparams.entropy_thold    = params.entropy_thold;
-            wparams.logprob_thold    = params.logprob_thold;
-
             whisper_print_user_data user_data = { &params, &pcmf32s };
 
             // this callback is called on each new segment
@@ -697,34 +653,27 @@ int main(int argc, char ** argv) {
 
             // output to text file
             if (params.output_txt) {
-                const auto fname_txt = fname_outp + ".txt";
+                const auto fname_txt = fname_inp + ".txt";
                 output_txt(ctx, fname_txt.c_str());
             }
 
             // output to VTT file
             if (params.output_vtt) {
-                const auto fname_vtt = fname_outp + ".vtt";
+                const auto fname_vtt = fname_inp + ".vtt";
                 output_vtt(ctx, fname_vtt.c_str());
             }
 
             // output to SRT file
             if (params.output_srt) {
-                const auto fname_srt = fname_outp + ".srt";
+                const auto fname_srt = fname_inp + ".srt";
                 output_srt(ctx, fname_srt.c_str(), params);
             }
 
             // output to WTS file
             if (params.output_wts) {
-                const auto fname_wts = fname_outp + ".wts";
+                const auto fname_wts = fname_inp + ".wts";
                 output_wts(ctx, fname_wts.c_str(), fname_inp.c_str(), params, float(pcmf32.size() + 1000)/WHISPER_SAMPLE_RATE);
             }
-
-	    // output to CSV file
-            if (params.output_csv) {
-                const auto fname_csv = fname_outp + ".csv";
-                output_csv(ctx, fname_csv.c_str());
-            }
-
         }
     }
 

examples/stream.wasm/CMakeLists.txt

@@ -8,8 +8,6 @@ add_executable(${TARGET}
     emscripten.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE
     whisper
     )

examples/stream.wasm/emscripten.cpp

@@ -49,9 +49,6 @@ void stream_main(size_t index) {
     wparams.max_tokens       = 32;
     wparams.audio_ctx        = 768; // partial encoder context for better performance
 
-    // disable temperature fallback
-    wparams.temperature_inc  = -1.0f;
-
     wparams.language         = "en";
 
     printf("stream: using %d threads\n", wparams.n_threads);
@@ -132,7 +129,7 @@ EMSCRIPTEN_BINDINGS(stream) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         for (size_t i = 0; i < g_contexts.size(); ++i) {
             if (g_contexts[i] == nullptr) {
-                g_contexts[i] = whisper_init_from_file(path_model.c_str());
+                g_contexts[i] = whisper_init(path_model.c_str());
                 if (g_contexts[i] != nullptr) {
                     g_running = true;
                     if (g_worker.joinable()) {

examples/stream/CMakeLists.txt

@@ -2,9 +2,6 @@ if (WHISPER_SUPPORT_SDL2)
     # stream
     set(TARGET stream)
     add_executable(${TARGET} stream.cpp)
-
-    include(DefaultTargetOptions)
-
     target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS})
     target_link_libraries(${TARGET} PRIVATE whisper ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
 endif ()

examples/stream/stream.cpp

@@ -8,7 +8,6 @@
 #include <SDL.h>
 #include <SDL_audio.h>
 
-#include <atomic>
 #include <cassert>
 #include <cstdio>
 #include <string>
@@ -145,7 +144,7 @@ private:
     int m_len_ms = 0;
     int m_sample_rate = 0;
 
-    std::atomic_bool m_running;
+    bool       m_running = false;
     std::mutex m_mutex;
 
     std::vector<float> m_audio;
@@ -156,8 +155,6 @@ private:
 
 audio_async::audio_async(int len_ms) {
     m_len_ms = len_ms;
-
-    m_running = false;
 }
 
 audio_async::~audio_async() {
@@ -423,20 +420,19 @@ int main(int argc, char ** argv) {
         return 1;
     }
 
-    params.keep_ms   = std::min(params.keep_ms,   params.step_ms);
+    params.keep_ms = std::min(params.keep_ms, params.step_ms); // cannot be more than step_ms
-    params.length_ms = std::max(params.length_ms, params.step_ms);
 
     const int n_samples_step = (params.step_ms  *1e-3)*WHISPER_SAMPLE_RATE;
     const int n_samples_len  = (params.length_ms*1e-3)*WHISPER_SAMPLE_RATE;
     const int n_samples_keep = (params.keep_ms  *1e-3)*WHISPER_SAMPLE_RATE;
     const int n_samples_30s  = (30000           *1e-3)*WHISPER_SAMPLE_RATE;
 
+    const int n_new_line = params.length_ms / params.step_ms - 1; // number of steps to print new line
+
     const bool use_vad = n_samples_step <= 0; // sliding window mode uses VAD
 
-    const int n_new_line = !use_vad ? std::max(1, params.length_ms / params.step_ms - 1) : 1; // number of steps to print new line
-
     params.no_timestamps = !use_vad;
-    params.no_context    |= use_vad;
+    params.no_context    = use_vad;
     params.max_tokens    = 0;
 
     // init audio
@@ -457,10 +453,10 @@ int main(int argc, char ** argv) {
         exit(0);
     }
 
-    struct whisper_context * ctx = whisper_init_from_file(params.model.c_str());
+    struct whisper_context * ctx = whisper_init(params.model.c_str());
 
     std::vector<float> pcmf32    (n_samples_30s, 0.0f);
-    std::vector<float> pcmf32_old;
+    std::vector<float> pcmf32_old(n_samples_30s, 0.0f);
     std::vector<float> pcmf32_new(n_samples_30s, 0.0f);
 
     std::vector<whisper_token> prompt_tokens;
@@ -487,7 +483,7 @@ int main(int argc, char ** argv) {
                 params.no_timestamps ? 0 : 1);
 
         if (!use_vad) {
-            fprintf(stderr, "%s: n_new_line = %d, no_context = %d\n", __func__, n_new_line, params.no_context);
+            fprintf(stderr, "%s: n_new_line = %d\n", __func__, n_new_line);
         } else {
             fprintf(stderr, "%s: using VAD, will transcribe on speech activity\n", __func__);
         }
@@ -616,9 +612,6 @@ int main(int argc, char ** argv) {
             wparams.audio_ctx        = params.audio_ctx;
             wparams.speed_up         = params.speed_up;
 
-            // disable temperature fallback
-            wparams.temperature_inc  = -1.0f;
-
             wparams.prompt_tokens    = params.no_context ? nullptr : prompt_tokens.data();
             wparams.prompt_n_tokens  = params.no_context ? 0       : prompt_tokens.size();
 

examples/talk.wasm/CMakeLists.txt

@@ -9,8 +9,6 @@ add_executable(${TARGET}
     gpt-2.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE
     whisper
     )
@@ -33,8 +31,8 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     --bind \
     -s USE_PTHREADS=1 \
     -s PTHREAD_POOL_SIZE=8 \
-    -s INITIAL_MEMORY=1800MB \
+    -s INITIAL_MEMORY=1600MB \
-    -s TOTAL_MEMORY=1800MB \
+    -s TOTAL_MEMORY=1600MB \
     -s FORCE_FILESYSTEM=1 \
     -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
     ${EXTRA_FLAGS} \

examples/talk.wasm/README.md

@@ -36,7 +36,7 @@ In order to run this demo efficiently, you need to have the following:
 - Latest Chrome or Firefox browser (Safari is not supported)
 - Run this on a desktop or laptop with modern CPU (a mobile phone will likely not be good enough)
 - Speak phrases that are no longer than 10 seconds - this is the audio context of the AI
-- The web-page uses about 1.8GB of RAM
+- The web-page uses about 1.6GB of RAM
 
 Notice that this demo is using the smallest GPT-2 model, so the generated text responses are not always very good.
 Also, the prompting strategy can likely be improved to achieve better results.

examples/talk.wasm/emscripten.cpp

@@ -271,7 +271,7 @@ EMSCRIPTEN_BINDINGS(talk) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         for (size_t i = 0; i < g_contexts.size(); ++i) {
             if (g_contexts[i] == nullptr) {
-                g_contexts[i] = whisper_init_from_file(path_model.c_str());
+                g_contexts[i] = whisper_init(path_model.c_str());
                 if (g_contexts[i] != nullptr) {
                     g_running = true;
                     if (g_worker.joinable()) {

examples/talk/CMakeLists.txt

@@ -8,9 +8,6 @@ if (WHISPER_SUPPORT_SDL2)
     # TODO: this is temporary
     #       need to export ggml symbols for MSVC, but too lazy ..
     add_executable(${TARGET} talk.cpp gpt-2.cpp ../../ggml.c ../../whisper.cpp)
-
-    include(DefaultTargetOptions)
-
     target_include_directories(${TARGET} PRIVATE ${SDL2_INCLUDE_DIRS} ../../)
     target_link_libraries(${TARGET} PRIVATE ${SDL2_LIBRARIES} ${CMAKE_THREAD_LIBS_INIT})
 endif ()

examples/talk/talk.cpp

@@ -498,7 +498,7 @@ int main(int argc, char ** argv) {
 
     // whisper init
 
-    struct whisper_context * ctx_wsp = whisper_init_from_file(params.model_wsp.c_str());
+    struct whisper_context * ctx_wsp = whisper_init(params.model_wsp.c_str());
 
     // gpt init
 

examples/whisper.android/app/src/main/java/com/whispercppdemo/ui/main/MainScreenViewModel.kt

@@ -64,21 +64,16 @@ class MainScreenViewModel(private val application: Application) : ViewModel() {
     private suspend fun copyAssets() = withContext(Dispatchers.IO) {
         modelsPath.mkdirs()
         samplesPath.mkdirs()
-        //application.copyData("models", modelsPath, ::printMessage)
+        application.copyData("models", modelsPath, ::printMessage)
         application.copyData("samples", samplesPath, ::printMessage)
         printMessage("All data copied to working directory.\n")
     }
 
     private suspend fun loadBaseModel() = withContext(Dispatchers.IO) {
         printMessage("Loading model...\n")
-        val models = application.assets.list("models/")
+        val firstModel = modelsPath.listFiles()!!.first()
-        if (models != null) {
+        whisperContext = WhisperContext.createContext(firstModel.absolutePath)
-            whisperContext = WhisperContext.createContextFromAsset(application.assets, "models/" + models[0])
+        printMessage("Loaded model ${firstModel.name}.\n")
-            printMessage("Loaded model ${models[0]}.\n")
-        }
-
-        //val firstModel = modelsPath.listFiles()!!.first()
-        //whisperContext = WhisperContext.createContextFromFile(firstModel.absolutePath)
     }
 
     fun transcribeSample() = viewModelScope.launch {

examples/whisper.android/app/src/main/java/com/whispercppdemo/whisper/LibWhisper.kt

@@ -1,11 +1,9 @@
 package com.whispercppdemo.whisper
 
-import android.content.res.AssetManager
 import android.os.Build
 import android.util.Log
 import kotlinx.coroutines.*
 import java.io.File
-import java.io.InputStream
 import java.util.concurrent.Executors
 
 private const val LOG_TAG = "LibWhisper"
@@ -41,31 +39,13 @@ class WhisperContext private constructor(private var ptr: Long) {
     }
 
     companion object {
-        fun createContextFromFile(filePath: String): WhisperContext {
+        fun createContext(filePath: String): WhisperContext {
             val ptr = WhisperLib.initContext(filePath)
             if (ptr == 0L) {
                 throw java.lang.RuntimeException("Couldn't create context with path $filePath")
             }
             return WhisperContext(ptr)
         }
-
-        fun createContextFromInputStream(stream: InputStream): WhisperContext {
-            val ptr = WhisperLib.initContextFromInputStream(stream)
-
-            if (ptr == 0L) {
-                throw java.lang.RuntimeException("Couldn't create context from input stream")
-            }
-            return WhisperContext(ptr)
-        }
-
-        fun createContextFromAsset(assetManager: AssetManager, assetPath: String): WhisperContext {
-            val ptr = WhisperLib.initContextFromAsset(assetManager, assetPath)
-
-            if (ptr == 0L) {
-                throw java.lang.RuntimeException("Couldn't create context from asset $assetPath")
-            }
-            return WhisperContext(ptr)
-        }
     }
 }
 
@@ -96,8 +76,6 @@ private class WhisperLib {
         }
 
         // JNI methods
-        external fun initContextFromInputStream(inputStream: InputStream): Long
-        external fun initContextFromAsset(assetManager: AssetManager, assetPath: String): Long
         external fun initContext(modelPath: String): Long
         external fun freeContext(contextPtr: Long)
         external fun fullTranscribe(contextPtr: Long, audioData: FloatArray)

examples/whisper.android/app/src/main/jni/whisper/Whisper.mk

@@ -1,5 +1,5 @@
 WHISPER_LIB_DIR := $(LOCAL_PATH)/../../../../../../../
-LOCAL_LDLIBS    := -landroid -llog
+LOCAL_LDLIBS    := -llog
 
 # Make the final output library smaller by only keeping the symbols referenced from the app.
 ifneq ($(APP_OPTIM),debug)

examples/whisper.android/app/src/main/jni/whisper/jni.c

@@ -1,17 +1,13 @@
 #include <jni.h>
-#include <android/asset_manager.h>
-#include <android/asset_manager_jni.h>
 #include <android/log.h>
 #include <stdlib.h>
 #include <sys/sysinfo.h>
-#include <string.h>
 #include "whisper.h"
 
 #define UNUSED(x) (void)(x)
 #define TAG "JNI"
 
 #define LOGI(...) __android_log_print(ANDROID_LOG_INFO,     TAG, __VA_ARGS__)
-#define LOGW(...) __android_log_print(ANDROID_LOG_WARN,     TAG, __VA_ARGS__)
 
 static inline int min(int a, int b) {
     return (a < b) ? a : b;
@@ -21,132 +17,13 @@ static inline int max(int a, int b) {
     return (a > b) ? a : b;
 }
 
-struct input_stream_context {
-    size_t offset;
-    JNIEnv * env;
-    jobject thiz;
-    jobject input_stream;
-
-    jmethodID mid_available;
-    jmethodID mid_read;
-};
-
-size_t inputStreamRead(void * ctx, void * output, size_t read_size) {
-    struct input_stream_context* is = (struct input_stream_context*)ctx;
-
-    jint avail_size = (*is->env)->CallIntMethod(is->env, is->input_stream, is->mid_available);
-    jint size_to_copy = read_size < avail_size ? (jint)read_size : avail_size;
-
-    jbyteArray byte_array = (*is->env)->NewByteArray(is->env, size_to_copy);
-
-    jint n_read = (*is->env)->CallIntMethod(is->env, is->input_stream, is->mid_read, byte_array, 0, size_to_copy);
-
-    if (size_to_copy != read_size || size_to_copy != n_read) {
-        LOGI("Insufficient Read: Req=%zu, ToCopy=%d, Available=%d", read_size, size_to_copy, n_read);
-    }
-
-    jbyte* byte_array_elements = (*is->env)->GetByteArrayElements(is->env, byte_array, NULL);
-    memcpy(output, byte_array_elements, size_to_copy);
-    (*is->env)->ReleaseByteArrayElements(is->env, byte_array, byte_array_elements, JNI_ABORT);
-
-    (*is->env)->DeleteLocalRef(is->env, byte_array);
-
-    is->offset += size_to_copy;
-
-    return size_to_copy;
-}
-bool inputStreamEof(void * ctx) {
-    struct input_stream_context* is = (struct input_stream_context*)ctx;
-
-    jint result = (*is->env)->CallIntMethod(is->env, is->input_stream, is->mid_available);
-    return result <= 0;
-}
-void inputStreamClose(void * ctx) {
-
-}
-
-JNIEXPORT jlong JNICALL
-Java_com_whispercppdemo_whisper_WhisperLib_00024Companion_initContextFromInputStream(
-        JNIEnv *env, jobject thiz, jobject input_stream) {
-    UNUSED(thiz);
-
-    struct whisper_context *context = NULL;
-    struct whisper_model_loader loader = {};
-    struct input_stream_context inp_ctx = {};
-
-    inp_ctx.offset = 0;
-    inp_ctx.env = env;
-    inp_ctx.thiz = thiz;
-    inp_ctx.input_stream = input_stream;
-
-    jclass cls = (*env)->GetObjectClass(env, input_stream);
-    inp_ctx.mid_available = (*env)->GetMethodID(env, cls, "available", "()I");
-    inp_ctx.mid_read = (*env)->GetMethodID(env, cls, "read", "([BII)I");
-
-    loader.context = &inp_ctx;
-    loader.read = inputStreamRead;
-    loader.eof = inputStreamEof;
-    loader.close = inputStreamClose;
-
-    loader.eof(loader.context);
-
-    context = whisper_init(&loader);
-    return (jlong) context;
-}
-
-static size_t asset_read(void *ctx, void *output, size_t read_size) {
-    return AAsset_read((AAsset *) ctx, output, read_size);
-}
-
-static bool asset_is_eof(void *ctx) {
-    return AAsset_getRemainingLength64((AAsset *) ctx) <= 0;
-}
-
-static void asset_close(void *ctx) {
-    AAsset_close((AAsset *) ctx);
-}
-
-static struct whisper_context *whisper_init_from_asset(
-        JNIEnv *env,
-        jobject assetManager,
-        const char *asset_path
-) {
-    LOGI("Loading model from asset '%s'\n", asset_path);
-    AAssetManager *asset_manager = AAssetManager_fromJava(env, assetManager);
-    AAsset *asset = AAssetManager_open(asset_manager, asset_path, AASSET_MODE_STREAMING);
-    if (!asset) {
-        LOGW("Failed to open '%s'\n", asset_path);
-        return NULL;
-    }
-
-    whisper_model_loader loader = {
-            .context = asset,
-            .read = &asset_read,
-            .eof = &asset_is_eof,
-            .close = &asset_close
-    };
-
-    return whisper_init(&loader);
-}
-
-JNIEXPORT jlong JNICALL
-Java_com_whispercppdemo_whisper_WhisperLib_00024Companion_initContextFromAsset(
-        JNIEnv *env, jobject thiz, jobject assetManager, jstring asset_path_str) {
-    UNUSED(thiz);
-    struct whisper_context *context = NULL;
-    const char *asset_path_chars = (*env)->GetStringUTFChars(env, asset_path_str, NULL);
-    context = whisper_init_from_asset(env, assetManager, asset_path_chars);
-    (*env)->ReleaseStringUTFChars(env, asset_path_str, asset_path_chars);
-    return (jlong) context;
-}
-
 JNIEXPORT jlong JNICALL
 Java_com_whispercppdemo_whisper_WhisperLib_00024Companion_initContext(
         JNIEnv *env, jobject thiz, jstring model_path_str) {
     UNUSED(thiz);
     struct whisper_context *context = NULL;
     const char *model_path_chars = (*env)->GetStringUTFChars(env, model_path_str, NULL);
-    context = whisper_init_from_file(model_path_chars);
+    context = whisper_init(model_path_chars);
     (*env)->ReleaseStringUTFChars(env, model_path_str, model_path_chars);
     return (jlong) context;
 }

examples/whisper.android/local.properties

@@ -0,0 +1,10 @@
+## This file is automatically generated by Android Studio.
+# Do not modify this file -- YOUR CHANGES WILL BE ERASED!
+#
+# This file should *NOT* be checked into Version Control Systems,
+# as it contains information specific to your local configuration.
+#
+# Location of the SDK. This is only used by Gradle.
+# For customization when using a Version Control System, please read the
+# header note.
+sdk.dir=/Users/kevin/Library/Android/sdk

examples/whisper.objc/whisper.objc/ViewController.m

@@ -61,7 +61,7 @@ void AudioInputCallback(void * inUserData,
         NSLog(@"Loading model from %@", modelPath);
 
         // create ggml context
-        stateInp.ctx = whisper_init_from_file([modelPath UTF8String]);
+        stateInp.ctx = whisper_init([modelPath UTF8String]);
 
         // check if the model was loaded successfully
         if (stateInp.ctx == NULL) {

examples/whisper.swiftui/README.md

@@ -10,5 +10,3 @@ To use:
 5. Select the "release" build configuration under "Run", then deploy and run to your device.
 
 [^1]: I recommend the tiny, base or small models for running on an iOS device.
-
-![image](https://user-images.githubusercontent.com/1991296/212539216-0aef65e4-f882-480a-8358-0f816838fd52.png)

examples/whisper.swiftui/whisper.cpp.swift/LibWhisper.swift

@@ -55,7 +55,7 @@ actor WhisperContext {
     }
     
     static func createContext(path: String) throws -> WhisperContext {
-        let context = whisper_init_from_file(path)
+        let context = whisper_init(path)
         if let context {
             return WhisperContext(context: context)
         } else {

examples/whisper.swiftui/whisper.swiftui.xcodeproj/project.pbxproj

@@ -35,10 +35,10 @@
 		0AAC5DA029539CD0003032C3 /* WhisperCppDemo.entitlements */ = {isa = PBXFileReference; lastKnownFileType = text.plist.entitlements; path = WhisperCppDemo.entitlements; sourceTree = "<group>"; };
 		0AAC5DA229539CD0003032C3 /* Preview Assets.xcassets */ = {isa = PBXFileReference; lastKnownFileType = folder.assetcatalog; path = "Preview Assets.xcassets"; sourceTree = "<group>"; };
 		0AAC5DC629539EAF003032C3 /* WhisperCppDemo-Bridging-Header.h */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.c.h; path = "WhisperCppDemo-Bridging-Header.h"; sourceTree = "<group>"; };
-		0AAC5DC729539EB0003032C3 /* whisper.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; path = whisper.cpp; sourceTree = "<group>"; };
+		0AAC5DC729539EB0003032C3 /* whisper.cpp */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.cpp.cpp; name = whisper.cpp; path = ../../../whisper.cpp; sourceTree = "<group>"; };
-		0AAC5DC829539EB0003032C3 /* whisper.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = whisper.h; sourceTree = "<group>"; };
+		0AAC5DC829539EB0003032C3 /* whisper.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = whisper.h; path = ../../../whisper.h; sourceTree = "<group>"; };
-		0AAC5DC929539EB0003032C3 /* ggml.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; path = ggml.c; sourceTree = "<group>"; };
+		0AAC5DC929539EB0003032C3 /* ggml.c */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.c; name = ggml.c; path = ../../../ggml.c; sourceTree = "<group>"; };
-		0AAC5DCA29539EB0003032C3 /* ggml.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; path = ggml.h; sourceTree = "<group>"; };
+		0AAC5DCA29539EB0003032C3 /* ggml.h */ = {isa = PBXFileReference; fileEncoding = 4; lastKnownFileType = sourcecode.c.h; name = ggml.h; path = ../../../ggml.h; sourceTree = "<group>"; };
 		0AAC5DCD2953A05C003032C3 /* WhisperState.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = WhisperState.swift; sourceTree = "<group>"; };
 		0AAC5DD02953A394003032C3 /* LibWhisper.swift */ = {isa = PBXFileReference; lastKnownFileType = sourcecode.swift; path = LibWhisper.swift; sourceTree = "<group>"; };
 /* End PBXFileReference section */
@@ -129,8 +129,7 @@
 				0AAC5DC729539EB0003032C3 /* whisper.cpp */,
 				0AAC5DC829539EB0003032C3 /* whisper.h */,
 			);
-			name = whisper.cpp;
+			path = whisper.cpp;
-			path = ../..;
 			sourceTree = "<group>";
 		};
 		0AAC5DCF2953A36C003032C3 /* whisper.cpp.swift */ = {

examples/whisper.wasm/CMakeLists.txt

@@ -8,8 +8,6 @@ add_executable(${TARGET}
     emscripten.cpp
     )
 
-include(DefaultTargetOptions)
-
 target_link_libraries(${TARGET} PRIVATE
     whisper
     )
@@ -32,8 +30,8 @@ set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     --bind \
     -s USE_PTHREADS=1 \
     -s PTHREAD_POOL_SIZE=8 \
-    -s INITIAL_MEMORY=1500MB \
+    -s INITIAL_MEMORY=1024MB \
-    -s TOTAL_MEMORY=1500MB \
+    -s TOTAL_MEMORY=1024MB \
     -s FORCE_FILESYSTEM=1 \
     -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
     ${EXTRA_FLAGS} \

examples/whisper.wasm/emscripten.cpp

@@ -18,7 +18,7 @@ EMSCRIPTEN_BINDINGS(whisper) {
 
         for (size_t i = 0; i < g_contexts.size(); ++i) {
             if (g_contexts[i] == nullptr) {
-                g_contexts[i] = whisper_init_from_file(path_model.c_str());
+                g_contexts[i] = whisper_init(path_model.c_str());
                 if (g_contexts[i] != nullptr) {
                     return i + 1;
                 } else {

examples/whisper.wasm/index-tmpl.html

@@ -50,8 +50,6 @@
                 <button id="fetch-whisper-tiny"    onclick="loadWhisper('tiny')">tiny (75 MB)</button>
                 <button id="fetch-whisper-base-en" onclick="loadWhisper('base.en')">base.en (142 MB)</button>
                 <button id="fetch-whisper-base"    onclick="loadWhisper('base')">base (142 MB)</button>
-                <button id="fetch-whisper-small-en" onclick="loadWhisper('small.en')">small.en (466 MB)</button>
-                <button id="fetch-whisper-small"    onclick="loadWhisper('small')">small (466 MB)</button>
                 <span id="fetch-whisper-progress"></span>
 
                 <input type="file" id="whisper-file" name="file" onchange="loadFile(event, 'whisper.bin')" />
@@ -62,8 +60,8 @@
             <!-- radio button to select between file upload or microphone -->
             <div id="input">
                 Input:
-                <input type="radio" id="file" name="input" value="file" checked="checked" onchange="changeInput('file')" /> <label for="file">File</label>
+                <input type="radio" id="file" name="input" value="file" checked="checked" onchange="changeInput('file')" /> File
-                <input type="radio" id="mic" name="input" value="mic" onchange="changeInput('mic')" /> <label for="mic">Microphone</label>
+                <input type="radio" id="mic" name="input" value="mic" onchange="changeInput('mic')" /> Microphone
             </div>
 
             <br>
@@ -288,10 +286,8 @@
 
                 document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
                 document.getElementById('fetch-whisper-base-en').style.display = 'none';
-                document.getElementById('fetch-whisper-small-en').style.display = 'none';
                 document.getElementById('fetch-whisper-tiny'   ).style.display = 'none';
                 document.getElementById('fetch-whisper-base'   ).style.display = 'none';
-                document.getElementById('fetch-whisper-small'   ).style.display = 'none';
                 document.getElementById('whisper-file'         ).style.display = 'none';
                 document.getElementById('model-whisper-status' ).innerHTML = 'loaded model: ' + file.name;
             }
@@ -302,8 +298,6 @@
                     'tiny':    'https://whisper.ggerganov.com/ggml-model-whisper-tiny.bin',
                     'base.en': 'https://whisper.ggerganov.com/ggml-model-whisper-base.en.bin',
                     'base':    'https://whisper.ggerganov.com/ggml-model-whisper-base.bin',
-                    'small.en': 'https://whisper.ggerganov.com/ggml-model-whisper-small.en.bin',
-                    'small':    'https://whisper.ggerganov.com/ggml-model-whisper-small.bin',
                 };
 
                 let sizes = {
@@ -311,8 +305,6 @@
                     'tiny':    75,
                     'base.en': 142,
                     'base':    142,
-                    'small.en': 466,
-                    'small':    466,
                 };
 
                 let url     = urls[model];
@@ -323,10 +315,8 @@
 
                 document.getElementById('fetch-whisper-tiny-en').style.display = 'none';
                 document.getElementById('fetch-whisper-base-en').style.display = 'none';
-                document.getElementById('fetch-whisper-small-en').style.display = 'none';
                 document.getElementById('fetch-whisper-tiny'   ).style.display = 'none';
                 document.getElementById('fetch-whisper-base'   ).style.display = 'none';
-                document.getElementById('fetch-whisper-small'   ).style.display = 'none';
                 document.getElementById('whisper-file'         ).style.display = 'none';
                 document.getElementById('model-whisper-status' ).innerHTML = 'loading model: ' + model;
 
@@ -339,10 +329,8 @@
                     var el;
                     el = document.getElementById('fetch-whisper-tiny-en'); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-base-en'); if (el) el.style.display = 'inline-block';
-                    el = document.getElementById('fetch-whisper-small-en'); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-tiny'   ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-base'   ); if (el) el.style.display = 'inline-block';
-                    el = document.getElementById('fetch-whisper-small'   ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('whisper-file'         ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('model-whisper-status' ); if (el) el.innerHTML = '';
                 };

extra/bench-all.sh

@@ -12,18 +12,6 @@ fi
 
 models=( "tiny" "base" "small" "medium" "large" )
 
-printf "\n"
-printf "Running memcpy benchmark with 1 thread\n"
-printf "\n"
-
-./bench -w 1 -t 1 2>&1
-
-printf "\n"
-printf "Running ggml_mul_mat benchmark with $n_threads threads\n"
-printf "\n"
-
-./bench -w 2 -t $n_threads 2>&1
-
 printf "\n"
 printf "Running benchmark for all models\n"
 printf "This can take a while!\n"
@@ -68,3 +56,4 @@ for model in "${models[@]}"; do
 
     printf "| <todo> | <todo> | $config | $model | $n_threads | $load_time | $encode_time | $commit |\n"
 done
+

ggml.h

@@ -182,6 +182,8 @@ extern "C" {
 #define GGML_MAX_PARAMS       16
 #define GGML_MAX_CONTEXTS     64
 #define GGML_MAX_OPT          4
+#define GGML_MAX_THREADS      64
+#define GGML_MAX_THREAD_POOLS 16
 
 #ifdef __ARM_NEON
 // we use the built-in 16-bit float type
@@ -301,13 +303,6 @@ struct ggml_cgraph {
     int64_t perf_time_us;
 };
 
-// scratch buffer
-struct ggml_scratch {
-    size_t offs;
-    size_t size;
-    void * data;
-};
-
 struct ggml_init_params {
     // memory pool
     size_t mem_size;   // bytes
@@ -334,8 +329,6 @@ void ggml_free(struct ggml_context * ctx);
 
 size_t ggml_used_mem(const struct ggml_context * ctx);
 
-size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch);
-
 struct ggml_tensor * ggml_new_tensor(
         struct ggml_context * ctx,
         enum   ggml_type type,
@@ -740,8 +733,6 @@ int ggml_cpu_has_f16c(void);
 int ggml_cpu_has_fp16_va(void);
 int ggml_cpu_has_wasm_simd(void);
 int ggml_cpu_has_blas(void);
-int ggml_cpu_has_sse3(void);
-int ggml_cpu_has_vsx(void);
 
 #ifdef  __cplusplus
 }

models/convert-h5-to-ggml.py

@@ -56,7 +56,7 @@ def bytes_to_unicode():
     The reversible bpe codes work on unicode strings.
     This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
     When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
-    This is a significant percentage of your normal, say, 32K bpe vocab.
+    This is a signficant percentage of your normal, say, 32K bpe vocab.
     To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
     And avoids mapping to whitespace/control characters the bpe code barfs on.
     """

models/download-ggml-model.cmd

@@ -40,7 +40,7 @@ if exist "ggml-%model%.bin" (
   goto :eof
 )
 
-PowerShell -NoProfile -ExecutionPolicy Bypass -Command "Invoke-WebRequest -Uri https://huggingface.co/datasets/ggerganov/whisper.cpp/resolve/main/ggml-%model%.bin -OutFile ggml-%model%.bin"
+PowerShell -NoProfile -ExecutionPolicy Bypass -Command "Invoke-WebRequest -Uri https://huggingface.co/datasets/ggerganov/whisper.cpp/raw/main/ggml-%model%.bin -OutFile ggml-%model%.bin"
 
 if %ERRORLEVEL% neq 0 (
   echo Failed to download ggml model %model%

whisper.h

@@ -1,7 +1,6 @@
 #ifndef WHISPER_H
 #define WHISPER_H
 
-#include <stddef.h>
 #include <stdint.h>
 #include <stdbool.h>
 
@@ -41,7 +40,7 @@ extern "C" {
     //
     //     ...
     //
-    //     struct whisper_context * ctx = whisper_init_from_file("/path/to/ggml-base.en.bin");
+    //     struct whisper_context * ctx = whisper_init("/path/to/ggml-base.en.bin");
     //
     //     if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
     //         fprintf(stderr, "failed to process audio\n");
@@ -74,7 +73,6 @@ extern "C" {
         whisper_token tid; // forced timestamp token id
 
         float p;           // probability of the token
-        float plog;        // log probability of the token
         float pt;          // probability of the timestamp token
         float ptsum;       // sum of probabilities of all timestamp tokens
 
@@ -86,20 +84,9 @@ extern "C" {
         float vlen;        // voice length of the token
     } whisper_token_data;
 
-    typedef struct whisper_model_loader {
+    // Allocates all memory needed for the model and loads the model from the given file.
-        void * context;
+    // Returns NULL on failure.
-
+    WHISPER_API struct whisper_context * whisper_init(const char * path_model);
-        size_t (*read)(void * ctx, void * output, size_t read_size);
-        bool    (*eof)(void * ctx);
-        void  (*close)(void * ctx);
-    } whisper_model_loader;
-
-    // Various functions for loading a ggml whisper model.
-    // Allocate (almost) all memory needed for the model.
-    // Return NULL on failure
-    WHISPER_API struct whisper_context * whisper_init_from_file(const char * path_model);
-    WHISPER_API struct whisper_context * whisper_init_from_buffer(void * buffer, size_t buffer_size);
-    WHISPER_API struct whisper_context * whisper_init(struct whisper_model_loader * loader);
 
     // Frees all memory allocated by the model.
     WHISPER_API void whisper_free(struct whisper_context * ctx);
@@ -137,7 +124,6 @@ extern "C" {
     // tokens + n_tokens is the provided context for the decoder.
     // n_past is the number of tokens to use from previous decoder calls.
     // Returns 0 on success
-    // TODO: add support for multiple decoders
     WHISPER_API int whisper_decode(
             struct whisper_context * ctx,
                const whisper_token * tokens,
@@ -145,6 +131,14 @@ extern "C" {
                                int   n_past,
                                int   n_threads);
 
+    // Token sampling methods.
+    // These are provided for convenience and can be used after each call to whisper_decode().
+    // You can also implement your own sampling method using the whisper_get_probs() function.
+    // whisper_sample_best() returns the token with the highest probability
+    // whisper_sample_timestamp() returns the most probable timestamp token
+    WHISPER_API whisper_token_data whisper_sample_best(struct whisper_context * ctx);
+    WHISPER_API whisper_token_data whisper_sample_timestamp(struct whisper_context * ctx, bool is_initial);
+
     // Convert the provided text into tokens.
     // The tokens pointer must be large enough to hold the resulting tokens.
     // Returns the number of tokens on success, no more than n_max_tokens
@@ -183,14 +177,10 @@ extern "C" {
     WHISPER_API int whisper_n_len          (struct whisper_context * ctx); // mel length
     WHISPER_API int whisper_n_vocab        (struct whisper_context * ctx);
     WHISPER_API int whisper_n_text_ctx     (struct whisper_context * ctx);
-    WHISPER_API int whisper_n_audio_ctx    (struct whisper_context * ctx);
     WHISPER_API int whisper_is_multilingual(struct whisper_context * ctx);
 
-    // Token logits obtained from the last call to whisper_decode()
+    // The probabilities for the next token
-    // The logits for the last token are stored in the last row
+    WHISPER_API float * whisper_get_probs(struct whisper_context * ctx);
-    // Rows: n_tokens
-    // Cols: n_vocab
-    WHISPER_API float * whisper_get_logits(struct whisper_context * ctx);
 
     // Token Id -> String. Uses the vocabulary in the provided context
     WHISPER_API const char * whisper_token_to_str(struct whisper_context * ctx, whisper_token token);
@@ -219,8 +209,8 @@ extern "C" {
 
     // Available sampling strategies
     enum whisper_sampling_strategy {
-        WHISPER_SAMPLING_GREEDY,      // similar to OpenAI's GreefyDecoder
+        WHISPER_SAMPLING_GREEDY,      // Always select the most probable token
-        WHISPER_SAMPLING_BEAM_SEARCH, // similar to OpenAI's BeamSearchDecoder
+        WHISPER_SAMPLING_BEAM_SEARCH, // TODO: not implemented yet!
     };
 
     // Text segment callback
@@ -240,17 +230,17 @@ extern "C" {
         enum whisper_sampling_strategy strategy;
 
         int n_threads;
-        int n_max_text_ctx;     // max tokens to use from past text as prompt for the decoder
+        int n_max_text_ctx;
         int offset_ms;          // start offset in ms
         int duration_ms;        // audio duration to process in ms
 
         bool translate;
-        bool no_context;        // do not use past transcription (if any) as initial prompt for the decoder
+        bool no_context;
         bool single_segment;    // force single segment output (useful for streaming)
-        bool print_special;     // print special tokens (e.g. <SOT>, <EOT>, <BEG>, etc.)
+        bool print_special;
-        bool print_progress;    // print progress information
+        bool print_progress;
-        bool print_realtime;    // print results from within whisper.cpp (avoid it, use callback instead)
+        bool print_realtime;
-        bool print_timestamps;  // print timestamps for each text segment when printing realtime
+        bool print_timestamps;
 
         // [EXPERIMENTAL] token-level timestamps
         bool  token_timestamps; // enable token-level timestamps
@@ -260,11 +250,10 @@ extern "C" {
         int   max_tokens;       // max tokens per segment (0 = no limit)
 
         // [EXPERIMENTAL] speed-up techniques
-        // note: these can significantly reduce the quality of the output
         bool speed_up;          // speed-up the audio by 2x using Phase Vocoder
         int  audio_ctx;         // overwrite the audio context size (0 = use default)
 
-        // tokens to provide to the whisper decoder as initial prompt
+        // tokens to provide the whisper model as initial prompt
         // these are prepended to any existing text context from a previous call
         const whisper_token * prompt_tokens;
         int prompt_n_tokens;
@@ -272,35 +261,19 @@ extern "C" {
         // for auto-detection, set to nullptr, "" or "auto"
         const char * language;
 
-        // common decoding parameters:
-        bool suppress_blank;    // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L89
-
-        float temperature;      // initial decoding temperature, ref: https://ai.stackexchange.com/a/32478
-        float max_initial_ts;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/decoding.py#L97
-        float length_penalty;   // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L267
-
-        // fallback parameters
-        // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L274-L278
-        float temperature_inc;
-        float entropy_thold;    // similar to OpenAI's "compression_ratio_threshold"
-        float logprob_thold;
-        float no_speech_thold;  // TODO: not implemented
-
         struct {
-            int best_of;    // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L264
+            int n_past;
         } greedy;
 
         struct {
-            int beam_size;  // ref: https://github.com/openai/whisper/blob/f82bc59f5ea234d4b97fb2860842ed38519f7e65/whisper/transcribe.py#L265
+            int n_past;
-
+            int beam_width;
-            float patience; // TODO: not implemented, ref: https://arxiv.org/pdf/2204.05424.pdf
+            int n_best;
         } beam_search;
 
-        // called for every newly generated text segment
         whisper_new_segment_callback new_segment_callback;
         void * new_segment_callback_user_data;
 
-        // called each time before the encoder starts
         whisper_encoder_begin_callback encoder_begin_callback;
         void * encoder_begin_callback_user_data;
     };
@@ -350,13 +323,6 @@ extern "C" {
     // Get the probability of the specified token in the specified segment.
     WHISPER_API float whisper_full_get_token_p(struct whisper_context * ctx, int i_segment, int i_token);
 
-    ////////////////////////////////////////////////////////////////////////////
-
-    // Temporary helpers needed for exposing ggml interface
-
-    WHISPER_API int whisper_bench_memcpy(int n_threads);
-    WHISPER_API int whisper_bench_ggml_mul_mat(int n_threads);
-
 #ifdef __cplusplus
 }
 #endif