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* examples : reduce initial memory to 512MB This commit reduces the initial memory size to 512MB. This is done to to avoid WebAssembly memory allocation issues on some platforms. It also adds a flag to allow the memory to grow dynamically (up to the maximum). The motivation for this change is that currently the initial memory is set to 2GB which might be to large for some platforms. This will lead to an error being thrown from the JavaScript code generated by Emscripten when trying to allocate memory. More details can be found in the referenced issue below. * examples : set MAXIMUM_MEMORY instead of TOTAL_MEMORY This commit sets MAXIMUM_MEMORY instead of TOTAL_MEMORY in the whisper.wasm example. The motivation for this is that TOTAL_MEMORY and INITIAL_MEMORY are actually the same thing. Instead we want to set MAXIMUM_MEMORY to 2GB. Refs: https://github.com/ggerganov/whisper.cpp/issues/2920 Refs: https://emscripten.org/docs/tools_reference/settings_reference.html#initial-memory |
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| CMakeLists.txt | ||
| emscripten.cpp | ||
| index-tmpl.html | ||
| README.md | ||
whisper.wasm
Inference of OpenAI's Whisper ASR model inside the browser
This example uses a WebAssembly (WASM) port of the whisper.cpp
implementation of the transformer to run the inference inside a web page. The audio data does not leave your computer -
it is processed locally on your machine. The performance is not great but you should be able to achieve x2 or x3
real-time for the tiny and base models on a modern CPU and browser (i.e. transcribe a 60 seconds audio in about
~20-30 seconds).
This WASM port utilizes WASM SIMD 128-bit intrinsics so you have to make sure that your browser supports them.
The example is capable of running all models up to size small inclusive. Beyond that, the memory requirements and
performance are unsatisfactory. The implementation currently support only the Greedy sampling strategy. Both
transcription and translation are supported.
Since the model data is quite big (74MB for the tiny model) you need to manually load the model into the web-page.
The example supports both loading audio from a file and recording audio from the microphone. The maximum length of the audio is limited to 120 seconds.
Live demo
Link: https://whisper.ggerganov.com
Build instructions
# build using Emscripten
git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp
mkdir build-em && cd build-em
emcmake cmake ..
make -j
The example can then be started by running a local HTTP server:
python3 examples/server.py
And then opening a browser to the following URL: http://localhost:8000/whisper.wasm
To run the example in a different server, you need to copy the following files to the server's HTTP path:
# copy the produced page to your HTTP path
cp bin/whisper.wasm/* /path/to/html/
cp bin/libmain.worker.js /path/to/html/