whisper.cpp/examples/stream
Georgi Gerganov d17e7139d8
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stream : update build instructions
2024-12-15 21:55:36 +02:00
..
CMakeLists.txt whisper : add GPU support via cuBLAS (#834) 2023-04-30 12:14:33 +03:00
README.md stream : update build instructions 2024-12-15 21:55:36 +02:00
stream.cpp whisper : reorganize source code + improve CMake (#2256) 2024-06-26 19:34:09 +03:00

stream

This is a naive example of performing real-time inference on audio from your microphone. The stream tool samples the audio every half a second and runs the transcription continously. More info is available in issue #10.

./build/bin/stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000

https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a80f-28ba83be7d09.mp4

Sliding window mode with VAD

Setting the --step argument to 0 enables the sliding window mode:

 ./build/bin/stream -m ./models/ggml-small.en.bin -t 6 --step 0 --length 30000 -vth 0.6

In this mode, the tool will transcribe only after some speech activity is detected. A very basic VAD detector is used, but in theory a more sophisticated approach can be added. The -vth argument determines the VAD threshold - higher values will make it detect silence more often. It's best to tune it to the specific use case, but a value around 0.6 should be OK in general. When silence is detected, it will transcribe the last --length milliseconds of audio and output a transcription block that is suitable for parsing.

Building

The stream tool depends on SDL2 library to capture audio from the microphone. You can build it like this:

# Install SDL2
# On Debian based linux distributions:
sudo apt-get install libsdl2-dev

# On Fedora Linux:
sudo dnf install SDL2 SDL2-devel

# Install SDL2 on Mac OS
brew install sdl2

cmake -B build -DWHISPER_SDL2=ON
cmake --build build --config Release

./build/bin/stream

Web version

This tool can also run in the browser: examples/stream.wasm