This is a naive example of performing real-time inference on audio from your microphone.
The whisper-stream
tool samples the audio every half a second and runs the transcription continously.
More info is available in issue #10.
./build/bin/whisper-stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
rt_esl_csgo_2.mp4
Setting the --step
argument to 0
enables the sliding window mode:
./build/bin/whisper-stream -m ./models/ggml-base.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.
The whisper-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/whisper-stream
This tool can also run in the browser: examples/stream.wasm