whisper.cpp/examples/stream/README.md
2022-12-16 18:04:19 +02:00

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# 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](https://github.com/ggerganov/whisper.cpp/issues/10).
```java
./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:
```java
./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:
```bash
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# Install SDL2 on Mac OS
brew install sdl2
make stream
```
## Web version
This tool can also run in the browser: [examples/stream.wasm](/examples/stream.wasm)