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45 lines
1.6 KiB
Markdown
45 lines
1.6 KiB
Markdown
# stream
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This is a naive example of performing real-time inference on audio from your microphone.
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The `stream` tool samples the audio every half a second and runs the transcription continously.
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More info is available in [issue #10](https://github.com/ggerganov/whisper.cpp/issues/10).
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```java
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./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
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```
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https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a80f-28ba83be7d09.mp4
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## Sliding window mode with VAD
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Setting the `--step` argument to `0` enables the sliding window mode:
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```java
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./stream -m ./models/ggml-small.en.bin -t 6 --step 0 --length 30000 -vth 0.6
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```
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In this mode, the tool will transcribe only after some speech activity is detected. A very
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basic VAD detector is used, but in theory a more sophisticated approach can be added. The
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`-vth` argument determines the VAD threshold - higher values will make it detect silence more often.
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It's best to tune it to the specific use case, but a value around `0.6` should be OK in general.
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When silence is detected, it will transcribe the last `--length` milliseconds of audio and output
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a transcription block that is suitable for parsing.
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## Building
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The `stream` tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
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```bash
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# Install SDL2 on Linux
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sudo apt-get install libsdl2-dev
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# Install SDL2 on Mac OS
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brew install sdl2
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make stream
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```
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## Web version
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This tool can also run in the browser: [examples/stream.wasm](/examples/stream.wasm)
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