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--pcm-input option information

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Quentin Fuxa 2025-09-17 16:06:28 +02:00
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@ -80,8 +80,8 @@ See **Parameters & Configuration** below on how to use them.
# Large model and translate from french to danish
whisperlivekit-server --model large-v3 --language fr --target-language da
# Advanced configuration with diarization and language
whisperlivekit-server --host 0.0.0.0 --port 8000 --model medium --diarization --language fr
# Diarization and server listening on */80
whisperlivekit-server --host 0.0.0.0 --port 80 --model medium --diarization --language fr
```
@ -135,6 +135,7 @@ async def websocket_endpoint(websocket: WebSocket):
| `--language` | List [here](https://github.com/QuentinFuxa/WhisperLiveKit/blob/main/whisperlivekit/simul_whisper/whisper/tokenizer.py). If you use `auto`, the model attempts to detect the language automatically, but it tends to bias towards English. | `auto` |
| `--target-language` | If sets, activates translation using NLLB. Ex: `fr`. [118 languages available](https://github.com/QuentinFuxa/WhisperLiveKit/blob/main/whisperlivekit/translation/mapping_languages.py). If you want to translate to english, you should rather use `--task translate`, since Whisper can do it directly. | `None` |
| `--task` | Set to `translate` to translate *only* to english, using Whisper translation. | `transcribe` |
| `--diarization` | Enable speaker identification | `False` |
| `--backend` | Processing backend. You can switch to `faster-whisper` if `simulstreaming` does not work correctly | `simulstreaming` |
| `--no-vac` | Disable Voice Activity Controller | `False` |
| `--no-vad` | Disable Voice Activity Detection | `False` |
@ -144,8 +145,18 @@ async def websocket_endpoint(websocket: WebSocket):
| `--ssl-certfile` | Path to the SSL certificate file (for HTTPS support) | `None` |
| `--ssl-keyfile` | Path to the SSL private key file (for HTTPS support) | `None` |
| `--pcm-input` | raw PCM (s16le) data is expected as input and FFmpeg will be bypassed. Frontend will use AudioWorklet instead of MediaRecorder | `False` |
| `--min-chunk-size` | Minimum audio chunk size (seconds), used by different sections of WLK | `0.5` |
| Translation options | Description | Default |
|-----------|-------------|---------|
| `--nllb-backend` | `transformers` or `ctranslate2` | `ctranslate2` |
| `--nllb-size` | `600M` or `1.3B` | `600M` |
| Diarization options | Description | Default |
|-----------|-------------|---------|
| `--diarization-backend` | `diart` or `sortformer` | `sortformer` |
| `--disable-punctuation-split` | Disable punctuation based splits. See #214 | `False` |
| `--segmentation-model` | Hugging Face model ID for Diart segmentation model. [Available models](https://github.com/juanmc2005/diart/tree/main?tab=readme-ov-file#pre-trained-models) | `pyannote/segmentation-3.0` |
| `--embedding-model` | Hugging Face model ID for Diart embedding model. [Available models](https://github.com/juanmc2005/diart/tree/main?tab=readme-ov-file#pre-trained-models) | `speechbrain/spkrec-ecapa-voxceleb` |
| SimulStreaming backend options | Description | Default |
|-----------|-------------|---------|
@ -164,30 +175,16 @@ async def websocket_endpoint(websocket: WebSocket):
| `--preload-model-count` | Optional. Number of models to preload in memory to speed up loading (set up to the expected number of concurrent users) | `1` |
| WhisperStreaming backend options | Description | Default |
|-----------|-------------|---------|
| `--confidence-validation` | Use confidence scores for faster validation | `False` |
| `--buffer_trimming` | Buffer trimming strategy (`sentence` or `segment`) | `segment` |
| Diarization options | Description | Default |
|-----------|-------------|---------|
| `--diarization` | Enable speaker identification | `False` |
| `--diarization-backend` | `diart` or `sortformer` | `sortformer` |
| `--disable-punctuation-split` | Disable punctuation based splits. See #214 | `False` |
| `--segmentation-model` | Hugging Face model ID for Diart segmentation model. [Available models](https://github.com/juanmc2005/diart/tree/main?tab=readme-ov-file#pre-trained-models) | `pyannote/segmentation-3.0` |
| `--embedding-model` | Hugging Face model ID for Diart embedding model. [Available models](https://github.com/juanmc2005/diart/tree/main?tab=readme-ov-file#pre-trained-models) | `speechbrain/spkrec-ecapa-voxceleb` |
| Translation options | Description | Default |
|-----------|-------------|---------|
| `--nllb-backend` | `transformers` or `ctranslate2` | `ctranslate2` |
| `--nllb-size` | `600M` or `1.3B` | `600M` |
> For diarization using Diart, you need access to pyannote.audio models:
> 1. [Accept user conditions](https://huggingface.co/pyannote/segmentation) for the `pyannote/segmentation` model
> 2. [Accept user conditions](https://huggingface.co/pyannote/segmentation-3.0) for the `pyannote/segmentation-3.0` model
> 3. [Accept user conditions](https://huggingface.co/pyannote/embedding) for the `pyannote/embedding` model
>4. Login with HuggingFace: `huggingface-cli login`
> For diarization using Diart, you need to accept user conditions [here](https://huggingface.co/pyannote/segmentation) for the `pyannote/segmentation` model, [here](https://huggingface.co/pyannote/segmentation-3.0) for the `pyannote/segmentation-3.0` model and [here](https://huggingface.co/pyannote/embedding) for the `pyannote/embedding` model. **Then**, login to HuggingFace: `huggingface-cli login`
### 🚀 Deployment Guide