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--- |
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pipeline_tag: voice-activity-detection |
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license: bsd-2-clause |
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tags: |
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- speech-processing |
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- semantic-vad |
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- multilingual |
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datasets: |
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- pipecat-ai/smart-turn-data-v3.1-train |
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- pipecat-ai/smart-turn-data-v3.1-test |
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--- |
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# Smart Turn v3.x |
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**Smart Turn** is an open‑source semantic Voice Activity Detection (VAD) model that tells you whether a speaker has finished their turn by analysing the raw waveform, not the transcript. |
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## Links |
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* [Blog post: Smart Turn v3](https://www.daily.co/blog/announcing-smart-turn-v3-with-cpu-inference-in-just-12ms/) |
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* [GitHub repo](https://github.com/pipecat-ai/smart-turn) with training and inference code, and more information |
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* [Datasets](https://huggingface.co/pipecat-ai/datasets) |
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## Model architecture |
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* Backbone: Whisper Tiny encoder |
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* Head: shallow linear classifier |
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* Params: 8M |
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* Checkpoint: 8 MB ONNX (int8 quantized), 32MB ONNX (unquantized) |
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## How to use |
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Please see the blog post and GitHub repo for more information on using the model, either standalone or with Pipecat. |
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## Thanks |
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Thank you to the following organisations for contributing audio datasets: |
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- [Liva AI](https://www.theliva.ai/) |
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- [Midcentury](https://www.midcentury.xyz/) |
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- [MundoAI](https://mundoai.world/) |
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