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---
pipeline_tag: voice-activity-detection
license: bsd-2-clause
tags:
- speech-processing
- semantic-vad
- multilingual
datasets:
- pipecat-ai/smart-turn-data-v3.1-train
- pipecat-ai/smart-turn-data-v3.1-test
---
# Smart Turn v3.x
**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.
## Links
* [Blog post: Smart Turn v3](https://www.daily.co/blog/announcing-smart-turn-v3-with-cpu-inference-in-just-12ms/)
* [GitHub repo](https://github.com/pipecat-ai/smart-turn) with training and inference code, and more information
* [Datasets](https://huggingface.co/pipecat-ai/datasets)
## Model architecture
* Backbone: Whisper Tiny encoder
* Head: shallow linear classifier
* Params: 8M
* Checkpoint: 8 MB ONNX (int8 quantized), 32MB ONNX (unquantized)
## How to use
Please see the blog post and GitHub repo for more information on using the model, either standalone or with Pipecat.
## Thanks
Thank you to the following organisations for contributing audio datasets:
- [Liva AI](https://www.theliva.ai/)
- [Midcentury](https://www.midcentury.xyz/)
- [MundoAI](https://mundoai.world/)
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