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Dimitrii Voronin
2021-01-20 15:18:10 +02:00
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# Silero VAD
![image](https://user-images.githubusercontent.com/36505480/102872739-ce099280-4448-11eb-967b-724440165eb5.png)
![image](https://user-images.githubusercontent.com/36505480/105179755-5eafbd00-5b32-11eb-963d-1eb7461144fb.png)
**Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD), Number Detector and Language Classifier.**
Enterprise-grade Speech Products made refreshingly simple (see our [STT](https://github.com/snakers4/silero-models) models).
@@ -309,7 +308,9 @@ Since our VAD (only VAD, other networks are more flexible) was trained on chunks
[Webrtc](https://github.com/wiseman/py-webrtcvad) splits audio into frames, each frame has corresponding number (0 **or** 1). We use 30ms frames for webrtc, so each 250 ms chunk is split into 8 frames, their **mean** value is used as a treshold for plot.
![image](https://user-images.githubusercontent.com/36505480/102872739-ce099280-4448-11eb-967b-724440165eb5.png)
[Auditok](https://github.com/amsehili/auditok) - logic same as Webrtc, but we use 50ms frames.
![image](https://user-images.githubusercontent.com/36505480/105179755-5eafbd00-5b32-11eb-963d-1eb7461144fb.png)
## FAQ