Silero VAD

Silero VAD - pre-trained enterprise-grade Voice Activity Detector (also see our STT models).

Real Time Example

https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-9be7-004c891dd481.mp4

Key Features

• High accuracy

  Silero VAD has excellent results on speech detection tasks.

• Fast

  One audio chunk (30+ ms) takes around 1ms to be processed on a single CPU thread. Using batching or GPU can also improve performance considerably.

• Lightweight

  JIT model is less than one megabyte in size.

• General

  Silero VAD was trained on huge corpora that include over 100 languages and it performs well on audios from different domains with various background noise and quality levels.

• Flexible sampling rate

  Silero VAD supports 8000 Hz and 16000 Hz sampling rates.

• Flexible chunk size

  Model was trained on audio chunks of different lengths. 30 ms, 60 ms and 100 ms long chunks are supported directly, others may work as well.

Typical Use Cases

• Voice activity detection for IOT / edge / mobile use cases
• Data cleaning and preparation, voice detection in general

Links

• Examples and Dependencies
• Quality Metrics
• Performance Metrics
• Number Detector and Language classifier models
• Versions and Available Models

Get In Touch

Try our models, create an issue, start a discussion, join our telegram chat, email us, read our news. Please see our wiki and tiers for relevant information and email us directly.

Please see our wiki and tiers for relevant information and email us directly.

Citations

@misc{Silero VAD,
  author = {Silero Team},
  title = {Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD), Number Detector and Language Classifier},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/snakers4/silero-vad}},
  commit = {insert_some_commit_here},
  email = {hello@silero.ai}
}