Silero VAD: pre-trained enterprise-grade Voice Activity Detector
Silero VAD - pre-trained enterprise-grade Voice Activity Detector (also see our STT models).
Stellar accuracy
Silero VAD has excellent results on speech detection tasks.
Fast
One audio chunk (30+ ms) takes less than 1ms to be processed on a single CPU thread. Using batching or GPU can also improve performance considerably. Under certain conditions ONNX may even run up to 4-5x faster.
Lightweight
JIT model is around 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 30 ms. Longer chunks are supported directly, others may work as well.
Highly Portable
Silero VAD reaps benefits from the rich ecosystems built around PyTorch and ONNX running everywhere where these runtimes are available.
No Strings Attached
Published under permissive license (MIT) Silero VAD has zero strings attached - no telemetry, no keys, no registration, no built-in expiration, no keys or vendor lock.
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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 = {[email protected]}
}