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Alexander Veysov
2021-12-07 13:11:13 +03:00
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@@ -29,26 +29,27 @@ https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-
- **High accuracy** - **High accuracy**
Silero VAD shows an [excellent result](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#vs-other-available-solutions) for speech detection in streaming tasks. Silero VAD has [excellent results](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#vs-other-available-solutions) on speech detection tasks.
- **Fast** - **Fast**
One audio chunk (30+ ms) [takes](https://github.com/snakers4/silero-vad/wiki/Performance-Metrics#silero-vad-performance-metrics) **1ms** to be processed on a single CPU thread. Using batching and/or GPU one can greatly speed up inference time in production tasks. One audio chunk (30+ ms) [takes](https://github.com/snakers4/silero-vad/wiki/Performance-Metrics#silero-vad-performance-metrics) around **1ms** to be processed on a single CPU thread. Using batching or GPU can also improve performance considerably.
- **Lightweight** - **Lightweight**
JIT model size is less than one megabyte. JIT model is less than one megabyte in size.
- **Generalized** - **General**
Silero VAD was trained on a big corpora that included over **100** languages and performs well on audio of varying backgorund noise levels. 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.
- **Variable sampling rate** - **Flexible sampling rate**
Silero VAD [supports](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#sample-rate-comparison) **8000** and **16000** [sampling rate](https://en.wikipedia.org/wiki/Sampling_(signal_processing)#Sampling_rate) Silero VAD [supports](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#sample-rate-comparison) **8000 Hz** and **16000 Hz** [sampling rates](https://en.wikipedia.org/wiki/Sampling_(signal_processing)#Sampling_rate).
- **Variable chunk size** - **Flexible chunk size**
Model was trained on audio chunks of variable lengths. Chunks of length **30 ms**, **60 ms** and **100 ms** are supported directly, other may perform well too. 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.
<br/> <br/>
<h2 align="center">Typical Use Cases</h2> <h2 align="center">Typical Use Cases</h2>