mirror of
https://github.com/snakers4/silero-vad.git
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141 lines
5.6 KiB
Markdown
141 lines
5.6 KiB
Markdown
[](mailto:hello@silero.ai) [](https://t.me/silero_speech) [](https://github.com/snakers4/silero-vad/blob/master/LICENSE)
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[](https://colab.research.google.com/github/snakers4/silero-vad/blob/master/silero-vad.ipynb)
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<br/>
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<h1 align="center">Silero VAD</h1>
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<br/>
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**Silero VAD** - pre-trained enterprise-grade [Voice Activity Detector](https://en.wikipedia.org/wiki/Voice_activity_detection) (also see our [STT models](https://github.com/snakers4/silero-models)).
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<br/>
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<p align="center">
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<img src="https://github.com/snakers4/silero-vad/assets/36505480/300bd062-4da5-4f19-9736-9c144a45d7a7" />
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</p>
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<details>
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<summary>Real Time Example</summary>
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https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-9be7-004c891dd481.mp4
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</details>
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<br/>
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<h2 align="center">Fast start</h2>
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<br/>
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**Using pip**:
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`pip install silero-vad`
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```python3
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from silero_vad import load_silero_vad, read_audio, get_speech_timestamps
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model = load_silero_vad()
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wav = read_audio('path_to_audio_file') # backend (sox, soundfile, or ffmpeg) required!
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speech_timestamps = get_speech_timestamps(wav, model)
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```
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**Using torch.hub**:
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```python3
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import torch
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torch.set_num_threads(1)
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model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad', model='silero_vad')
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(get_speech_timestamps, _, read_audio, _, _) = utils
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wav = read_audio('path_to_audio_file') # backend (sox, soundfile, or ffmpeg) required!
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speech_timestamps = get_speech_timestamps(wav, model)
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```
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<br/>
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<h2 align="center">Key Features</h2>
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<br/>
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- **Stellar accuracy**
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Silero VAD has [excellent results](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#vs-other-available-solutions) on speech detection tasks.
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- **Fast**
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One audio chunk (30+ ms) [takes](https://github.com/snakers4/silero-vad/wiki/Performance-Metrics#silero-vad-performance-metrics) 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.
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- **Lightweight**
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JIT model is around two megabytes in size.
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- **General**
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Silero VAD was trained on huge corpora that include over **6000** languages and it performs well on audios from different domains with various background noise and quality levels.
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- **Flexible sampling rate**
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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).
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- **Highly Portable**
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Silero VAD reaps benefits from the rich ecosystems built around **PyTorch** and **ONNX** running everywhere where these runtimes are available.
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- **No Strings Attached**
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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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<br/>
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<h2 align="center">Typical Use Cases</h2>
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<br/>
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- Voice activity detection for IOT / edge / mobile use cases
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- Data cleaning and preparation, voice detection in general
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- Telephony and call-center automation, voice bots
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- Voice interfaces
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<br/>
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<h2 align="center">Links</h2>
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<br/>
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- [Examples and Dependencies](https://github.com/snakers4/silero-vad/wiki/Examples-and-Dependencies#dependencies)
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- [Quality Metrics](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics)
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- [Performance Metrics](https://github.com/snakers4/silero-vad/wiki/Performance-Metrics)
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- [Versions and Available Models](https://github.com/snakers4/silero-vad/wiki/Version-history-and-Available-Models)
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- [Further reading](https://github.com/snakers4/silero-models#further-reading)
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- [FAQ](https://github.com/snakers4/silero-vad/wiki/FAQ)
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<br/>
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<h2 align="center">Get In Touch</h2>
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<br/>
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Try our models, create an [issue](https://github.com/snakers4/silero-vad/issues/new), start a [discussion](https://github.com/snakers4/silero-vad/discussions/new), join our telegram [chat](https://t.me/silero_speech), [email](mailto:hello@silero.ai) us, read our [news](https://t.me/silero_news).
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Please see our [wiki](https://github.com/snakers4/silero-models/wiki) for relevant information and [email](mailto:hello@silero.ai) us directly.
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**Citations**
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```
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@misc{Silero VAD,
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author = {Silero Team},
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title = {Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD), Number Detector and Language Classifier},
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year = {2021},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/snakers4/silero-vad}},
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commit = {insert_some_commit_here},
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email = {hello@silero.ai}
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}
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```
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<br/>
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<h2 align="center">Examples and VAD-based Community Apps</h2>
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<br/>
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- Example of VAD ONNX Runtime model usage in [C++](https://github.com/snakers4/silero-vad/tree/master/examples/cpp)
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- Voice activity detection for the [browser](https://github.com/ricky0123/vad) using ONNX Runtime Web
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- [Rust](https://github.com/snakers4/silero-vad/tree/master/examples/rust-example), [Go](https://github.com/snakers4/silero-vad/tree/master/examples/go), [Java](https://github.com/snakers4/silero-vad/tree/master/examples/java-example) and [other](https://github.com/snakers4/silero-vad/tree/master/examples) examples
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