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Merge branch 'master' of github.com:snakers4/silero-vad

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2020-12-15 14:30:09 +00:00
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[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/snakers4/silero-vad/blob/master/silero-vad.ipynb)
![header)](https://user-images.githubusercontent.com/12515440/89997349-b3523080-dc94-11ea-9906-ca2e8bc50535.png)
![header](https://user-images.githubusercontent.com/12515440/89997349-b3523080-dc94-11ea-9906-ca2e8bc50535.png)
- [Silero VAD](#silero-vad)
- [Getting Started](#getting-started)
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`Single Image Why our VAD is better than WebRTC`
Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD), Number Detector and Language Classifier.
Enterprise-grade Speech Products made refreshingly simple (all see our [STT](https://github.com/snakers4/silero-models)).
Enterprise-grade Speech Products made refreshingly simple (see our [STT](https://github.com/snakers4/silero-models) models).
Currently, there are hardly any high quality / modern / free / public voice activity detectors except for WebRTC Voice Activity Detector ([link](https://github.com/wiseman/py-webrtcvad)).
Also in enterprise it is crucial to be able to anonymize large-scale spoken corpora (i.e. remove personal data). Typically personal data is considered to be private / sensitive if it contains (i) a name (ii) some private ID. Name recognition is highly subjective and would depend on locale and business case, but Voice Activity and Number detections are quite general tasks.
**Key advantages / features:**
**Key features:**
- Modern, portable;
- Small memory footprint;
- Trained on huge spoken corpora and noise / sound libraries;
- Slower than WebRTC, but sufficiently fast for IOT / edge / mobile applications;
- Lowe memory footprint;
- Superior metrics to WebRTC;
- Trained on huge spoken corpora and noise / sound libraries;
- Slower than WebRTC, but fast enough for IOT / edge / mobile applications;
**Typical use cases:**
- Spoken corpora anonymization;
- Voice detection for IOT / edge / mobile use cases;
- Voice activity detection for IOT / edge / mobile use cases;
- Data cleaning and preparation, number and voice detection in general;
## Getting Started
The models are small enough to be included directly into this repository. Newer models will supersede older models directly.
Currently we provide the following models:
Currently we provide the following functionality:
| | Released |PyTorch | ONNX | VAD | Number Detector | Language Classifier | Languages | Colab |
|----|------------|-------------------|--------------------|---------------------| --------------------|---------------------|-------------------------|-------|
| v1 | 2020-12-15 |:heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | | `ru`, `en`, `de`, `es` | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/snakers4/silero-vad/blob/master/silero-vad.ipynb) |
| PyTorch | ONNX | VAD | Number Detector | Language Clf | Languages | Colab |
|-------------------|--------------------|---------------------|-----------------|--------------|------------------------|-------|
| :heavy_check_mark:| :heavy_check_mark: | :heavy_check_mark: | | | `ru`, `en`, `de`, `es` | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/snakers4/silero-vad/blob/master/silero-vad.ipynb) |
Version history:
**Version history:**
- v1, 2020-12-15, initial release, no Number Detector or Language Classifier heads yet;
| Version | Date | Comment |
|---------|-------------|---------------------------------------------------|
| `v1` | 2020-12-15 | initial release |
| `v2` | coming soon | Add Number Detector or Language Classifier heads |
### PyTorch