base on Silero VAD: pre-trained enterprise-grade Voice Activity Detector [](mailto:[email protected]) [](https://t.me/silero_speech) [](https://github.com/snakers4/silero-vad/blob/master/LICENSE) [](https://pypi.org/project/silero-vad/) [](https://colab.research.google.com/github/snakers4/silero-vad/blob/master/silero-vad.ipynb)  <br/> <h1 align="center">Silero VAD</h1> <br/> **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)). <br/> <p align="center"> <img src="https://github.com/snakers4/silero-vad/assets/36505480/300bd062-4da5-4f19-9736-9c144a45d7a7" /> </p> <details> <summary>Real Time Example</summary> https://user-images.githubusercontent.com/36505480/144874384-95f80f6d-a4f1-42cc-9be7-004c891dd481.mp4 Please note, that video loads only if you are logged in your GitHub account. </details> <br/> <h2 align="center">Fast start</h2> <br/> <details> <summary>Dependencies</summary> System requirements to run python examples on `x86-64` systems: - `python 3.8+`; - 1G+ RAM; - A modern CPU with AVX, AVX2, AVX-512 or AMX instruction sets. Dependencies: - `torch>=1.12.0`; - `torchaudio>=0.12.0` (for I/O only); - `onnxruntime>=1.16.1` (for ONNX model usage). Silero VAD uses torchaudio library for audio I/O (`torchaudio.info`, `torchaudio.load`, and `torchaudio.save`), so a proper audio backend is required: - Option №1 - [**FFmpeg**](https://www.ffmpeg.org/) backend. `conda install -c conda-forge 'ffmpeg<7'`; - Option №2 - [**sox_io**](https://pypi.org/project/sox/) backend. `apt-get install sox`, TorchAudio is tested on libsox 14.4.2; - Option №3 - [**soundfile**](https://pypi.org/project/soundfile/) backend. `pip install soundfile`. If you are planning to run the VAD using solely the `onnx-runtime`, it will run on any other system architectures where onnx-runtume is [supported](https://onnxruntime.ai/getting-started). In this case please note that: - You will have to implement the I/O; - You will have to adapt the existing wrappers / examples / post-processing for your use-case. </details> **Using pip**: `pip install silero-vad` ```python3 from silero_vad import load_silero_vad, read_audio, get_speech_timestamps model = load_silero_vad() wav = read_audio('path_to_audio_file') speech_timestamps = get_speech_timestamps( wav, model, return_seconds=True, # Return speech timestamps in seconds (default is samples) ) ``` **Using torch.hub**: ```python3 import torch torch.set_num_threads(1) model, utils = torch.hub.load(repo_or_dir='snakers4/silero-vad', model='silero_vad') (get_speech_timestamps, _, read_audio, _, _) = utils wav = read_audio('path_to_audio_file') speech_timestamps = get_speech_timestamps( wav, model, return_seconds=True, # Return speech timestamps in seconds (default is samples) ) ``` <br/> <h2 align="center">Key Features</h2> <br/> - **Stellar accuracy** Silero VAD has [excellent results](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics#vs-other-available-solutions) on speech detection tasks. - **Fast** 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. - **Lightweight** JIT model is around two megabytes in size. - **General** 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. - **Flexible 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). - **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. <br/> <h2 align="center">Typical Use Cases</h2> <br/> - Voice activity detection for IOT / edge / mobile use cases - Data cleaning and preparation, voice detection in general - Telephony and call-center automation, voice bots - Voice interfaces <br/> <h2 align="center">Links</h2> <br/> - [Examples and Dependencies](https://github.com/snakers4/silero-vad/wiki/Examples-and-Dependencies#dependencies) - [Quality Metrics](https://github.com/snakers4/silero-vad/wiki/Quality-Metrics) - [Performance Metrics](https://github.com/snakers4/silero-vad/wiki/Performance-Metrics) - [Versions and Available Models](https://github.com/snakers4/silero-vad/wiki/Version-history-and-Available-Models) - [Further reading](https://github.com/snakers4/silero-models#further-reading) - [FAQ](https://github.com/snakers4/silero-vad/wiki/FAQ) <br/> <h2 align="center">Get In Touch</h2> <br/> 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:[email protected]) us, read our [news](https://t.me/silero_news). Please see our [wiki](https://github.com/snakers4/silero-models/wiki) for relevant information and [email](mailto:[email protected]) 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 = {2024}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/snakers4/silero-vad}}, commit = {insert_some_commit_here}, email = {[email protected]} } ``` <br/> <h2 align="center">Examples and VAD-based Community Apps</h2> <br/> - Example of VAD ONNX Runtime model usage in [C++](https://github.com/snakers4/silero-vad/tree/master/examples/cpp) - Voice activity detection for the [browser](https://github.com/ricky0123/vad) using ONNX Runtime Web - [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), [C++](https://github.com/snakers4/silero-vad/tree/master/examples/cpp), [C#](https://github.com/snakers4/silero-vad/tree/master/examples/csharp) and [other](https://github.com/snakers4/silero-vad/tree/master/examples) community examples ", Assign "at most 3 tags" to the expected json: {"id":"10994","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"