This project has seen a number of exciting updates recently. A growing number of people and startups are using these Javascript packages to create innovative speech-enabled products and personal projects. I would like to highlight that we now have

• A Discord server for the community.
• New documentation at wiki.vad.ricky0123.com. This documentation can be edited by anyone with a GitHub account. Just log in and create a new page or revise a current one.
• A growing number of generous and talented people have contributed code or opened PRs that I am working my way through. The startup Pleap has also kindly taken on some of the work of reviewing PRs.
• If you would like to contribute, I have started writing some documentation on how to get started hacking on these packages here. If you have any questions, you can open an issue here or leave a message on Discord.
• If you appreciate this work, you can now support me on Github sponsors!
• If you want to share a project, commercial or otherwise, that you made using these packages, let me know and we can mention it in a new section in this readme.

This package aims to provide an accurate, user-friendly voice activity detector (VAD) that runs in the browser. It also has limited support for node. Currently, it runs Silero VAD [1] using ONNX Runtime Web / ONNX Runtime Node.js.

For documentation and a demo, visit vad.ricky0123.com.

To use the VAD via a script tag in the browser, include the following script tags:

<script src="https://cdn.jsdelivr.net/npm/onnxruntime-web/dist/ort.js"></script>
<script src="https://cdn.jsdelivr.net/npm/@ricky0123/[email protected]/dist/bundle.min.js"></script>
<script>
  async function main() {
    const myvad = await vad.MicVAD.new({
      onSpeechStart: () => {
        console.log("Speech start detected")
      },
      onSpeechEnd: (audio) => {
        // do something with `audio` (Float32Array of audio samples at sample rate 16000)...
      }
    })
    myvad.start()
  }
  main()
</script>

Documentation for bundling the voice activity detector for the browser or using it in node or React projects can be found on vad.ricky0123.com.

[1] Silero Team. (2021). Silero VAD: pre-trained enterprise-grade Voice Activity Detector (VAD), Number Detector and Language Classifier. GitHub, GitHub repository, https://github.com/snakers4/silero-vad, [email protected].