> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/XDcobra/react-native-sherpa-onnx/llms.txt
> Use this file to discover all available pages before exploring further.

# VAD (Voice Activity Detection)

> Voice activity detection API (coming soon)

<Note>
  Voice Activity Detection (VAD) API is planned for a future release.
</Note>

## Overview

Voice Activity Detection (VAD) is a technique for detecting the presence or absence of human speech in an audio signal. It's commonly used to:

* Reduce computational load by processing only speech segments
* Improve speech recognition accuracy by filtering out silence and noise
* Enable push-to-talk and voice-triggered applications
* Optimize audio streaming and bandwidth

## Planned Features

The VAD API will provide:

* **Real-time voice detection**: Detect speech in live audio streams
* **Batch processing**: Analyze audio files for speech segments
* **Configurable sensitivity**: Adjust detection thresholds
* **Multiple VAD models**: Support for different VAD architectures
* **Integration with STT**: Seamless integration with speech recognition

## Expected Usage (Preview)

```typescript theme={null}
import { createVAD, assetModelPath } from 'react-native-sherpa-onnx/vad';
import { createPcmLiveStream } from 'react-native-sherpa-onnx/audio';

// Create VAD instance
const vad = await createVAD({
  modelPath: assetModelPath('models/silero-vad'),
});

// Process live audio
const mic = createPcmLiveStream({ sampleRate: 16000 });

mic.onData(async (samples, sampleRate) => {
  const isSpeech = await vad.detectSpeech(samples, sampleRate);
  
  if (isSpeech) {
    console.log('Speech detected');
    // Process audio with STT
  }
});

await mic.start();

// Later: cleanup
await mic.stop();
await vad.destroy();
```

## Model Support

Planned support for popular VAD models:

* **Silero VAD**: Lightweight and accurate VAD model
* **WebRTC VAD**: Fast, low-latency detection
* **Custom models**: Bring your own ONNX VAD models

## Integration Example

Combining VAD with streaming STT:

```typescript theme={null}
import { createVAD } from 'react-native-sherpa-onnx/vad';
import { createStreamingSTT } from 'react-native-sherpa-onnx/stt';
import { createPcmLiveStream } from 'react-native-sherpa-onnx/audio';

const vad = await createVAD({ /* ... */ });
const stt = await createStreamingSTT({ /* ... */ });
const stream = await stt.createStream();

const mic = createPcmLiveStream({ sampleRate: 16000 });

mic.onData(async (samples, sampleRate) => {
  const isSpeech = await vad.detectSpeech(samples, sampleRate);
  
  if (isSpeech) {
    // Only process speech segments
    const { result, isEndpoint } = await stream.processAudioChunk(
      samples,
      sampleRate
    );
    
    console.log('Transcription:', result.text);
  }
});
```

## Availability

This API is not yet implemented. Track progress on the [react-native-sherpa-onnx GitHub repository](https://github.com/k2-fsa/react-native-sherpa-onnx).

## See Also

* [Streaming STT](/api/stt/streaming-stt) - Real-time speech recognition
* [Audio Utilities](/api/audio) - Audio capture and processing
* [Diarization API](/api/diarization) - Speaker identification (planned)