> ## Documentation Index
> Fetch the complete documentation index at: https://doc.rapida.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Silero VAD

> Configure Silero Voice Activity Detection in assistant-api.

[Silero VAD](https://github.com/snakers4/silero-vad) is a pre-trained ONNX model (\~2 MB) for real-time voice activity detection. It is the default VAD provider in Rapida.

**Provider identifier:** `silero_vad`

***

## Source Location

```
api/assistant-api/internal/vad/internal/silero_vad/
├── silero_vad.go        # Main implementation
├── detector.go          # ONNX Runtime inference wrapper
├── models/
│   └── silero_vad_20251001.onnx   # Pre-trained model (~2 MB)
```

***

## How It Works

1. Incoming LINEAR16 bytes are converted to `float32` samples in the range `[-1.0, 1.0]`
2. Samples are fed to the Silero ONNX detector which produces speech segments with start/end timestamps
3. On speech onset, an `InterruptionPacket` is emitted (triggers barge-in)
4. While speech is active, `VadSpeechActivityPacket` heartbeats keep the EOS timer from firing

```go theme={null}
// Simplified flow
samples := linear16ToFloat32(pkt.Audio)
segments, isSpeaking, _ := detector.Detect(samples)

if hasSpeechStart(segments) {
    callback(InterruptionPacket{...})   // barge-in
}
if isSpeaking {
    callback(VadSpeechActivityPacket{}) // EOS timer reset
}
```

***

## Parameters

| Option Key                         | Default | Range   | Description                                  |
| ---------------------------------- | ------- | ------- | -------------------------------------------- |
| `microphone.vad.threshold`         | `0.5`   | 0.3–1.0 | Speech probability threshold                 |
| `microphone.vad.min_silence_frame` | `20`    | 1–30    | Silence frames before segment end (× 10 ms)  |
| `microphone.vad.min_speech_frame`  | `8`     | 1–20    | Speech frames before segment start (× 10 ms) |

Internally, frame counts are converted to milliseconds: `min_silence_frame × 10 = MinSilenceDurationMs`, `min_speech_frame × 10 = SpeechPadMs`.

***

## Model Path

| Source               | Resolution                                                                           |
| -------------------- | ------------------------------------------------------------------------------------ |
| Environment variable | `SILERO_MODEL_PATH` — absolute path to the `.onnx` file                              |
| Default (Docker)     | `./models/silero_vad/silero_vad_20251001.onnx`                                       |
| Default (source)     | `api/assistant-api/internal/vad/internal/silero_vad/models/silero_vad_20251001.onnx` |

***

## Local Source Setup

Silero VAD requires ONNX Runtime. The Docker base image includes it. For local builds:

```bash theme={null}
# macOS (Homebrew)
brew install onnxruntime

# Linux — download from https://github.com/microsoft/onnxruntime/releases
# Extract and set:
export CGO_CFLAGS="-I/opt/onnxruntime/include"
export CGO_LDFLAGS="-L/opt/onnxruntime/lib -lonnxruntime"
export LD_LIBRARY_PATH="/opt/onnxruntime/lib:$LD_LIBRARY_PATH"
```

The model file is checked into the repository — no download needed.