Silero VAD

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

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

// 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:

# 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.

Getting Started

Dashboard (UI)

Web API

Assistant API

Integration API

Endpoint API

Document API

Source Location

How It Works

Parameters

Model Path

Local Source Setup

​Source Location

​How It Works

​Parameters

​Model Path

​Local Source Setup

Source Location

How It Works

Parameters

Model Path

Local Source Setup