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idle-intelligence/silero-vad-v5-safetensors
silero-vad-v5-safetensors is a voice activity detection model from idle-intelligence. Use it for the voice activity detection task on the model card, and read the license before you ship it in a product. It is set up for silero-vad. The card lists the license as mit.
Silero Voice Activity Detection v5, converted from ONNX to safetensors format for use with candle / Rust inference.
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From the Hugging Face model README
Silero Voice Activity Detection v5, converted from ONNX to safetensors format for use with candle / Rust inference.
Original model: snakers4/silero-vad (MIT License)
| Task | Voice Activity Detection |
| Input | 16 kHz mono PCM, 512 samples per call (32 ms) |
| Output | Speech probability ∈ [0, 1] |
| Size | 1.2 MB |
| Format | safetensors (f32) |
Input: [batch, 576] (64 context + 512 audio samples)
→ Reflection pad (64 samples, right only) → [batch, 1, 640]
→ Conv1d(1, 258, k=256, stride=128) → STFT → magnitude [batch, 129, 4]
→ Conv1d(129, 128, k=3, pad=1) + ReLU
→ Conv1d(128, 64, k=3, stride=2, pad=1) + ReLU
→ Conv1d(64, 64, k=3, stride=2, pad=1) + ReLU
→ Conv1d(64, 128, k=3, pad=1) + ReLU
→ LSTM(128, 128) → ReLU
→ Conv1d(128, 1, k=1) + Sigmoid → probability
The model is stateful — LSTM hidden/cell state and a 64-sample context buffer carry across calls.
| Tensor | Shape |
|---|---|
stft.conv.weight | [258, 1, 256] |
encoder.{0-3}.conv.weight | Conv weights (BN-fused / reparameterized) |
encoder.{0-3}.conv.bias | Conv biases |
decoder.lstm.weight_ih_l0 | [512, 128] |
decoder.lstm.weight_hh_l0 | [512, 128] |
decoder.lstm.bias_ih_l0 | [512] |
decoder.lstm.bias_hh_l0 | [512] |
decoder.output.weight | [1, 128, 1] |
decoder.output.bias | [1] |
Used by vad-rs for client-side speech detection in the browser (via WASM + candle-core). See the original silero-vad repository for Python/ONNX usage examples and documentation.
| Parameter | Default |
|---|---|
| Speech start | probability ≥ 0.5 |
| Speech end | probability < 0.35 |
MIT (same as original Silero VAD)