Silero VAD v5 MLX EU AI Act Compliance Profile

Silero VAD v5 — MLX

MLX-compatible weights for Silero VAD v5, converted from the official JIT model.

Model

Silero VAD v5 is a lightweight (~309K params) voice activity detection model that processes 512-sample chunks (32ms @ 16kHz) with sub-millisecond latency. It outputs a speech probability between 0 and 1 for each chunk, with LSTM state carried across chunks for streaming operation.

Architecture: STFT → 4×Conv1d+ReLU encoder → LSTM(128) → Conv1d decoder → sigmoid

Usage (Swift / MLX)

import SpeechVAD

// Load model
let vad = try await SileroVADModel.fromPretrained()

// Streaming: process 512-sample chunks
let prob = vad.processChunk(samples)  // → 0.0...1.0

// Batch: detect speech segments in complete audio
let segments = vad.detectSpeech(audio: samples, sampleRate: 16000)
for seg in segments {
    print("Speech: \(seg.startTime)s - \(seg.endTime)s")
}

Part of speech-swift.

Conversion

python3 scripts/convert_silero_vad.py --upload

Converts the official Silero VAD v5 JIT model via torch.hub, transposes Conv1d weights for MLX channels-last format, sums LSTM biases (bias_ih + bias_hh), and saves as safetensors.

Weight Mapping

| JIT Key | MLX Key | Shape | |---------|---------|-------| | _model.stft.forward_basis_buffer | stft.weight | [258, 256, 1] | | _model.encoder.{i}.reparam_conv.weight | encoder.{i}.weight | varies | | _model.encoder.{i}.reparam_conv.bias | encoder.{i}.bias | varies | | _model.decoder.rnn.weight_ih | lstm.Wx | [512, 128] | | _model.decoder.rnn.weight_hh | lstm.Wh | [512, 128] | | _model.decoder.rnn.bias_ih + bias_hh | lstm.bias | [512] | | _model.decoder.decoder.2.weight | decoder.weight | [1, 1, 128] | | _model.decoder.decoder.2.bias | decoder.bias | [1] |

License

The original Silero VAD model is released under the [MIT License](https://github.com/snakers4/sile

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Tags

Library

Base Model