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Silero VAD v6.2.0, a small voice activity detector by the Silero Team, converted to the GGUF that NeMo-Speech.cpp v0.3.0 loads as its VAD companion. NeMo-Speech.cpp uses it to mask silence before the speech recogniser sees it, and to end utterances.
It was converted for Goscriber, an offline push-to-talk dictation app, and works with any NeMo-Speech.cpp runtime. This is not a Silero Team or NVIDIA release.
| File | Weights | Size (bytes) | SHA-256 |
|---|---|---|---|
silero-vad-v6.2.0.gguf |
F32 | 1,240,224 | 83d702b11378ced4b1bbfcb53394bd00994f7382ff0b9a11b87605dd0898369d |
Pass it next to the ASR model and turn masking on:
nemo-speech transcribe audio.wav --model parakeet-tdt-0.6b-v2.q8_0.gguf \
--vad-model silero-vad-v6.2.0.gguf --vad-masking
Through the C ABI, set model_path and enable_masking in nemo_speech_asr_vad_config. The file holds the 16 kHz model only, and it is not the whisper.cpp Silero GGML format.
Source: the silero-vad 6.2.0 package from PyPI (wheel SHA-256 8a31f1e58e73cdc20820d842f757e678e0ae1b0ee1cb7b8aa50f20f8fd7f7638), which carries the model weights.
Converter: convert_model.py from NeMo-Speech.cpp v0.3.0 (commit 20999cc9), on Python 3.12 with hash-pinned packages.
Command:
python convert_model.py silero --silero-version 6.2.0 --outfile silero-vad-v6.2.0.gguf
Reproduce: scripts/convert-models.sh in Goscriber builds this file and Parakeet TDT 0.6B v2 from scratch in an isolated environment, then checks their SHA-256 against these. See docs/models/gguf.md.
The weights are copied as they are, in F32: nothing is quantised or retrained.
Silero VAD is © 2020-present Silero Team and released under the MIT License. This GGUF is the same model in another file format and keeps that licence: see LICENSE, copied from the silero-vad 6.2.0 package.