v6.2.3

Gen-Verse/MMaDAv6.2.3Sep 23, 2026by adamnsandle

Upgrading?

AI Summary

This release makes the `torchaudio` dependency optional, requiring users to explicitly install a backend like `silero-vad[audio]` if they need audio I/O. It also addresses import errors related to `onnxruntime` and improves dependency management for the library.

Key Highlights

  • torchaudio is now an optional dependency (only torch is required).
  • Explicit backend installation options: `[audio]`, `[codec]`, or `[all]`.
  • Fixed import errors when `onnxruntime` is not installed by lazy-loading the sequence path.
  • `read_audio` / `save_audio` helpers now support multiple backends.

Breaking Changes

  • torchaudio is now optional; users must install an extra (e.g., `[audio]`) to use audio I/O helpers.

New Features

  • Support for `silero-vad[audio]` (torchaudio) and `silero-vad[codec]` (torchcodec) extras.
  • Lazy import of the sequence path for `onnxruntime` compatibility.
  • Explicit declaration of `numpy` in `[onnx-cpu]` and `[onnx-gpu]` extras.

Full Release Notes

torchaudio is now an optional dependency instead of required. Only torch is required — the model itself never used torchaudio, only the `read_audio` / `save_audio` helpers did.

Users who need audio I/O must now install a backend explicitly:

- `pip install silero-vad[audio]` (torchaudio)
- `pip install silero-vad[codec]` (torchcodec)
- `pip install silero-vad[all]` (everything)

Key changes:

- `read_audio` / `save_audio` now work with either torchaudio or torchcodec; with neither installed they raise an error naming the extra to install
- Fixed: `import silero_vad` failed when onnxruntime was not installed — the sequence path is now imported lazily
- numpy is now declared in [onnx-cpu] / [onnx-gpu]

If you load audio yourself, no backend is needed at all:

```python3
from silero_vad import load_silero_vad, get_speech_timestamps

model = load_silero_vad()
audio = ...                                      # 1-D float32 torch.Tensor from any source
ts = get_speech_timestamps(audio, model, return_seconds=True)
```

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