v6.2.3

andimarafioti/faster-qwen3-ttsv6.2.3Sep 23, 2026by adamnsandle

Upgrading?

AI Summary

This release makes torchaudio an optional dependency, allowing users to choose between torchaudio, torchcodec, or no audio backend.

Key Highlights

  • Torchaudio is now optional; only torch is required
  • Lazy import of sequence path fixes import errors without onnxruntime
  • Numpy added to onnx-cpu and onnx-gpu dependencies

Breaking Changes

  • Users must now explicitly install a backend (audio, codec, or all) for audio I/O
  • Changing a required dependency to optional is a breaking change for existing users

New Features

  • Support for multiple audio backends (torchaudio or torchcodec)
  • Lazy loading of sequence path to prevent import errors

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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