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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