Silero VAD Lite
Silero VAD Lite is a lightweight Python wrapper for the high-quality Silero Voice Activity Detection (VAD) model using ONNX Runtime.
- Simple interface to use Silero VAD in Python, supporting streaming audio processing
- Binary wheels for Windows, Linux, and MacOS for easy installation
- Zero dependencies for the installable package, because it includes internally:
- The Silero VAD model in ONNX format, so you don't need to supply it separately
- The C++ ONNX Runtime (CPU), so the Python package for ONNX Runtime is not required
Installation
You can install Silero VAD Lite using pip:
python -m pip install silero-vad-lite
Supported wheel targets are standard (GIL-enabled) CPython 3.10–3.14 on Linux x86-64 (glibc 2.17+), Windows x86-64, and macOS Intel/Apple Silicon. Python 3.6–3.9 are no longer supported; existing older releases remain available. Free-threaded Python, PyPy, musl Linux, and Linux/Windows ARM wheels are not part of the current test matrix.
Wheels include the streaming model from Silero VAD v6.2.3 and ONNX Runtime 1.19.0. See model provenance and compatibility for the pinned upstream source, checksums, and license. Building from a source distribution requires a C++ compiler and network access to download the matching native ONNX Runtime archive; Python build dependencies are installed automatically by pip. Linux and Windows use static ONNX Runtime linking, while macOS uses the shared runtime.
Usage
Here's a simple example of how to use Silero VAD Lite:
from silero_vad_lite import SileroVAD
vad = SileroVAD(16000) # sample_rate = 16000 Hz
speech_probability = vad.process(audio_data)
print(f"Voice activity detection probability of speech: {speech_probability}") # 0 <= speech_probability <= 1
Requirements:
- Sample rate must be either 8000 Hz or 16000 Hz.
- Audio data must be 32-bit float PCM samples, normalized to the range [-1, 1], mono channel.
- Audio data must be supplied with length of 32ms (512 samples for 16kHz, 256 samples for 8kHz).
- Audio data can be supplied as:
bytes,bytearray,memoryview,array.array, orctypes.Array.
See docstrings in the code for more details.
Streaming context and reset
Each instance retains the recurrent state and the preceding 4 ms of audio (64 samples at 16 kHz, 32 samples at 8 kHz), as required by the bundled Silero streaming model. Keep supplying exactly 32 ms per call; do not prepend context yourself. The first window starts with zero context. Releases before 0.3.0 omitted this context. The model update from v5.1 to the v6.2.3 artifact also changes speech probabilities; recheck thresholds tuned against an older release.
Call vad.reset() before an unrelated recording to clear both recurrent state
and audio context without reloading the model. Processing after reset is
identical to using a fresh instance at the same sample rate. Use a separate
instance for each stream, and do not call process() or reset() concurrently
on the same instance.
vad.reset()
probability = vad.process(first_window_of_new_recording)
License
This project is licensed under the MIT License: see the LICENSE file for details. The bundled Silero model is also MIT-licensed; its upstream notice is included in LICENSE.silero in both wheels and source distributions.
Acknowledgments
- Silero Team for the original Silero VAD model
- Microsoft for the ONNX Runtime
Contributing
To build Silero VAD Lite from source:
-
Clone the repository:
git clone https://github.com/daanzu/py-silero-vad-lite.git cd py-silero-vad-lite -
Install the package (editable mode likely won't work):
pip install .[dev]
This will compile the C++ extension and install the package, including the development dependencies for testing, which can be run with:
python -m pytest
Contributions are welcome! Please feel free to submit a Pull Request.
1 maintainer
Metadata
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Release files for silero-vad-lite 0.4.0
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