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Silero VAD Lite

PyPI Version Supported Python Versions Wheel Support

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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

This should install the package from the provided binary wheels, which are highly recommended. Installing from source is somewhat brittle and requires a C++ compiler.

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, or ctypes.Array.

See docstrings in the code for more details.

License

This project is licensed under the MIT License: see the LICENSE file for details.

Acknowledgments

Contributing

To build Silero VAD Lite from source:

  1. Clone the repository:

    git clone https://github.com/daanzu/py-silero-vad-lite.git
    cd silero-vad-lite
    
  2. 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.

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