MinimalSileroVad

Overview

MinimalSileroVad is a .NET implementation for Voice Activity Detection (VAD) and speech segmentation. It uses the Silero VAD AI model to determine if audio input contains speech, providing a lightweight pipeline for detecting and segmenting speech in audio streams or files via ONNX inference. This project is designed for developers needing efficient, real-time voice detection in applications like telephony, voice assistants, or audio processing tools.

Key highlights:

• Minimalist Design: Focuses on core VAD functionality with minimal dependencies.
• AI-Powered Detection: Leverages the Silero VAD neural network model for accurate speech identification.
• ONNX-Based Inference: Utilizes the Silero VAD model exported to ONNX for cross-platform compatibility.
• Extensible: Easy to integrate into larger audio processing pipelines.

This project is ideal for building speech detection components in automated systems, transcription services, or interactive voice applications.

Features

• Voice Activity Detection: Accurately identifies speech segments in audio inputs using AI.
• Speech Segmentation: Breaks down audio into speech and non-speech parts with timestamps.
• Real-Time Processing: Supports streaming audio for live detection.
• Model Compatibility: Uses the pre-trained Silero VAD model via ONNX.
• Customizable Thresholds: Adjust sensitivity for speech detection.
• Logging Support: Includes basic logging for debugging and monitoring.
• Cross-Platform: Runs on .NET environments with GPU/CPU support.

Prerequisites

• .NET SDK (version 8.0 or higher recommended)
• ONNX Runtime (for model inference)
• cuDNN (for GPU acceleration with CUDA-enabled setups)
• CUDA Toolkit (optional, for GPU support; ensure compatibility with ONNX Runtime)
• Optional: NAudio (for microphone input in test projects)

Installation

1. Clone the repository:

   git clone https://github.com/calebtt/MinimalSileroVad.git cd MinimalSileroVad

2. Restore NuGet packages:

   dotnet restore

3. Configure settings:

   • Download the Silero VAD ONNX model if not included (e.g., from the official Silero repository).
   • Place the model file (e.g., silero_vad.onnx) in the appropriate directory or update paths in code.

4. Build the project:

   dotnet build

Usage

1. Run the application:

   dotnet run

2. Process audio:

   • Provide an audio file or stream as input.
   • The tool will output detected speech segments with start/end timestamps.

For advanced customization:

• Modify detection thresholds in the code (e.g., probability threshold for speech).
• Integrate into your application by calling the VAD functions.

Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -m 'Add YourFeature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a Pull Request.

Adhere to modern best practices: Use meaningful commit messages, include unit tests, and follow C# coding standards (e.g., async/await for I/O operations).

License

MIT

Acknowledgments

• Based on the Silero VAD model.
• Utilizes ONNX Runtime for inference.

For questions or issues, open a GitHub issue or reach out via discussions.