silero vad

Introduction
Silero VAD is a Voice Activity Detection model shared by the ONNX Community on Hugging Face. It utilizes the ONNX framework and is designed to identify human speech within audio data.

Architecture
The model leverages the ONNX format, which is optimized for interoperability across various machine learning frameworks, enabling efficient deployment in diverse environments.

Training
Detailed information about the training process for the Silero VAD model, including datasets and specific methodologies used, is not provided in the README. Users interested in these details are encouraged to explore the community discussions or contact contributors.

Guide: Running Locally

1. Setup Environment: Ensure you have Python and necessary libraries installed. Clone the repository containing the Silero VAD model files.
2. Install Dependencies: Install required dependencies using a package manager, such as pip.
3. Run Model: Use ONNX-compatible libraries to load and run the model on your local machine.
4. Hardware Suggestions: For optimal performance, especially with large datasets or real-time processing, consider using cloud GPUs from providers like AWS, Google Cloud, or Azure.

License
The Silero VAD model is distributed under the MIT license, allowing for modification and distribution with few restrictions.