Silero VAD is a pre-trained enterprise-grade Voice Activity Detector library that provides speech detection capabilities for audio signals. The system consists of a core PyTorch model (also available in ONNX format) with Python utilities for audio processing, speech timestamp extraction, and streaming applications. It supports 8kHz and 16kHz sampling rates and includes a VADIterator class for real-time processing. The repository offers multi-language examples (C++, C#, Go, Haskell, Java, Rust) demonstrating integration, along with tools for model tuning and sequence-based ONNX optimization for improved performance on long audio files.
This repository contains a C-based frequency scanner for Gqrx, a software-defined radio (SDR) application. The scanner controls Gqrx via its remote TCP protocol to perform sweep or bookmark-based scanning, with integrated voice activity detection (VAD) for distinguishing speech from noise. The system supports interactive controls (skip, ban, pause frequencies) and automatic recording of detected signals. The architecture is a standalone CLI executable built with CMake, featuring two scanning modes: adaptive sweep (fast, with fine-tuning) and bookmark-based (reading Gqrx's bookmarks CSV). VAD is implemented using a G.729B-style pitch-based algorithm with LPC analysis, running on Linux via PipeWire audio capture. The codebase includes a comprehensive test suite using cmocka, with mock socket infrastructure for simulating Gqrx responses. Notable strengths include self-contained VAD modules and a reusable mock Gqrx protocol implementation. However, the code exhibits heavy use of global variables, some known bugs (e.g., unsigned underflow in frequency saving), and platform-specific limitations (VOX and sweep tests are Linux-only).