FDSoundActivatedRecorder is a Swift library for iOS that implements sound-activated audio recording. It automatically starts recording when sound exceeds a dynamic threshold and stops when silence is detected, saving the output as an m4a file with fade-in/fade-out to prevent clicks. The core logic uses a moving average of audio power levels to dynamically adjust trigger thresholds, making it robust to varying noise environments. Built with modern Swift concurrency (actor) for thread safety, it provides a delegate protocol for callbacks and metering updates. The library is self-contained, depends only on standard iOS frameworks, and includes an example app demonstrating integration via SwiftUI.
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.