Voice Activity Detector (VAD) : low-latency, high-performance and lightweight

Voice activity detector (VAD) for the browser with a simple API

Android Voice Activity Detection (VAD) library. Supports WebRTC VAD GMM, Silero VAD DNN, Yamnet VAD DNN models.

Very fast, accurate speaker diarization

AI Speech Solutions for Tasks such as ASR, Vocal Extraction, Accompaniment Extraction, Audio Denoising, and Enhancement, Support models such as paraformer, sensevoice, fireredasr, zipformer, moonshine, wenet, whisper, fsmn-vad, silero-vad, CT Transformer punc, Spleeter, Uvr5, etc, apply ONNX models in various scenarios.

A real-time Voice Activity Detection (VAD) library for iOS and macOS using Silero models powered by ONNX Runtime. Includes advanced noise suppression and audio preprocessing with WebRTC APM, supporting seamless WAV data output with header metadata.

iOS Voice Activity Detection (VAD). Supports WebRTC VAD GMM, Silero VAD DNN, Yamnet VAD DNN models.

Tool for speech recognition using sensevoice-small

In this repository, I show you how to use SILERO VAD with ONNX-WEB runtime to run the VAD compeletely in the browser.

A sophisticated real-time voice assistant that seamlessly integrates speech recognition, AI reasoning, and neural text-to-speech synthesis. It is designed for natural conversational interactions with advanced tool-calling capabilities.

VAD is a cross-platform Dart binding for the VAD JavaScript library. This package provides access to a Voice Activity Detection (VAD) system, allowing Flutter applications to start and stop VAD-based listening and handle various VAD events.

Audio transcription using mlx whisper and vad silence processing

Uses the excellent silero VAD with onnxruntime C api for fast detection of audio segments with speech

Python script for detect silences with Silero-VAD and transcribing with the whisper AI model.

This repo provides an addon that can perform VAD model reasoning in nodes and electric environments, based on cmake-js and Fastdeploy. Silero VAD is a pre-trained enterprise-grade Voice Activity Detector.

C++ implementation of real-time Voice Activity Detection (VAD) using Silero models with ONNX Runtime and WebRTC Audio Processing. Provides precise voice segmentation and cross-platform XCFramework support.

Real-time speech-to-text translation over WebSocket. Streams Opus or raw PCM audio from client to server for live transcription and optional translation. Supports CLI and Python API.

Real-time Voice Activity Detection (VAD) library for Android using Silero models powered by ONNX Runtime. Includes advanced noise suppression and audio preprocessing with WebRTC APM, supporting seamless WAV data output with header metadata.

Experimental voice user interface (VUI) to interact with an agentic AI assistant

Test comparison of two VAD models with English and multilingual speech datasets