silero-vad

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

Speech synthesis, speech recognition and voice activity detection for voice conversation, in C++ on ggml: Qwen3-TTS, Irodori-TTS, Qwen3-ASR, ReazonSpeech, parakeet and Silero VAD on Metal, Vulkan and the CPU, with an OpenAI-compatible server and live transcription.

Speech-to-Text based on SileroVAD + whisper.cpp (GGML Whisper) for ROS 2

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.

Real-time on-device speech translation for macOS. Silero VAD + Qwen3-ASR-1.7B + Qwen3.5 (MLX) on Apple Silicon. No cloud, no API keys, no telemetry.

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

Tool for speech recognition using sensevoice-small

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.

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

Voice Activity Detection library for Rust with a unified trait interface over multiple backends (WebRTC VAD, Silero). Includes vad-lab, a web-based tool for live experimentation and comparison.

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.

Production-ready batch inference for Cohere’s Arabic/English ASR model, with optimized Silero VAD, multi-file GPU batching, subtitles, and optional word-level timestamps.

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

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.

High-throughput Silero VAD inference for CPU with multi-window ONNX execution and an optimized RFFT frontend.

Real-time speech-to-text clipboard tool with Silero VAD and local ASR support