voice-activity-detection

A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.

Real-time microphone noise suppression on Linux.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

Automagically synchronize subtitles with video.

Silero VAD: pre-trained enterprise-grade Voice Activity Detector

🔊 A comprehensive list of open-source datasets for voice and sound computing (95+ datasets).

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

Real-time speech recognition and voice activity detection (VAD) using next-gen Kaldi with ncnn without Internet connection. Support iOS, Android, Linux, macOS, Windows, Raspberry Pi, VisionFive2, LicheePi4A etc.

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

A python package to build AI-powered real-time audio applications

💎 A list of accessible speech corpora for ASR, TTS, and other Speech Technologies

Python AI assistant 🧠

The Open Source Alternative to Cluely - A lightning-fast, privacy-first AI assistant that works seamlessly during meetings, interviews, and conversations without anyone knowing. Built with Tauri for native performance, just 10MB. Completely undetectable in video calls, screen shares, and recordings.

Voice activity detection (VAD) toolkit including DNN, bDNN, LSTM and ACAM based VAD. We also provide our directly recorded dataset.

CNN-based audio segmentation toolkit. Allows to detect speech, music, noise and speaker gender. Has been designed for large scale gender equality studies based on speech time per gender.

An audio/acoustic activity detection and audio segmentation tool

Native Swift and CoreML SDK for local speaker diarization, VAD, and speech-to-text for real-time workloads. Works on iOS and macOS.

Automatically synchronize and translate subtitles, or create new ones by transcribing, using pre-trained DNNs, Forced Alignments and Transformers. https://subaligner.readthedocs.io/

An Optimized Speech-to-Text Pipeline for the Whisper Model Supporting Multiple Inference Engine

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