Popular GitHub Repositories for Vocal Separation

Deezer source separation library including pretrained models.

GUI for a Vocal Remover that uses Deep Neural Networks.

A PyTorch-based Speech Toolkit

End-to-End Speech Processing Toolkit

Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2E, F5-TTS, CosyVoice), with Whisper audio processing, RVC voice changer, YouTube download, UVR5 vocal isolation, and multilingual translation.

An AI-Powered Speech Processing Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Enhancement, Separation, and Target Speaker Extraction, etc.

The PyTorch-based audio source separation toolkit for researchers

Whisper & Faster-Whisper standalone executables for those who don't want to bother with Python.

Vocal Remover using Deep Neural Networks

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

All in One Version : Youtube WAV Download, Separating Vocal, Splitting Audio, Training, and Inference Using Google Colab

A curated list of different papers and datasets in various areas of audio-visual processing

Implementation of Band Split Roformer, SOTA Attention network for music source separation out of ByteDance AI Labs

PyTorch implementation of "FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancement."

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

UniSpeech - Large Scale Self-Supervised Learning for Speech

The dataset of Speech Recognition

Tools for Speech Enhancement integrated with Kaldi

Cross-platform speech toolset, used from the command-line or as a Node.js library. Includes a variety of engines for speech synthesis, speech recognition, forced alignment, speech translation, voice isolation, language detection and more.

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.