audio-processing

Cross-platform, customizable ML solutions for live and streaming media.

Deezer source separation library including pretrained models.

A PyTorch-based Speech Toolkit

A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.

macOS System-wide Audio Equalizer & Volume Mixer 🎧

🎛 🔊 A Python library for audio.

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

An implementation of Shazam's song recognition algorithm.

A library for audio and music analysis, feature extraction.

Isolate vocals, drums, bass, and other instrumental stems from any song

List of articles related to deep learning applied to music

Data manipulation and transformation for audio signal processing, powered by PyTorch

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn.

Synchronized Translation for Videos. Video dubbing

High quality training free inpaint for every stable diffusion model. Supports ComfyUI

StreamSpeech is an “All in One” seamless model for offline and simultaneous speech recognition, speech translation and speech synthesis.

AI Productivity Tool - Free and open source, improve user productivity, and protect privacy and data security. Including but not limited to: built-in local exclusive ChatGPT, DeepSeek, Phi, Qwen and other models, one-click batch intelligent processing of pictures, videos, audio, etc.

Collection of resources on the applications of Large Language Models (LLMs) in Audio AI.

Vector Hub - Library for easy discovery, and consumption of State-of-the-art models to turn data into vectors. (text2vec, image2vec, video2vec, graph2vec, bert, inception, etc)