A timeline of the latest AI models for audio generation, starting in 2023!

Audio generation using diffusion models, in PyTorch.

Implementation of SoundStorm, Efficient Parallel Audio Generation from Google Deepmind, in Pytorch

Codes and Model of the paper "Text-to-Audio Generation using Instruction Tuned LLM and Latent Diffusion Model"

Official PyTorch implementation of BigVGAN (ICLR 2023)

TTS Generation Web UI (Bark, MusicGen + AudioGen, Tortoise, RVC, Vocos, Demucs)

Source code for "Taming Visually Guided Sound Generation" (Oral at the BMVC 2021)

[CVPR'23] MM-Diffusion: Learning Multi-Modal Diffusion Models for Joint Audio and Video Generation

Official pytorch implementation of the paper: "Catch-A-Waveform: Learning to Generate Audio from a Single Short Example" (NeurIPS 2021)

Python library for designing and training your own Diffusion Models with PyTorch.

Trainer for audio-diffusion-pytorch

This is a list of datasets consisting of speech, music, and sound effects, which can provide training data for Generative AI, AIGC, AI model training, intelligent audio tool development, and audio applications. It is mainly used for speech recognition, speech synthesis, singing voice synthesis, music information retrieval, music generation, etc.

Word2Wave: a framework for generating short audio samples from a text prompt using WaveGAN and COALA.

Reading list for research topics in Sound AI

This is a list of sound, audio and music development tools which contains machine learning, audio generation, audio signal processing, sound synthesis, spatial audio, music information retrieval, music generation, speech recognition, speech synthesis, singing voice synthesis and more.

A collection of useful audio datasets and transforms for PyTorch.

Official implementation of the pipeline presented in I hear your true colors: Image Guided Audio Generation

Text prompt steered synthetic audio generators

Site for sharing Bark voices

Tracking states of the arts and recent results (bibliography) on sound tasks.