Jukebox: A Generative Model for Music

Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford +1 more
4/30/2020
eess.AScs.LGcs.SD

Official code: openai/jukebox (8,029 stars, PyTorch, last commit 2024-06-19).

Abstract

We introduce Jukebox, a model that generates music with singing in the raw audio domain. We tackle the long context of raw audio using a multi-scale VQ-VAE to compress it to discrete codes, and modeling those using autoregressive Transformers. We show that the combined model at scale can generate high-fidelity and diverse songs with coherence up to multiple minutes. We can condition on artist and genre to steer the musical and vocal style, and on unaligned lyrics to make the singing more controllable. We are releasing thousands of non cherry-picked samples at https://jukebox.openai.com, along with model weights and code at https://github.com/openai/jukebox

View on arXivView PDF

Code Implementations(1)

openai/jukeboxOfficial100%
PyTorch

Code for the paper "Jukebox: A Generative Model for Music"

8,0291,442C++, CSSApr 29, 20202 years agoNOASSERTION
audiogenerative-modelmusicpaperpytorch+2 more

Similar Papers

Cite this paper

@article{dhariwal2020jukebox,
  title  = {Jukebox: A Generative Model for Music},
  author = {Prafulla Dhariwal and Heewoo Jun and Christine Payne and Jong Wook Kim and Alec Radford and Ilya Sutskever},
  year   = {2020},
  eprint = {2005.00341},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2005.00341}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2005.00341.svg)](https://codeofpaper.com/paper/2005.00341)

Discussion