Jukebox: A Generative Model for Music

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Authors Alec Radford, Prafulla Dhariwal, Jong Wook Kim, Ilya Sutskever, Heewoo Jun, Christine Payne
Journal/Conference Name Preprint 2020 4
Paper Category
Paper 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
Date of publication 2020
Code Programming Language Python

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