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Jukebox: A Generative Model for Music
by
Radford, Alec
, Dhariwal, Prafulla
, Sutskever, Ilya
, Heewoo Jun
, Kim, Jong Wook
, Payne, Christine
in
Autoregressive models
/ Jukeboxes
/ Music
/ Singing
2020
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Do you wish to request the book?
Jukebox: A Generative Model for Music
by
Radford, Alec
, Dhariwal, Prafulla
, Sutskever, Ilya
, Heewoo Jun
, Kim, Jong Wook
, Payne, Christine
in
Autoregressive models
/ Jukeboxes
/ Music
/ Singing
2020
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Paper
Jukebox: A Generative Model for Music
2020
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Overview
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
Publisher
Cornell University Library, arXiv.org
Subject
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