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Long-form music generation with latent diffusion

16 April 2024
Zach Evans
Julian Parker
CJ Carr
Zack Zukowski
Josiah Taylor
Jordi Pons
    MGen
    DiffM
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Abstract

Audio-based generative models for music have seen great strides recently, but so far have not managed to produce full-length music tracks with coherent musical structure. We show that by training a generative model on long temporal contexts it is possible to produce long-form music of up to 4m45s. Our model consists of a diffusion-transformer operating on a highly downsampled continuous latent representation (latent rate of 21.5Hz). It obtains state-of-the-art generations according to metrics on audio quality and prompt alignment, and subjective tests reveal that it produces full-length music with coherent structure.

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