Long-form music generation with latent diffusion
Zach Evans Julian D. Parker CJ Carr Zack Zukowski Josiah Taylor Jordi Pons
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.