title: Long-form music generation with latent diffusion
summary: 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.
paper_authors._id: 66200147b760cd2e987fc32a
paper_authors.name: Zach Evans
paper_authors._id: 66200147b760cd2e987fc32b
paper_authors.name: Julian D. Parker
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-04-18T08:09:49.408Z
paper_authors._id: 657c2cf25c6f0b1f36077033
paper_authors.avatarUrl: /avatars/af538ee6d185d49efc0b7cf8660217ad.svg
paper_authors.fullname: Julian Parker
paper_authors.type: user
paper_authors.user: julian-parker
paper_authors._id: 66200147b760cd2e987fc32c
paper_authors.name: CJ Carr
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-04-18T08:19:53.221Z
paper_authors._id: 64932b4a7ed33d93550902bb
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/RAF-iCFqukRnjZ1VbtVZU.jpeg
paper_authors.fullname: CJ Carr
paper_authors.type: user
paper_authors.user: cjus13
paper_authors._id: 66200147b760cd2e987fc32d
paper_authors.name: Zack Zukowski
paper_authors._id: 66200147b760cd2e987fc32e
paper_authors.name: Josiah Taylor
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-04-18T08:20:14.709Z
paper_authors._id: 642c16a0c3694d2b74558f14
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/642c16a0c3694d2b74558f14/ILnrIBeO_tA3BjkEmyyFZ.png
paper_authors.fullname: Josiah Taylor
paper_authors.type: user
paper_authors.user: AtOdds
paper_authors._id: 66200147b760cd2e987fc32f
paper_authors.name: Jordi Pons
paper_title: Long-form music generation with latent diffusion
paper_summary: 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.
paper_ai_keywords: generative models diffusion-transformer generative models diffusion-transformer