Long-form music generation with latent diffusion
Zach Evans (Stability AI), Julian D Parker (Stability AI)*, CJ Carr (Stability AI), Zachary Zuckowski (Stability AI), Josiah Taylor (Stability AI), Jordi Pons (Stability AI)
Keywords: Applications -> music composition, performance, and production, Generative Tasks -> music and audio synthesis
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 from text prompts. 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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