Riffusion

Generated spectrogram from the prompt "bossa nova with electric guitar" (top), and the resulting audio after conversion (bottom)

Riffusion is a neural network, designed by Seth Forsgren and Hayk Martiros, that generates music using images of sound rather than audio.^[1] It was created as a fine-tuning of Stable Diffusion, an existing open-source model for generating images from text prompts, on spectrograms.^[1] This results in a model which uses text prompts to generate image files, which can be put through an inverse Fourier transform and converted into audio files.^[2] While these files are only several seconds long, the model can also use latent space between outputs to interpolate different files together.^[1][3] This is accomplished using a functionality of the Stable Diffusion model known as img2img.^[4]

The resulting music has been described as "de otro mundo" (otherworldly),^[5] although unlikely to replace man-made music.^[5] The model was made available on December 15, 2022, with the code also freely available on GitHub.^[2] It is one of many models derived from Stable Diffusion.^[4]

Riffusion is classified within a subset of AI text-to-music generators. In December 2022, Mubert^[6] similarly used Stable Diffusion to turn descriptive text into music loops. In January 2023, Google published a paper on their own text-to-music generator called MusicLM.^[7][8]

References

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This page was last edited on 29 November 2023, at 11:16