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A Novel Approach To Extending Music Using Latent Diffusion, Keon Roohparvar, Franz J. Kurfess
A Novel Approach To Extending Music Using Latent Diffusion, Keon Roohparvar, Franz J. Kurfess
Master's Theses
Using deep learning to synthetically generate music is a research domain that has gained more attention from the public in the past few years. A subproblem of music generation is music extension, or the task of taking existing music and extending it. This work proposes the Continuer Pipeline, a novel technique that uses deep learning to take music and extend it in 5 second increments. It does this by treating the musical generation process as an image generation problem; we utilize latent diffusion models (LDMs) to generate spectrograms, which are image representations of music. The Continuer Pipeline is able to …