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Full-Text Articles in Physical Sciences and Mathematics
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 …
A Symbolic Music Transformer For Real-Time Expressive Performance And Improvisation, Arnav Shirodkar
A Symbolic Music Transformer For Real-Time Expressive Performance And Improvisation, Arnav Shirodkar
Senior Projects Fall 2023
With the widespread proliferation of AI technology, deep architectures — many of which are based on neural networks — have been incredibly successful in a variety of different research areas and applications. Within the relatively new domain of Music Information Retrieval (MIR), deep neural networks have also been successful for a variety of tasks, including tempo estimation, beat detection, genre classification, and more. Drawing inspiration from projects like George E. Lewis's Voyager and Al Biles's GenJam, two pioneering endeavors in human-computer interaction, this project attempts to tackle the problem of expressive music generation and seeks to create a Symbolic Music …