SYMPLEX: Controllable Symbolic Music Generation using Simplex Diffusion with Vocabulary Priors
Sound
2024-05-22 v1 Machine Learning
Audio and Speech Processing
Abstract
We present a new approach for fast and controllable generation of symbolic music based on the simplex diffusion, which is essentially a diffusion process operating on probabilities rather than the signal space. This objective has been applied in domains such as natural language processing but here we apply it to generating 4-bar multi-instrument music loops using an orderless representation. We show that our model can be steered with vocabulary priors, which affords a considerable level control over the music generation process, for instance, infilling in time and pitch and choice of instrumentation -- all without task-specific model adaptation or applying extrinsic control.
Cite
@article{arxiv.2405.12666,
title = {SYMPLEX: Controllable Symbolic Music Generation using Simplex Diffusion with Vocabulary Priors},
author = {Nicolas Jonason and Luca Casini and Bob L. T. Sturm},
journal= {arXiv preprint arXiv:2405.12666},
year = {2024}
}