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Generative Deep Learning for Virtuosic Classical Music: Generative Adversarial Networks as Renowned Composers

Sound 2021-11-16 v3 Machine Learning Neural and Evolutionary Computing Audio and Speech Processing

Abstract

Current AI-generated music lacks fundamental principles of good compositional techniques. By narrowing down implementation issues both programmatically and musically, we can create a better understanding of what parameters are necessary for a generated composition nearly indistinguishable from that of a master composer.

Keywords

Cite

@article{arxiv.2101.00169,
  title  = {Generative Deep Learning for Virtuosic Classical Music: Generative Adversarial Networks as Renowned Composers},
  author = {Daniel Szelogowski},
  journal= {arXiv preprint arXiv:2101.00169},
  year   = {2021}
}

Comments

13 pages, 6 figures Update: Revised format to align closer to IEEE standards

R2 v1 2026-06-23T21:40:52.289Z