Aligning Generative Music AI with Human Preferences: Methods and Challenges

Dorien Herremans; Abhinaba Roy

AAAI 2026technical0 citations

Aligning Generative Music AI with Human Preferences: Methods and Challenges

Abstract

Recent advances in generative AI for music have achieved remarkable fidelity and stylistic diversity, yet these systems often fail to align with nuanced human preferences due to the specific loss functions they use. This paper advocates for the systematic application of preference alignment techniques to music generation, addressing the fundamental gap between computational optimization and human musical appreciation. Drawing on recent breakthroughs including MusicRL

BibTeX

@inproceedings{aaai2026_aligninggenerati,
  title = {Aligning Generative Music AI with Human Preferences: Methods and Challenges},
  author = {Dorien Herremans and Abhinaba Roy},
  booktitle = {AAAI 2026},
  year = {2026}
}