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Evaluating Co-Creativity using Total Information Flow

Sound 2024-02-13 v1 Artificial Intelligence Human-Computer Interaction Information Theory Machine Learning Audio and Speech Processing math.IT

Abstract

Co-creativity in music refers to two or more musicians or musical agents interacting with one another by composing or improvising music. However, this is a very subjective process and each musician has their own preference as to which improvisation is better for some context. In this paper, we aim to create a measure based on total information flow to quantitatively evaluate the co-creativity process in music. In other words, our measure is an indication of how "good" a creative musical process is. Our main hypothesis is that a good musical creation would maximize information flow between the participants captured by music voices recorded in separate tracks. We propose a method to compute the information flow using pre-trained generative models as entropy estimators. We demonstrate how our method matches with human perception using a qualitative study.

Keywords

Cite

@article{arxiv.2402.06810,
  title  = {Evaluating Co-Creativity using Total Information Flow},
  author = {Vignesh Gokul and Chris Francis and Shlomo Dubnov},
  journal= {arXiv preprint arXiv:2402.06810},
  year   = {2024}
}
R2 v1 2026-06-28T14:44:41.148Z