English

MorpheuS: generating structured music with constrained patterns and tension

Sound 2018-12-13 v1 Audio and Speech Processing

Abstract

Automatic music generation systems have gained in popularity and sophistication as advances in cloud computing have enabled large-scale complex computations such as deep models and optimization algorithms on personal devices. Yet, they still face an important challenge, that of long-term structure, which is key to conveying a sense of musical coherence. We present the MorpheuS music generation system designed to tackle this problem. MorpheuS' novel framework has the ability to generate polyphonic pieces with a given tension profile and long- and short-term repeated pattern structures. A mathematical model for tonal tension quantifies the tension profile and state-of-the-art pattern detection algorithms extract repeated patterns in a template piece. An efficient optimization metaheuristic, variable neighborhood search, generates music by assigning pitches that best fit the prescribed tension profile to the template rhythm while hard constraining long-term structure through the detected patterns. This ability to generate affective music with specific tension profile and long-term structure is particularly useful in a game or film music context. Music generated by the MorpheuS system has been performed live in concerts.

Keywords

Cite

@article{arxiv.1812.04832,
  title  = {MorpheuS: generating structured music with constrained patterns and tension},
  author = {Dorien Herremans and Elaine Chew},
  journal= {arXiv preprint arXiv:1812.04832},
  year   = {2018}
}

Comments

IEEE Transactions on Affective Computing. PP(99)

R2 v1 2026-06-23T06:39:53.807Z