@article{7669da3cbd69452185283a7e03ed6831,
title = "MorpheuS: Generating Structured Music with Constrained Patterns and Tension",
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 = "affective computing, music information retrieval, music generation, sound and music computing, variable neighborhood search, pattern recognition",
author = "Dorien Herremans and Elaine Chew",
year = "2019",
month = oct,
day = "1",
language = "English",
journal = "IEEE transactions on affective computing",
issn = "1949-3045",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
}