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Article Dans Une Revue IEEE Transactions on Affective Computing Année : 2019

MorpheuS: generating structured music with constrained patterns and tension

Résumé

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.
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Dates et versions

hal-03278024 , version 1 (05-07-2021)

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Dorien Herremans, Elaine Chew. MorpheuS: generating structured music with constrained patterns and tension. IEEE Transactions on Affective Computing, 2019, 10 (4), pp.510-523. ⟨10.1109/TAFFC.2017.2737984⟩. ⟨hal-03278024⟩
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