Fox, Charles (2021) MusicHastie: field-based hierarchical music representation. In: International Conference on Computer Music, 2021 Jul 25-30, Chile.
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MusicHastieICMC.pdf - Whole Document Available under License Creative Commons Attribution. 148kB |
Item Type: | Conference or Workshop contribution (Paper) |
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Item Status: | Live Archive |
Abstract
MusicHastie is a hierarchical music representation language designed for use in human and automated composition and for human and machine learning based music study and analysis. It represents and manipulates musical structure in a semantic form based on concepts from Schenkerian analysis, western European art music and popular music notations, electronica and some non-western forms such as modes and ragas. The representation is designed to model one form of musical perception by human musicians so can be used to aid human understanding and memorization of popular music pieces. An open source MusicHastie to MIDI compiler is released as part of this publication, now including capabilities for electronica MIDI control commands to model structures such as filter sweeps in addition to keys, chords, rhythms, patterns, and melodies.
Keywords: | music representation, artificial intelligence, computer music |
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Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence W Creative Arts and Design > W300 Music |
Divisions: | College of Science > School of Computer Science |
ID Code: | 45328 |
Deposited On: | 22 Jun 2021 10:31 |
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