Computer Assisted Composition in Continuous Time

Chamin Hewa Koneputugodagew, Rhys Healy, Sean Lamont, Ian Mallett, Matt Brown, Matt Walters, Ushini Attanayake, Libo Zhang, Roger T. Dean, Alexander Hunter, Charles Gretton, Christian Walder

Research output: Contribution to journalArticlepeer-review

Abstract

We address the problem of combining sequence models of symbolic music with user defined constraints. For typical models this is non-trivial as only the conditional distribution of each symbol given the earlier symbols is available, while the constraints correspond to arbitrary times. Previously this has been addressed by assuming a discrete time model of fixed rhythm. We generalise to continuous time and arbitrary rhythm by introducing a simple, novel, and efficient particle filter scheme, applicable to general continuous time point processes. Extensive experimental evaluations demonstrate that in comparison with a more traditional beam search baseline, the particle filter exhibits superior statistical proper- ties and yields more agreeable results in an extensive human listening test experiment.
Original languageEnglish
JournalarXiv (e-archive for Pre-prints, author submits)
DOIs
Publication statusPublished - 2019

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