Probabilistic prediction of rhythmic characteristics in Markov chain-based melodic sequences

Bongjun Kim, Woon Seung Yeo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Markov chain models have been widely used for algorithmic composition and machine improvisation. In this paper, we introduce a probabilistic prediction model of rhythmic characteristics of Markov chain-based note sequences. For this purpose, we propose an algorithm to generate a revised Markov chain model and calculate the onset probabilities of notes at each onset position in one measure. As an application of this algorithm, we present an interactive improvisation system which uses a customized syncopation index as an input parameter and allows the user to control the level of syncopation and rhythmic tension in real-time.

Original languageEnglish
Title of host publicationProceedings of the 2013 ICMC Conference
Subtitle of host publicationInternational Developments in Electroacoustics
PublisherInternational Computer Music Association
Pages418-421
Number of pages4
ISBN (Print)9780984527427
StatePublished - 2013
Event39th International Computer Music Conference, ICMC 2013 - Perth, WA, Australia
Duration: 11 Aug 201317 Aug 2013

Publication series

NameProceedings of the 2013 ICMC Conference: International Developments in Electroacoustics

Conference

Conference39th International Computer Music Conference, ICMC 2013
Country/TerritoryAustralia
CityPerth, WA
Period11/08/1317/08/13

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