Bayesian MAP estimation of piecewise arcs in tempo time-series

Daniel Stowell*, Elaine Chew

*Corresponding author for this work

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Abstract

In musical performances with expressive tempo modulation, the tempo variation can be modelled as a sequence of tempo arcs. Previous authors have used this idea to estimate series of piecewise arc segments from data. In this paper we describe a probabilistic model for a time-series process of this nature, and use this to perform inference of single- and multi-level arc processes from data. We describe an efficient Viterbi-like process for MAP inference of arcs. Our approach is score-agnostic, and together with efficient inference allows for online analysis of performances including improvisations, and can predict immediate future tempo trajectories.
Original languageEnglish
Title of host publicationProceedings of the 9th International Symposium on Computer Music Modeling and Retrieval (CMMR)
Place of PublicationLondon
PublisherCMMR
Volume9
Publication statusPublished - 19 Jun 2012
Event9th International Symposium on Computer Music Modeling and Retrieval - Queen Mary University of London, London, United Kingdom
Duration: 19 Jun 201222 Jun 2012
Conference number: 9
https://archive.org/details/podcast_cmmr-london-2012-a-feature-su_551018829

Publication series

NameProceedings of the 9th International Symposium on Computer Music Modeling and Retrieval (CMMR)
PublisherCMMR

Conference

Conference9th International Symposium on Computer Music Modeling and Retrieval
Abbreviated titleCMMR 2012
Country/TerritoryUnited Kingdom
CityLondon
Period19/06/201222/06/2012
Internet address

Keywords

  • musical prosody
  • musical expression
  • music expressivity
  • tempo arc
  • segmentation
  • music processing

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