Optimizing the mapping from a symbolic to an audio representation for music-to-score alignment

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

Abstract

A key processing step in music-to-score alignment systems is the estimation of the intantaneous match between an audio observation and the score. We here propose a general formulation of this matching measure, using a linear transformation from the symbolic domain to any time-frequency representation of the audio. We investigate the learning of the mapping for several common audio representations, based on a best-fit criterion. We evaluate the effectiveness of our mapping approach with two different alignment systems, on a large database of popular and classical polyphonic music. The results show that the learning procedure significantly improves the precision of the alignments, compared to common heuristic templates used in the literature.

Original languageEnglish
Title of host publication2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Pages121-124
Number of pages4
DOIs
Publication statusPublished - 19 Dec 2011
Externally publishedYes
Event2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011 - New Paltz, NY, United States
Duration: 16 Oct 201119 Oct 2011

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Country/TerritoryUnited States
CityNew Paltz, NY
Period16/10/1119/10/11

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