Evolutionary optimization of music performance annotation

Authors:
Maarten Grachten;Josep Lluís Arcos;Ramon López de Mántaras
Affiliations:
IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain
Venue:
CMMR'04 Proceedings of the Second international conference on Computer Music Modeling and Retrieval
Year:
2004

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Abstract

In this paper we present an enhancement of edit distance based music performance annotation. The annotation captures musical expressivity not only in terms of timing deviations but also represents e.g. spontaneous note ornamentation. To reduce the number of errors in automatic performance annotation, some optimization is essential. We have taken an evolutionary approach to optimize the parameter values of cost functions of the edit distance. Automatic optimization is desirable since manual parameter tuning is unfeasible when more than a few performances are taken into account. The validity of the optimized parameter settings is shown by assessing their error-percentage on a test set.