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Evolutionary Optimization of Music Performance Annotation

AuthorsGrachten, Maarten; Arcos Rosell, Josep Lluís ; López de Mántaras, Ramón
KeywordsArtificial Intelligence
Case-Based Reasoning
Issue Date2005
CitationComputer Music Modeling and Retrieval, Second International Symposium, CMMR 2004, Esbjerg, Denmark, May 26-29, 2004. Revised Papers, Lecture Notes in Computer Science, Vol. 3310, p.p.: 347-358, Springer Berlin, 2005.
AbstractIn 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
DescriptionThe original publication is available at http://www.springerlink.com
Appears in Collections:(IIIA) Comunicaciones congresos
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