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http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3219| Title: | Evolutionary Optimization of Music Performance Annotation |
| Keywords: | Artificial Intelligence Case-Based Reasoning CBR |
| Publisher: | Springer |
| Description: | The original publication is available at
http://www.springerlink.com 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 This research has been partially supported by the Spanish Ministry of Science and Technology under the project TIC 2003-07776-C2-02 “CBR-ProMusic: Content-based Music Processing using CBR” and EU-FEDER funds. Peer reviewed |
| URI: | http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3219 |
| Other Identifiers: | Computer 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. 978-3-540-24458-5 0302-9743 http://hdl.handle.net/10261/3219 |
| Appears in Collections: | Digital Csic |
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