Antipattern Discovery in Folk Tunes

Bibliographic Data

ID7857565
AuthorsDarrell Conklin (0000-0002-2313-9326, University of the Basque Country, corresponding author)
Year2013
Volume42
Issue2
Pages161-169
Publication date2013-06-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of New Music Research (JOURNAL)
Journal identifiersISSN: 0929-8215 • E-ISSN: 1744-5027
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/09298215.2013.809125
OpenAlexW2008951045
LanguageEN
Citations received2
References cited9

This paper presents a new pattern discovery method for labelled folk song corpora. The method discovers general patterns that are rare or even entirely absent from a set of pieces, and among those the patterns that are frequent in a background set. Pattern discovery is performed with reference to a background ontology of folk tune genres. The method is applied to a large corpus of Basque folk tunes and results are evaluated as descriptive patterns and as negative association rules. Acknowledgments The Fundación Euskomedia and Fundación Eresbil are graciously thanked for participating in the project and providing the Cancionero Vasco for study. This research was partially supported by a grant Análisis Computacional de la Música Folclórica Vasca (2011–2012) from the Diputación Foral de Gipuzkoa, Spain. Thanks to Izaro Goienetxea for assistance with ontology building and pattern interpretation. Special thanks to Kerstin Neubarth and the reviewers for valuable comments on the manuscript. Notes Darrell Conklin, Department of Computer Science and Artificial Intelligence, University of the Basque Country UPV/EHU, San Sebastián, Spain, and IKERBASQUE, Basque Foundation for Science, Bilbao, Spain. www.euskomedia.org www.eresbil.com

Art · Epistemology · Humanities · Library science · Ontology · Computer Science · Music and Audio Processing · Music Technology and Sound Studies · Natural Language Processing Techniques · Philosophy · Artificial Intelligence

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