Mining Musical Patterns: Identification of Transposed Motives

Authors:
Fernando Berzal;Waldo Fajardo;Aída Jiménez;Miguel Molina-Solana
Affiliations:
Dept. Computer Science and Artificial Intelligence, ETSIIT - University of Granada, Granada, Spain 18071;Dept. Computer Science and Artificial Intelligence, ETSIIT - University of Granada, Granada, Spain 18071;Dept. Computer Science and Artificial Intelligence, ETSIIT - University of Granada, Granada, Spain 18071;Dept. Computer Science and Artificial Intelligence, ETSIIT - University of Granada, Granada, Spain 18071
Venue:
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Year:
2009

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Abstract

Automatic extraction of frequent repeated patterns in music material is an interesting problem. This paper presents an effective approach of unsupervised frequent pattern discovery method from symbolic music sources. Patterns are discovered even if they are transposed. Experiments on some songs suggest that our approach is promising, specially when dealing with songs that include non-exact repetitions.