Mining musical patterns: Identification of transposed motives
LNCS, Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009
5722
, pp. 271–280
(2009)
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.
Links:
| DOI: 10.1007/978-3-642-04125-9_30 PDF: |
Bibtex:
@incollection{Berzal2009,
title = {Mining musical patterns: Identification of transposed motives},
author = {Berzal, Fernando and Fajardo, Waldo and Jim\'enez, A\'ida and Molina-Solana, Miguel},
booktitle = {LNCS, Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009},
publisher = {Springer Berlin Heidelberg},
year = {2009},
address = {Prague, Czech Republic},
month = sep,
pages = {271--280},
series = {Lecture Notes in Computer Science},
volume = {5722},
pdf = {},
doi = {10.1007/978-3-642-04125-9_30},
timestamp = {105},
url = {http://ismis09.vse.cz/}
}