TY - GEN
T1 - Music segmentation with genetic algorithms
AU - Rafael, Brigitte
AU - Oertl, Stefan
AU - Affenzeller, Michael
AU - Wagner, Stefan
PY - 2009
Y1 - 2009
N2 - Music segmentation is a key issue in music information retrieval (MIR) as it provides an insight into the structure of a composition. Based on structural information, several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization can be further improved. Various approaches are available to achieve an appropriate segmentation of a given composition. The authors of this paper present an approach to appliy genetic algorithms for a solution to the segmentation problem.
AB - Music segmentation is a key issue in music information retrieval (MIR) as it provides an insight into the structure of a composition. Based on structural information, several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization can be further improved. Various approaches are available to achieve an appropriate segmentation of a given composition. The authors of this paper present an approach to appliy genetic algorithms for a solution to the segmentation problem.
KW - Genetic algorithms
KW - Heuristic optimization
KW - Music information retrieval
KW - Music segmentation
KW - Pattern recognition
UR - http://www.scopus.com/inward/record.url?scp=73649088688&partnerID=8YFLogxK
U2 - 10.1109/DEXA.2009.16
DO - 10.1109/DEXA.2009.16
M3 - Conference contribution
AN - SCOPUS:73649088688
SN - 9780769537634
T3 - Proceedings - International Workshop on Database and Expert Systems Applications, DEXA
SP - 256
EP - 260
BT - Proceedings - 20th International Workshop on Database and Expert Systems Applications, DEXA2009
T2 - 20th International Workshop on Database and Expert Systems Applications, DEXA2009
Y2 - 31 August 2009 through 4 September 2009
ER -