Title :
Music Segmentation With Genetic Algorithms
Author :
Rafael, Brigitte ; Oertl, Stefan ; Affenzeller, Michael ; Wagner, Stefan
Author_Institution :
Re-Compose GmbH, Vienna, Austria
fDate :
Aug. 31 2009-Sept. 4 2009
Abstract :
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 apply genetic algorithms for a solution to the segmentation problem.
Keywords :
audio databases; audio signal processing; genetic algorithms; information retrieval; music; pattern recognition; genetic algorithms; lyric alignment; music collections; music information retrieval; music segmentation; music summarization; musical structure visualization; Databases; Encoding; Evolutionary computation; Expert systems; Genetic algorithms; Genetic mutations; Laboratories; Music information retrieval; Runtime; Visualization; genetic algorithms; heuristic optimization; music information retrieval; music segmentation; pattern recognition;
Conference_Titel :
Database and Expert Systems Application, 2009. DEXA '09. 20th International Workshop on
Conference_Location :
Linz
Print_ISBN :
978-0-7695-3763-4
DOI :
10.1109/DEXA.2009.16