Using heuristic optimization for segmentation of symbolic music

Brigitte Rafael, Stefan Örtl, Michael Affenzeller, Stefan Wagner

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

4 Citations (Scopus)

Abstract

Solving the segmentation problem for music is a key issue in music information retrieval (MIR). Structural information about a composition achieved by music segmentation can improve several tasks related to MIR such as searching and browsing large music collections, visualizing musical structure, lyric alignment, and music summarization. Various approaches using genetic algorithms have already been introduced to the field of media segmentation including image and video segmentation as segmentation problems usually have complex fitness landscapes. The authors of this paper present an approach to apply genetic algorithms to the music segmentation problem.

Original languageEnglish
Title of host publicationComputer Aided Systems Theory, EUROCAST 2009 - 12th International Conference, Revised Selected Papers
Pages641-648
Number of pages8
Volume5717
Edition1
DOIs
Publication statusPublished - 2009
Event12th International Conference on Computer Aided Systems Theory, EUROCAST 2009 - Las Palmas de Gran Canaria, Spain
Duration: 15 Feb 200920 Feb 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5717 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Conference on Computer Aided Systems Theory, EUROCAST 2009
Country/TerritorySpain
CityLas Palmas de Gran Canaria
Period15.02.200920.02.2009

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