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.
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Rafael, B., Oertl, S., Affenzeller, M., Wagner, S. (2009). Using Heuristic Optimization for Segmentation of Symbolic Music. In: Moreno-DÃaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2009. EUROCAST 2009. Lecture Notes in Computer Science, vol 5717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04772-5_83
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DOI: https://doi.org/10.1007/978-3-642-04772-5_83
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04771-8
Online ISBN: 978-3-642-04772-5
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