2003 | OriginalPaper | Buchkapitel
Feature-Driven Recognition of Music Styles
verfasst von : Pedro J. Ponce de León, José M. Iñesta
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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In this paper the capability of using self-organising neural maps (SOM) as music style classifiers of musical fragments is studied. From MIDI files, the monophonic melody track is extracted and cut into fragments of equal length. From these sequences, melodic, harmonic, and rhythmic numerical descriptors are computed and presented to the SOM. Their performance is analysed in terms of separability in different music classes from the activations of the map, obtaining different degrees of success for classical and jazz music. This scheme has a number of applications like indexing and selecting musical databases or the evaluation of style-specific automatic composition systems.