Harmonic and instrumental information fusion for musical genre classification

Authors:
Tomás Pérez-García;Carlos Pérez-Sancho;José M. Iñesta
Affiliations:
University of Alicante, Alicante, Spain;University of Alicante, Alicante, Spain;University of Alicante, Alicante, Spain
Venue:
Proceedings of 3rd international workshop on Machine learning and music
Year:
2010

Citing 4
Cited 0

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Abstract

This paper presents a musical genre classification system based on the combination of two kinds of information of very different nature: the instrumentation information contained in a MIDI file (metadata) and the chords that provide the harmonic structure of the musical score stored in that file (content). The fusion of these two information sources gives a single feature vector that represents the file and to which classification techniques usually utilized for text categorization tasks are applied. The classification task is performed under a probabilistic approach that has improved the results previously obtained for the same data using the instrumental or the chord information independently.