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Erschienen in:
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2014 | OriginalPaper | Buchkapitel

Mining Audio Data for Multiple Instrument Recognition in Classical Music

verfasst von : Elżbieta Kubera, Alicja A. Wieczorkowska

Erschienen in: New Frontiers in Mining Complex Patterns

Verlag: Springer International Publishing

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Abstract

This paper addresses the problem of identification of multiple musical instruments in polyphonic recordings of classical music. A set of binary random forests was used as a classifier, and each random forest was trained to recognize the target class of sounds. Training data were prepared in two versions, one based on single sounds and their mixes, and the other containing also sound frames taken from classical music recordings. The experiments on identification of multiple instrument sounds in recordings are presented, and their results are discussed in this paper.

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Vorheriges Kapitel From Personalized to Hierarchically Structured Classifiers for Retrieving Music by Mood
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Metadaten
Titel
Mining Audio Data for Multiple Instrument Recognition in Classical Music
verfasst von
Elżbieta Kubera
Alicja A. Wieczorkowska
Copyright-Jahr
2014
Buch
New Frontiers in Mining Complex Patterns

Print ISBN: 978-3-319-08406-0

Electronic ISBN: 978-3-319-08407-7

Copyright-Jahr: 2014

DOI
https://doi.org/10.1007/978-3-319-08407-7_16