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Journal of Intelligent Information Systems
Erschienen in: Journal of Intelligent Information Systems 1/2012

01.02.2012

Wavelet ridges for musical instrument classification

verfasst von: M. Erdal Özbek, Nalan Özkurt, F. Acar Savacı

Erschienen in: Journal of Intelligent Information Systems | Ausgabe 1/2012

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Abstract

The time-varying frequency structure of musical signals have been analyzed using wavelets by either extracting the instantaneous frequency of signals or building features from the energies of sub-band coefficients. We propose to benefit from a combination of these two approaches and use the time-frequency domain energy localization curves, called as wavelet ridges, in order to build features for classification of musical instrument sounds. We evaluated the representative capability of our feature in different musical instrument classification problems using support vector machine classifiers. The comparison with the features based on parameterizing the wavelet sub-band energies confirmed the effectiveness of the proposed feature.
Vorheriger Artikel On context-aware co-clustering with metadata support
Nächster Artikel Learning Instance Weighted Naive Bayes from labeled and unlabeled data

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Metadaten
Titel
Wavelet ridges for musical instrument classification
verfasst von
M. Erdal Özbek
Nalan Özkurt
F. Acar Savacı
Publikationsdatum
01.02.2012
Verlag
Springer US
Erschienen in
Journal of Intelligent Information Systems / Ausgabe 1/2012
Print ISSN: 0925-9902
Elektronische ISSN: 1573-7675
DOI
https://doi.org/10.1007/s10844-011-0152-9

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