Improving Melody Classification by Discriminant Feature Extraction and Fusion

Li, M. and Sleep, M. R. (2004) Improving Melody Classification by Discriminant Feature Extraction and Fusion. In: ISMIR2004, 5th International Conference on Music Information Retrieval, 2004-10-10 - 2004-10-14.

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Abstract

We propose a general approach to discriminant feature extraction and fusion, built on an optimal feature transformation for discriminant analysis [6]. Our experiments indicate that our approach can dramatically reduce the dimensionality of original feature space whilst improving its discriminant power. Our feature fusion method can be carried out in the reduced lower-dimensional subspace, resulting in a further improvement in accuracy. Our experiments concern the classification of music styles based only on the pitch sequence derived from monophonic melodies

Item Type: Conference or Workshop Item (Paper)
Faculty \ School: Faculty of Science > School of Computing Sciences
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Depositing User: Vishal Gautam
Date Deposited: 21 Jul 2011 09:56
Last Modified: 19 Sep 2020 23:47
URI: https://ueaeprints.uea.ac.uk/id/eprint/21576
DOI:

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