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Classification of audio signals using statistical features on time and wavelet transform domains

Lambrou, T; Kudumakis, P; Speller, R; Sandler, M; Linney, A; (1998) Classification of audio signals using statistical features on time and wavelet transform domains. In: (pp. pp. 3621-3624).

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Abstract

This paper presents a study on musical signal classification, using wavelet transform analysis in conjunction with statistical pattern recognition techniques. A comparative evaluation between different wavelet analysis architectures in terms of their classification ability, as well as between different classifiers is carried out. We seek to establish which statistical measures clearly distinguish between the three different musical styles of rock, piano, and jazz. Our preliminary results suggest that the features collected by the adaptive splitting wavelet transform technique performed better compared to the other wavelet based techniques, achieving an overall classification accuracy of 91.67%, using either the minimum distance classifier or the least squares minimum distance classifier. Such a system can play a useful part in multimedia applications which require content based search, classification, and retrieval of audio signals, as defined in MPEG-7. © 1998 IEEE.

Type: Proceedings paper
Title: Classification of audio signals using statistical features on time and wavelet transform domains
ISBN: 0780344286
ISBN-13: 9780780344280
DOI: 10.1109/ICASSP.1998.679665
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: http://discovery.ucl.ac.uk/id/eprint/84143
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