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Proceedings Paper

Semi-automatic approach for music classification
Author(s): Tong Zhang
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Paper Abstract

Audio categorization is essential when managing a music database, either a professional library or a personal collection. However, a complete automation in categorizing music into proper classes for browsing and searching is not yet supported by today’s technology. Also, the issue of music classification is subjective to some extent as each user may have his own criteria for categorizing music. In this paper, we propose the idea of semi-automatic music classification. With this approach, a music browsing system is set up which contains a set of tools for separating music into a number of broad types (e.g. male solo, female solo, string instruments performance, etc.) using existing music analysis methods. With results of the automatic process, the user may further cluster music pieces in the database into finer classes and/or adjust misclassifications manually according to his own preferences and definitions. Such a system may greatly improve the efficiency of music browsing and retrieval, while at the same time guarantee accuracy and user’s satisfaction of the results. Since this semi-automatic system has two parts, i.e. the automatic part and the manual part, they are described separately in the paper, with detailed descriptions and examples of each step of the two parts included.

Paper Details

Date Published: 26 November 2003
PDF: 11 pages
Proc. SPIE 5242, Internet Multimedia Management Systems IV, (26 November 2003); doi: 10.1117/12.511787
Show Author Affiliations
Tong Zhang, Hewlett-Packard Labs. (United States)

Published in SPIE Proceedings Vol. 5242:
Internet Multimedia Management Systems IV
John R. Smith; Sethuraman Panchanathan; Tong Zhang, Editor(s)

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