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Semi-Automatic Approach for Music Classification

Zhang, Tong


Keyword(s): music classification; music database management; audio content analysis; semi-automatic classification

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 technical report, 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. Notes: Copyright SPIE. To be published in and presented at the SPIE Conference on Internet Multimedia Management Systems IV, 10 September 2003, Orlando, Florida

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