Abstract
In the continuing goal of codifying the classification of musical sounds and extracting rules for data mining, we present the following methodology of categorization, based on numerical parameters. The motivation for this paper is based upon the fallibility of Hornbostel and Sachs generic classification scheme, used in Music Information Retrieval for instruments. In eliminating the redundancy and discrepancies of Hornbostel and Sachs’ classification of musical sounds we present a procedure that draws categorization from numerical attributes, describing both time domain and spectrum of sound. Rather than using classification based directly on Hornbostel and Sachs scheme, we rely on the empirical data describing the log attack, sustainability and harmonicity. We propose a categorization system based upon the empirical musical parameters and then incorporating the resultant structure for classification rules.
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Lewis, R., Wieczorkowska, A. (2007). Parameter-Based Categorization for Musical Instrument Retrieval. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_82
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DOI: https://doi.org/10.1007/978-3-540-73451-2_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73450-5
Online ISBN: 978-3-540-73451-2
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