Abstract
Multimedia data, including sound databases, require signal processing and parameterization to enable automatic searching for a specific content. Indexing of musical audio material with high-level timbre information requires extraction of low-level sound parameters first. In this paper, we analyze regularities in musical sound description, for the data representing musical instrument sounds by means of spectral and time-domain features. We examined digital audio recordings of singular sounds for 11 instruments of definite pitch. Woodwinds, brass, and strings used in contemporary orchestras were investigated, for various fundamental frequencies of sound and articulation techniques. General-purpose data mining system Forty-Niner was applied to investigate dependencies between the sound attributes, and the results of the experiments are presented and discussed. We also indicate a broad range of possible industry applications, which may influence directions of further research in this domain. We summarize our paper with conclusions on representation of musical instrument sound, and the emerging issue of exploration of audio databases.
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Wieczorkowska, A.A., Żytkow, J.M. Analysis of Feature Dependencies in Sound Description. Journal of Intelligent Information Systems 20, 285–302 (2003). https://doi.org/10.1023/A:1022864925044
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DOI: https://doi.org/10.1023/A:1022864925044