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Pitch-Dependent Identification of Musical Instrument Sounds (2005)
| Citations: | 3 - 3 self |
BibTeX
@MISC{Kitahara05pitch-dependentidentification,
author = {Tetsuro Kitahara and Masataka Goto and Hiroshi G. Okuno},
title = { Pitch-Dependent Identification of Musical Instrument Sounds },
year = {2005}
}
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Abstract
This paper describes a musical instrument identification method that takes into consideration the pitch dependency of timbres of musical instruments. The difficulty in musical instrument identification resides in the pitch dependency of musical instrument sounds, that is, acoustic features of most musical instruments vary according to the pitch (fundamental frequency, F0). To cope with this difficulty, we propose an F0-dependent multivariate normal distribution, where each element of the mean vector is represented by a function of F0. Our method first extracts 129 features (e.g., the spectral centroid, the gradient of the straight line approximating the power envelope) from a musical instrument sound and then reduces the dimensionality of the feature space into 18 dimension. In the 18-dimensional feature space, it calculates an F0-dependent mean function and an F0-normalized covariance, and finally applies the Bayes decision rule. Experimental results of identifying 6,247 solo tones of 19 musical instruments shows that the proposed method improved the recognition rate from 75.73 % to 79.73%.
Keyphrases
musical instrument sound musical instrument pitch-dependent identification pitch dependency musical instrument identification method feature space f0-dependent mean function recognition rate f0-dependent multivariate normal distribution solo tone mean vector straight line 18-dimensional feature space power envelope spectral centroid musical instrument identification resides experimental result acoustic feature f0-normalized covariance fundamental frequency bayes decision rule
