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Simultaneous processing of sound source separation and musical instrument identification using Bayesian spectral modeling

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5 Author(s)
Katsutoshi Itoyama ; Graduate School of Informatics, Kyoto University, Japan ; Masataka Goto ; Kazunori Komatani ; Tetsuya Ogata
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This paper presents a method of both separating audio mixtures into sound sources and identifying the musical instruments of the sources. A statistical tone model of the power spectrogram, called an integrated model, is defined and source separation and instrument identification are carried out on the basis of Bayesian inference. Since, the parameter distributions of the integrated model depend on each instrument, the instrument name is identified by selecting the one that has the maximum relative instrument weight. Experimental results showed correct instrument identification enables precise source separation even when many overtones overlap.

Published in:

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Date of Conference:

22-27 May 2011