Automatic identification of sound source position employing neural networks and rough sets

Authors:
Andrzej Czyzewski
Affiliations:
Sound and Vision Engineering Department, Technical University of Gdansk, ul. Narutowicza, 80-952 Gdansk, Poland
Venue:
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
Year:
2003

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Abstract

Methods for the identification of direction of the incoming acoustical signal in the presence of noise and reverberation are investigated. Since the problem is a non-deterministic one, thus applications of two learning algorithms, namely neural networks and rough sets are developed to solve it. Consequently, two sets of parameters have been formulated in order to discern target source from unwanted sound source position and then processed by learning algorithms. The applied feature extraction methods are discussed, training processes are described and obtained sound source localizing results are demonstrated and compared.