Selective noise cancellation using independent component analysis

Authors:
Jun-Il Sohn;Minho Lee
Affiliations:
Dept. of Sensor Engineering, Taegu, Korea;School of Electronic & Electrical Engineering, Taegu, Korea
Venue:
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Year:
2003

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Abstract

We propose a new ANC system that selectively cancels only the noise signal in the mixture at a specific local position. The BSS separates the desired sound signal from the unwanted noise signal and is used as a preprocessor of the proposed ANC system. In order to enhance the performance of noise separation, we propose a teacher-forced BSS learning algorithm. The teacher signal is obtained form a loudspeaker of the ANC system. Computer simulation and experimental results show that the proposed ANC system effectively cancels only the noise signals from the mixtures with human voice.