On the Efficient Speech Feature Extraction Based on Independent Component Analysis

Authors:
Jong-Hwan Lee;Te-Won Lee;Ho-Young Jung;Soo-Young Lee
Affiliations:
Brain Science Research Center and Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yusong-Gu, Taejon 305-701, Korea. E-mail: jhl ...;Institute for Neural Computation, University of California, San Diego, 9500 Gilman Dr., La Jolla, CA 92093-0523, USA;Brain Science Research Center and Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yusong-Gu, Taejon 305-701, Korea;Brain Science Research Center and Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, 373-1 Kusong-Dong, Yusong-Gu, Taejon 305-701, Korea
Venue:
Neural Processing Letters
Year:
2002

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Abstract

A new efficient code for speech signals is proposed. To represent speech signals with minimum redundancy we use independent component analysis to adapt features (basis vectors) that efficiently encode the speech signals. The learned basis vectors are sparsely distributed and localized in both time and frequency. Time-frequency analysis of basis vectors shows the property similar with the critical bandwidth of human auditory system. Our results suggest that the obtained codes of speech signals are sparse and biologically plausible.