Wavelet speech feature extraction using mean best basis algorithm

Authors:
Jakub Gałka;Mariusz Ziółko
Affiliations:
Department of Electronics, AGH University of Science and Technology, Kraków, Poland;Department of Electronics, AGH University of Science and Technology, Kraków, Poland
Venue:
NOLISP'09 Proceedings of the 2009 international conference on Advances in Nonlinear Speech Processing
Year:
2009

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Abstract

This paper presents Mean Best Basis algorithm, an extension of the well known Best Basis Wickerhouser's method, for an adaptive wavelet decomposition of variable-length signals. A novel approach is used to obtain a decomposition tree of the wavelet-packet cosine hybrid transform for speech signal feature extraction. Obtained features are tested using the Polish language hidden Markov model phone classifier.