4th International Conference on Spoken Language Processing

Philadelphia, PA, USA
October 3-6, 1996

Wavelet Based Feature Extraction for Phoneme Recognition

C. J. Long, S. Datta

Department of Electronic and Electrical Engineering, Loughborough University of Technology Loughborough, UK

In an effort to provide a more efficient representation of the acoustical speech signal in the pre-classification stage of a speech recognition system, we consider the application of the Best-Basis Algorithm of Coifman and Wickerhauser. This combines the advantages of using a smooth, compactly-supported wavelet basis with an adaptive time-scale analysis dependent on the problem at hand. We start by briefly reviewing areas within speech recognition where the Wavelet Transform has been applied with some success. Examples include pitch detection, formant tracking, phoneme classification. Finally, our wavelet based feature extraction system is described and its performance on a simple phonetic classification problem given.

Full Paper

Bibliographic reference.  Long, C. J. / Datta, S. (1996): "Wavelet based feature extraction for phoneme recognition", In ICSLP-1996, 264-267.