Cepstral Domain Feature Extraction Utilizing Entropic Distance-Based Filterbank

Youngjoo SUH  Hoirin KIM  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E93-D   No.2   pp.392-394
Publication Date: 2010/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E93.D.392
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
Keyword: 
cepstral feature,  entropic distance,  filterbank,  speech recognition,  

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Summary: 
The selection of effective features is especially important in achieving highly accurate speech recognition. Although the mel-cepstrum is a popular and effective feature for speech recognition, it is still unclear that the filterbank adopted in the mel-cepstrum always produces the optimal performance regardless of the phonetic environment of any specific speech recognition task. In this paper, we propose a new cepstral domain feature extraction approach utilizing the entropic distance-based filterbank for highly accurate speech recognition. Experimental results showed that the cepstral features employing the proposed filterbank reduce the relative error by 31% for clean as well as noisy speech compared to the mel-cepstral features.