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Cepstral Domain Feature Extraction Utilizing Entropic Distance-Based Filterbank
Youngjoo SUH Hoirin KIM
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2010/02/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
cepstral feature, entropic distance, filterbank, speech recognition,
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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.