Computationally Efficient Cepstral Domain Feature Compensation

Woohyung LIM  Chang Woo HAN  Nam Soo KIM  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E92-D   No.1   pp.86-89
Publication Date: 2009/01/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.86
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
Keyword: 
feature compensation,  cepstral domain,  linear approximation,  

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Summary: 
In this letter, we propose a novel approach to feature compensation performed in the cepstral domain. Processing in the cepstral domain has the advantage that the spectral correlation among different frequencies is taken into consideration. By introducing a linear approximation with diagonal covariance assumption, we modify the conventional log-spectral domain feature compensation technique to fit to the cepstral domain. The proposed approach shows significant improvements in the AURORA2 speech recognition task.