Using mel-frequency cepstral coefficients in missing data technique

Authors:
Zhang Jun;Sam Kwong;Wei Gang;Qingyang Hong
Affiliations:
Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China and School of Electronic and Communication Engineering, South China University of Technology, Guangzhou, Chi ...;Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China;School of Electronic and Communication Engineering, South China University of Technology, Guangzhou, China;Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong, China
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2004

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Abstract

Filter bank is the most common feature being employed in the research of the marginalisation approaches for robust speech recognition due to its simplicity in detecting the unreliable data in the frequency domain. In this paper, we propose a hybrid approach based on the marginalisation and the soft decision techniques that make use of the Mel-frequency cepstral coefficients (MFCCs) instead of filter bank coefficients. A new technique for estimating the reliability of each cepstral component is also presented. Experimental results show the effectiveness of the proposed approaches.