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Robust features for speech recognition using minimum variance distortionless response (MVDR) spectrum estimation and feature normalization techniques

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2 Author(s)
Yi Chen ; Graduate Inst. of Commun. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Lee, S.S.-M.

In this paper, feature extraction methods based on frequency-warped minimum variance distortionless response (MVDR) spectrum estimation are analyzed and tested. The effectiveness of the conventional FFT-based mel-frequency cepstrum coefficients (MFCC) and the MVDR-based features are carefully compared. Two normalization techniques are further applied to improve the robustness of the features: the widely used cepstral normalization (CN), and newly proposed progressive histogram equalization (PHEQ). Extensive experiments with respect to the AURORA2 database were performed. The results indicated that both the MVDR-based features and the normalization processes are very helpful.

Published in:

Chinese Spoken Language Processing, 2004 International Symposium on

Date of Conference:

15-18 Dec. 2004