Frequency Warping for VTLN and Speaker Adaptation




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Frequency Warping for VTLN and Speaker Adaptation by Linear Transformation of Standard MFCC Sankaran Panchapagesan Abeer Alwan Department of Electrical Engineering The Henry Samueli School of Engineering and Applied Science 66 147E Engr IV 405 Hilgard Avenue Box 951594 University of California Los Angeles CA 90095 1594 USA Abstract Vocal Tract Length Normalization VTLN for standard filterbank based Mel Frequency Cepstral Coefficient MFCC features is usually implemented by warping the center frequencies of the Mel filterbank and the warping factor is estimated using the maximum likelihood score MLS criterion Lee and Rose 1998 A linear transform LT equivalent for frequency warping FW would enable more efficient MLS estimation Umesh et al 2005 We recently proposed a novel LT to perform FW for VTLN and model adaptation with standard MFCC features Panchapagesan 2006 In this paper we present the mathematical derivation of the LT and give a compact formula to calculate it for any FW function We also show that our LT is very closely related to previously proposed LTs for FW McDonough 2000 Pitz et al 2001 Umesh et al 2005 and these LTs for FW are all found to be numerically almost identical for the sine log all pass transform SLAPT warping functions Our formula for the transformation matrix is however computationally simpler and unlike other previous linear transform approaches to VTLN with MFCC features Pitz and Ney 2003 Umesh et al 2005 no modification of the standard MFCC feature extraction scheme is required In VTLN and Speaker Adaptive Modeling Welling et al 2002 experiments with the DARPA Resource Management RM1 database the performance of the new LT was comparable to that of regular VTLN implemented by warping the Mel filterbank when the MLS criterion was used for FW estimation This demonstrates that the approximations involved do not lead to any performance degradation Performance comparable to front end VTLN was also obtained with LT adaptation of HMM means in the






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