Paper Info
Title
Study Of Jacobian Compensation Using Linear Transformation Of Conventional Mfcc For Vtln
Abstract
In this paper, we present a linear transformation (LT) to obtain warped features from unwarped features during vocal-tract length normalisation (VTLN). This LT between the warped and unwarped features is obtained within the conventional MFCC framework without any modification in the signal processing steps involved during the feature extraction stage. Further using the proposed LT, we study the effect of the Jacobian on the VTLN performance and show that it provides additional improvement in the recognition performance. The Jacobian of the proposed LT is simply the determinant of the LT matrix. Jacobian compensation is not done in conventional VTLN as the relation between warped and unwarped features is not known. We also study the effect of cepstral variance normalisation (CVN), which is often used as an approximation for Jacobian compensation in conventional VTLN. We show that the proposed Jacobian compensation gives better or comparable performance when compared to CVN.
Year
Venue
Keywords
2008
INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5
Automatic Speech Recognition, Speaker Normalisation, VTLN, Linear Transformation, Jacobian Compensation, Cepstral Variance Normalisation
Field
DocType
Citations 
Mel-frequency cepstrum,Pattern recognition,Jacobian matrix and determinant,Computer science,Speech recognition,Linear map,Artificial intelligence
Conference
10
PageRank 
References 
Authors
0.68
1
2
Name
Order
Citations
PageRank
D. R. Sanand1283.02
Srinivasan Umesh29316.31