Paper Info
Title
Study Of Non-Linear Frequency Warping Functions For Speaker Normalization.
Abstract
In this paper, we study non-linear frequency-warping functions that are commonly used in speaker normalization. This study is motivated by our recently proposed affine transformation model for speaker normalization which has provided improved recognition performance when compared to uniform scaling model. In this work, using formant data from Peterson & Barney and Hillenbrand vowel databases, we analyze the behavior of scale factor as a function of frequency. The empirical observation shows that while uniform scaling assumption may be valid at higher frequencies, there are significant deviations at low frequencies. We show that while our recently proposed model has behavior similar to the empirical result, the behavior of many of the commonly used non-linear models (including that of Eide-Gish, power law and bilinear transformation) differ significantly from the empirical result. This difference in behavior from the empirical observation may explain the limited improvement in recognition performance provided by these non-linear models when compared to conventional uniform-scaling model. We also show that our proposed model does better fitting to the formant data than these non-linear models. We, therefore, conclude that the affine-transformation model may be a more appropriate non-linear model for speaker normalization
Year
DOI
Venue
2006
10.1109/ICASSP.2006.1660253
ICASSP (1)
Keywords
Field
DocType
speech recognition,power law,databases,affine transformation,low frequency,data analysis,fitting
Scale factor,Affine transformation,Nonlinear system,Normalization (statistics),Image warping,Pattern recognition,Bilinear transform,Artificial intelligence,Formant,Scaling,Mathematics
Conference
Volume
ISSN
ISBN
1
1520-6149
1-4244-0469-X
Citations 
PageRank 
References 
0
0.34
6
Authors
3
Name
Order
Citations
PageRank
S. V. Bharath Kumar1133.38
Srinivasan Umesh29316.31
Rohit Sinha323130.54