TY - GEN
T1 - Study of non-linear frequency warping functions for speaker normalization
AU - Kumar, S. V.Bharath
AU - Umesh, S.
AU - Sinha, R.
PY - 2006
Y1 - 2006
N2 - 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 [1] which has provided improved recognition performance when compared to uniform scaling model [1, 2]. 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 [3, 4] 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.
AB - 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 [1] which has provided improved recognition performance when compared to uniform scaling model [1, 2]. 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 [3, 4] 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.
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M3 - Conference contribution
AN - SCOPUS:33947690236
SN - 142440469X
SN - 9781424404698
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - I1245-I1248
BT - 2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
T2 - 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Y2 - 14 May 2006 through 19 May 2006
ER -