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In this paper, we show that frequency-warping (including VTLN) can be implemented through linear transformation of conventional MFCC. Unlike the Pitz-Ney [1] continuous domain approach, we directly determine the relation between frequency-warping and the linear-transformation in the discrete-domain. The advantage of such an approach is that it can be(More)
In this paper, we study the use of different frequency warp-factors for different acoustic classes in a computationally efficient framework of Vocal Tract Length Normalization (VTLN). This is motivated by the fact that all acoustic classes do not exhibit similar spectral variations as a result of physiological differences in vocal tract, and therefore, the(More)
It is common to use a single speaker independent large Gaussian Mixture Model based Universal Background Model (GMM-UBM) as the alternative hypothesis for speaker verification tasks. The speaker models are themselves derived from the UBM using Maximum a Posteriori (MAP) adaptation technique. During verification, log likelihood ratio is calculated between(More)
Recently, Multiple Background Models (M-BMs) [1, 2] have been shown to be useful in speaker verification, where the M-BMs are formed based on different Vocal Tract Lengths (VTLs) among the population. The speaker models are adapted from the particular Background Model (BM) corresponding to their VTL. During test, log likelihood ratio of the test utterance(More)