Abraham Alcaim

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In this paper, a text-independent automatic speaker recognition (ASkR) system is proposed-the SR/sub Hurst/-which employs a new speech feature and a new classifier. The statistical feature pH is a vector of Hurst (H) parameters obtained by applying a wavelet-based multidimensional estimator (M/spl I.bar/dim/spl I.bar/wavelets ) to the windowed short-time(More)
In this paper, we introduce a formula to align the vertical coefficients of the SA-DCT (shape-adaptive discrete cosine transform). Instead of grouping coefficients with the same index as proposed by Sikora and Makai (1995), the new method employs an alignment by phase strategy. Experimental results are given for both synthetic segments and real testing(More)
This paper examines the role of the Principal Components Analysis (PCA) on the performance of two classification systems for text independent speaker verification: the Gaussian Mixture Model (GMM) and the AR-Vector Model. The use of the PCA transform resulted in an improvement in the performance of the GMM for training times of 60s and 30s. However, the(More)
A new approach for robust speaker identification using multiple classifiers in the subband domain is presented. The proposed system uses weights calculated from the energy in each subband of the speech signal to combine a set of likelihoods provided by GMM subband-classifiers. Experiments show the effectiveness of the proposed scheme as compared to other(More)