Abstract
A new speaker feature extracted from wavelet decomposition using biorthogonal Riesz bases is described. Biorthogonal Riesz bases can offer a significant computational advantage by reducing the dimensionality of the eigenvalue problem at a not square matrix. Our results have shown that these wavelet Riesz bases introduced better performance than the other wavelet transforms with respect to the percentages of recognition.
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