Feature extracted from wavelet decomposition using biorthogonal Riesz basis for text-independent speaker recognition

摘要

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.