Predicción lineal de la parte causal de la autocorrelación para la identificación del locutor en ambientes ruidosos

Abstract

Recently, a new parametrization technique based on the AR modelling of the one-sided autocorrelation sequence (OSALPC) has shown to be attractive for speech recognition because of its simplicity and its high recognition perfomance in noisy conditions. In this paper, that new parametrization technique is proposed to speaker identification in noisy enviroment. Experimental results obtained with a new speaker identification system based on the statistics of the cepstrals vectors show that OSALPC also achieves much better results than standard parametrization techniques.