Reconocimiento robusto del habla con parametrización lpc

Abstract

Cepstral coefficients obtained by means of a linear predictive analysis (LPC) of either the signal or a related sequence have given remarkable robustness against additive Gaussian white noise. From a comparative study of the most robust techniques appeared in the literature and some shight alternatives proposed in this paper, we attain two main conclusions : 1) the slope cepstral window and a relatively high model order are preferable; and 2) the spectral representation based on the autocorrelation (rather than on the signal) modelling achieves better results than the high performance cepstral projection distance measure for low signal-to-noise ratios.