Speech Modelling Based On Generalized Gaussian Probability Density Functions
Kostas Kokkinakis, Asoke Kumar Nandi · 2006
A number of commonly used methods for estimating the exponent parameter of a generalized Gaussian density (GGD) are reviewed, described and compared. More importantly, focusing on the family of entropy matching estimators (EMEs), a novel entropic expression with respect to higher-order moments of the modelled data is proposed. This yields an elegant generalized entropy matching estimator (G-EME). Comparative experimental results illustrate the high accuracy of the proposed estimator, for both light- and heavy-tailed distributions, as well as speech data.