IMPULSIVITY ESTIMATES OF MIXTURES OF THE POWER EXPONENTIAL DISTRUBUTIONS IN SPEECH MODELING

A parametric family of multivariate density functions formed by mixture models from univariate functions of the type exp(−|x|&bgr;) for modeling acoustic feature vectores are used in automatic recognition of speech. The parameter &bgr; is used to measure the non-Gaussian nature of the data. &bgr; is estimated from the input data using a maximum likelihood criterion. There is a balance between &bgr; and the number of data points that must be satisfied for efficient estimation.