Kanevsky, Dr Dimitri (2005) EXTENDED BAUM TRANSFORMATIONS FOR GENERAL FUNCTIONS, II. [Departmental Technical Report] (Unpublished)

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The discrimination technique for estimating the parameters of Gaussian mixtures that is based on the Extended Baum transformations (EB) has had significant impact on the speech recognition community. The proof that definitively shows that these transformations increase the value of an objective function with iteration (i.e., so-called "growth transformations") was presented by the author two years ago for a diagonal Gaussian mixture densities. In this paper this proof is extended to a multidimensional multivariate Gaussian mixtures. The proof presented in the current paper is based on the linearization process and the explicit growth estimate for linear forms of Gaussian mixtures.

Item Type:Departmental Technical Report
Keywords:Multidimensional Multivariate Gaussuan Mixture, Extended Baum-Welch transformations, discriminative training, estimation of statistical parameters, maximum mutual informaiton estimation
Subjects:Computer Science > Statistical Models
ID Code:5058
Deposited By: Kanevsky, Dr Dimitri
Deposited On:08 Aug 2006
Last Modified:11 Mar 2011 08:56

References in Article

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