gen_gmm.m
来自「最全的ASR工具集合」· M 代码 · 共 30 行
M
30 行
%==================================================================
% Generate a Gaussian Mixture Model (GMM) by the EM algorithm.
%
% The parameters are given with a structure defined as:
%
% (1) Par.Size : number of Gaussian functions
% (2) Par.MaxIter : maximum iterations
% (3) Par.RandSeed : random seed;
%
%
% Usage: Model = Gen_GMM(Data, Par);
%
% Example:
%
% suppose Data(1).Mat, Data(2).Mat, ...., contain training data,
%
% MyPar.Size = 8;
% MyPar.MaxIter = 20;
% MyPar.RandSeed = 1973;
%
% GMM = Gen_GMM(Data, MyPar);
%
% Each row of GMM.MeanMat is a mean vector.
% Each row of GMM.VariMat is a variance vector.
% GMM.WgtMat contains mixture weigth.
%------------------------------------------------------------------
% Author : Jialong HE
% Date : June 25, 1999
%==================================================================
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