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Method and apparatus for discriminative estimation of parameters in maximum a posteriori (MAP) speaker adaptation condition and voice recognition method and apparatus including these
Method and apparatus for discriminative estimation of parameters in maximum a posteriori (MAP) speaker adaptation condition and voice recognition method and apparatus including these
A method and apparatus for discriminative estimation of parameters in a maximum a posteriori (MAP) speaker adaptation condition, and a voice recognition apparatus having the apparatus and a voice recognition method using the method are provided. The method for discriminative estimation of parameters in a maximum a posteriori (MAP) speaker adaptation condition, in which at least speaker-independent model parameters and prior density parameters, which are standards in recognizing a speaker's voice, are obtained as the result of model training after fetching training sets on a plurality of speakers from a training database, has the steps of (a) classifying adaptation data among training sets for respective speakers; (b) obtaining model parameters adapted from adaptation data on each speaker by using the initial values of the parameters; (c) searching a plurality of candidate hypotheses on each uttered sentence of training sets by using the adapted model parameters, and calculating gradients of speaker-independent model parameters by measuring the degree of errors on each training sentence; and (d) when training sets of all speakers are adapted, updating parameters, which were set at the initial stage, based on the calculated gradients.
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