1. A method for discriminative estimation of parameters in a maximum a posteriori (MAP) speaker adaptation condition, wherein 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, the method for discriminative estimation comprising the steps of: (a) classifying adaptation data among training sets for respective speakers; (b) obtaining speaker-independent 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 adapted speaker-independent model parameters, and calculating gradients of adapted speaker-independent model parameters by measuring the degree of errors on each candidate hypotheses; and (d) when training sets of all speakers are adapted, updating parameters, which were set at the initial stage, based on the calculated gradients.