1. A probability density function compensation method comprising: extracting feature vectors from speech signals, and using the extracted feature vectors, training a model having a plurality of probability density functions to increase probabilities of recognizing the speech signals; obtaining a global variance by averaging variances of the plurality of the probability density functions after completing the training; obtaining a compensation factor using the global variance; and applying the global variance to each of the probability density functions and compensating each of the probability density functions for the global variance by using the compensation factor.