In practical problems, it adopts GMM - UBM as the background model when the training data is insufficient in speaker recognition system. Aiming at large amount of calculation in MCE training algorithm,it improved MCE. The improved MCE algorithm not only can reduce the amount of calculation, but also can get better recognition performance. The experimental results show that, under the different number of gaussian mixture and speakers, the improved MCE algorithm saves more training time than the traditional MCE algorithm, and as the growth of the number of gaussian mixture and speakers, the more time saving. In view of the MAP, MLLR, MAP\MLLR and EigenVoice adaptation ways which used in speaker recognition system modeling, then using MCE algorithm and the improved MCE algorithm, the improved MCE algorithm has higher recognition rate than the traditional MCE algorithm.