An algorithm using Geese particle swarm optimization (PSO) algorithm to improve the performance of AdaBoost.M2 with SVM was proposed in this paper. The algorithm first trains some support vector machines as weak classifiers

and then uses AdaBoost.M2 algorithm to embody the weak classifiers into a strong classifie

achieving multi-class classification. this algorithm uses GeesePSO to optimize the weights of SVM weak classifiers

leading to improve lift capacity of strong classifier

making up for the shortcomings of local optimization

and has better performance in global optimization. Experimental result demonstrates that in the low SNR speech recognition the improved AdaBoost.M2-SVM achieved better generalization performance and higher identification rate than SVM.