A Chinese speech (mandarin) database was established for speakers gender recognition. A combination method is proposed for gender recognition of speakers based on support vector machine and Melfrequency cepstrum coefficients (MFCC) for classification and feature extraction respectively. The comparative result shows that the accuracy of SVM is 98.7%, which is better than other methods.