Abstract: A novel WCCN kernel based on Bhattacharyya distance clustering algorithm was proposed in this paper in order to reduce the computation complexity of GMM super-vector,meanwhile the channel interference was removed from speaker verification system.Firstly,the GMM models of speakers were clustered based on Bhattacharyya distance,and clustering center models were obtained.Then super-vector sequence kernel was generated by adapting only mean vectors of these clustering center models.Finally,WCCN was used to restrain the noise and channel distortion effection of this kernel.Our experiment results showed that our new kernel can improve the recognition accuracy and speed.