关键词: 支持向量机, 高斯线性核, 高斯非线性核, NAP技术, 说话人识别

Abstract: Speaker recognition problems have important theoretical value and far-reaching practical significance.On the basis of the support vector machine kernel methods，this paper combines it with traditional Gaussian Mixture Model（GMM） to build into a new support vector machine based on Gaussian sequence kernel.Much of the flexibility and classification power of SVM resides in the choice of kernel.And in the process of identifying，it introduces feature space norm technology performed by Nuisance Attribute Projection（NAP） to compensate the feature difference in different channels and environment from the same speaker.It is tested on the National Institute of Standards and Technology（NIST） 2004 evaluation database.Experiments results show that this method can greatly improve the recognition rate.

Key words: support vector machine, Gaussian linear kernel, Gaussian non-linear kernel, Nuisance Attribute Projection（NAP）, speaker recognition