基于FCM和FSVM的说话人辨认

被引:2
作者
谭萍
邢玉娟
机构
[1] 甘肃联合电子信息工程学院
关键词
模糊C均值聚类; 模糊支持向量机; 说话人辨认; 多分类支持向量机;
D O I
暂无
中图分类号
TN912.34 [语音识别与设备];
学科分类号
0711 ;
摘要
针对经典支持向量机对非目标样本没有拒绝能力,且应用于说话人辨认时存在不可分区域的问题,提出一种基于模糊C均值聚类和模糊支持向量机的多级模糊说话人辨认方法。首先利用模糊C均值聚类方法对特征向量进行聚类,减少样本的数目,加快模糊支持向量机训练速度。最终由FSVM得出判决结果。并通过仿真实验验证了该方法的有效性。
引用
收藏
页码:5919 / 5922
页数:4
相关论文
共 7 条
[1]  
Iterative fuzzy support vector machine classification. Shilton,Alistair,Lai D T H. Fuzzy Systems conference . 2007
[2]  
Fuzzy Support Vector Machines for Pattern Classification. Inoue T, Abe S. Proceedings of International Joint Conference on Neural Networks(IJCNN ’01) . 2001
[3]  
Public databases for speaker recognition and verification. J. Godtrcy,D. Graff,A. Maim. Proc. ESCA Workshop Automatic Speaker Recognition Verification . 1994
[4]  
Fuzzy support vector machine for multi-class text categorization. Wang Tai yue,Chiang Huei min. Information Processing&Management . 2007
[5]  
Cluster-based Support Vector Machines in Text-Independent Speaker Identification. SHENG-YU SUN,TSENG C L,CHEN Y H,CHUNG FU H. Neural Network.2004Proceeding Interna-tional Joint Conference . 2004
[6]  
An adaptive fuzzy c-means clustering-based mixtures of experts model for unlabeled data classifica-tion. Xing Hong jie,Hu Bao gang. Neural Computing and Applications . 2008
[7]  
Face Recognition Based on Independent Component Analysis and Fuzzy Support Vector Machine. Y. G. Liu,G. Chen,J. W. Lu. Proceedings of 6th WCICA . 2006