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基于混合PCA和KFD的多级说话人确认
引用本文:邢玉娟,张成文,李明.基于混合PCA和KFD的多级说话人确认[J].计算机工程,2010,36(18):185-187.
作者姓名:邢玉娟  张成文  李明
作者单位:1. 甘肃联合大学电子信息工程学院,兰州,730000
2. 兰州理工大学计算机与通信学院,兰州,730000
基金项目:甘肃省自然科学基金资助项目 
摘    要:提出一种基于混合主成分分析(PCA)分类器和核Fisher判别(KFD)的多级说话人确认方法。利用PCA对注册说话人的特征向量进行降维,根据转换矩阵得到说话人特征向量的主成分空间和截断误差空间,结合这2个空间构造混合PCA分类器,用于快速判断最有可能的R个目标说话人,并采用KFD寻找最终目标说话人。仿真实验结果验证了该方法的有效性。

关 键 词:说话人确认  主成分分析  主成分空间  截断误差空间  核Fisher判别

Hierarchical Speaker Verification Based on Mixed Principal Component Analysis and Kernel Fisher Discriminant
XING Yu-juan,ZHANG Cheng-wen,LI Ming.Hierarchical Speaker Verification Based on Mixed Principal Component Analysis and Kernel Fisher Discriminant[J].Computer Engineering,2010,36(18):185-187.
Authors:XING Yu-juan  ZHANG Cheng-wen  LI Ming
Affiliation:(1. School of Electronics and Information Engineering, Gansu Lianhe University, Lanzhou 730000, China; 2. School of Computer and Communication, Lanzhou University of Technology, Lanzhou 730000, China)
Abstract:This paper proposes a hierarchical speaker verification approach based on mixed Principal Component Analysis(PCA) classifier and Kernel Fisher Discriminant(KFD). PCA is utilized to reduce the dimension of registered speakers' feature vectors, and Principal Component Space(PCS) and Truncation Error Space(TES) are obtained based on the transform matrix. A mixed-PCA classifier is proposed based on PCS and TES to select the most possible R target speakers fast. And the target speaker is found with KFD. Experimental results validaie the effectiveness of the approach.
Keywords:speaker verification  Principal Component Analysis(PCA)  Principal Component Space(PCS)  Truncation Error Space(TES)  Kernel Fisher Discriminant(KFD)
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