Text-independent speaker identification by genetic clustering radial basis function neural network

被引:2
作者
Yue, XC [1 ]
Ye, DT [1 ]
Liu, M [1 ]
机构
[1] Tsing Hua Univ, Dept Elect Engn & Appl Elect Technol, Beijing 100084, Peoples R China
来源
PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE | 2001年 / 23卷
关键词
speaker identification; vector quantization; genetic algorithm; neural networks;
D O I
10.1109/IEMBS.2001.1020564
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The authors combine genetic clustering algorithm with radial basis function neural network (RBFNN) for avoiding locally optimum solutions in speaker identification. The effectiveness of genetic clustering algorithm is evaluated with speech utterances by comparing with normal clustering method. Speaker identification experiments show that genetic clustering RBFNN can improve the correctness of text-independent speaker identification.
引用
收藏
页码:1777 / 1780
页数:4
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