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基于GMM说话人分类的说话人识别方法研究
引用本文:赵振东,张静,李圆,胡喜梅.基于GMM说话人分类的说话人识别方法研究[J].通信技术,2009,42(10):192-193.
作者姓名:赵振东  张静  李圆  胡喜梅
作者单位:华北电力大学电子与通信工程系,河北,保定,071003
摘    要:提出了基于高斯混合模型(GMM)说话人分类的分级说话人识别系统,同时将小波神经网络(WNN)引入到子识别系统中。分别对未分级说话人识别系统和分级说话人识别系统进行了比较。仿真实验结果表明,分级网络在保证正确识别率的同时,不仅改善了网络训练速度,亦大大提高了识别响应速度。

关 键 词:说话人识别  小波神经网络  高斯混合模型

Speaker Recognition Research Based on GMM Speaker Clustering Technology
ZHAO Zhen-dong,ZHANG Jing,LI Yuan,HU Xi-mei.Speaker Recognition Research Based on GMM Speaker Clustering Technology[J].Communications Technology,2009,42(10):192-193.
Authors:ZHAO Zhen-dong  ZHANG Jing  LI Yuan  HU Xi-mei
Affiliation:Department of Electronic and Communication Engineering, North China Electric Power University, Baoding Hebei 071003, China)
Abstract:Hierarchical speaker recognition system based on Gauss Mixed Model (GMM) speaker clustering technology is proposed, and the model of wavelet neural network (WNN) is introduced into the sub-recognition system. The hierarchical speaker recognition system is compared with the non-hierarchical system. The simulation results show that the hierarchical speaker recognition system is improved in network training speed and recognition response speed.
Keywords:speaker recognition  wavelet neural network: Gauss mixed model
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