A New Neural Network Measure for Objective Speech Quality Evaluation

被引：0
|
作者：
Yan Tian-yun [1 ]
Wei Min [1 ]
Wei Wei [1 ]
Xu Zhen-ming [1 ]
机构：
[1] Chengdu Univ Informat Technol, Coll Comp Sci & Technol, Chengdu 610225, Peoples R China
来源：
2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM) | 2010年
关键词：
objective speech quality evaluation; generalized congruence neural network; RBF;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
A new measure for objective speech quality evaluation based on the improved generalized congruence neural network (GCNN/OSQE) is proposed, which needs less training time and has better performance. Compared with radial basis function neural network for objective speech quality evaluation measure (RBFNN/OSQE), besides owning all the merits of RBFNN/OSQE, GCNN/OSQE has many more merits: higher correlation, smaller standard deviation, and saving about 1/3 training time. In all, the results of speech quality assessment show that the proposed GCNN/OSQE is feasible and effective.
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页数：4
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