Title :
A New Neural Network Measure for Objective Speech Quality Evaluation
Author :
Yan, Tian-Yun ; Wei, Min ; Wei, Wei ; Xu, Zhen-Ming
Author_Institution :
Coll. of Comput. Sci. & Technol., Chengdu Univ. of Inf. Technol., Chengdu, China
Abstract :
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.
Keywords :
radial basis function networks; speech processing; improved generalized congruence neural network; objective speech quality evaluation; radial basis function neural network; Acoustic distortion; Artificial neural networks; Correlation; Neurons; Speech; Testing; Training;
Conference_Titel :
Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-3708-5
Electronic_ISBN :
978-1-4244-3709-2
DOI :
10.1109/WICOM.2010.5600267
