Research on Multi-base Depth Neural Network Speech Recognition
In speech recognition system,an improved multi-base neural network speech recognition model is proposed to solve the problem of long learning time and slow convergence rate of deep neural network.However,the improved model introduces a large number of parameters in the training process to make the model over-fitted in the test set,resulting in the deterioration of generalization ability and the decrease of speech recognition rate.In order to solve this problem,an improved BP algorithm is introduced in the last layer of the depth neural network model.The experimental results show that the multi-base neural network model not only reduces the training time and calculation amount,but also improves the recognition accuracy compared with other recognition models,and it is an excellent speech recognition model.
speech recognition depth neural network over-fitting BP algorithm accuracy
Cai Jun Li Fei Zhang Yi LiuYu
College of Automation,Chongqing University of Posts and Telecommunications,Chongqing 400065,China Chongqing Information Accessibility and Service Robot Technology Research Center,Chongqing,400065,Ch School of Advanced Manufacturing Engineering,Chongqing University of Posts and Telecommunications,Ch
国际会议
重庆
英文
1540-1544
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）