The Study Of Neural Model Based On Sound Category Learning In Speech Acquisition And Production

Speech production is probably the most complex in various human motion control tasks. In the current neural network model of speech production ,DIVA model is relatively the most thorough , and is a unique pseudo- inverse model control scheme . This control scheme provides a very accurate interpretation of the kinematic data of the human vocal organs .Because the speech recognition process is too complicated , so recognition process in the current DIVA model of the system is just an expert system .The paper first reviews the development process of speech production model , describes the development and current status of the speech recognition technology . The DIVA speech production model is then introduced , including the basic concepts of the DIVA model , the structural framework , the status and inadequacies of the model. Then discusses processes and methods of pre-processing and feature extraction for speech recognition . In order to explain the phenomenon of perceptual magnetic effect ,it proposes a neural model based on self- organizing feature map ,and analysis the feasibility and correctness of the model by computer simulation. Speech recognition system in DIVA model is only a expert system ,so it improves the algorithm of the model proposed above and apply it to the DIVA model.The Simulation experiment shows that we reach the goal. Finally , It summarizes the paper , points out the inadequacies of current research , and pointed out the follow-up research directions for further research.