Speech recognition application system on Personal Digital Assistant

• Main Authors: Yi-Chun Sun, 孫益君
• Other Authors: Chu-Kuei Tu
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/32694050232063273633

碩士 === 中原大學 === 資訊工程研究所 === 92 === This paper presents a new approach to design a speech recognition system. The user can use speech voice to operate equipments in remote place. The first step of the procedure is to analysis the speech signal to get speech features. The second step is to establish a neural network, for the purpose of speech recognition. The model of neural network method uses Black Propagation Network (BPN). The speech features extraction uses the methods of Linear Predictive Coefficient (LPC) and Cepstrum. The Black Propagation Network import the 280 numbers of speech feature to train the neural model until the neural model has be convergent. Then, user input a speech command to the system. The neural model will recognize the command. The system is established on Personal Digital Assistant (PDA) and connected with computer system as its remote server. When user input speech command to PDA, the PDA will recognize speech and execute the commands. Then, the remote server will take action on equipment according to the command of the speech. The remote server has a basic ability of image analysis, and can transfer the image, which take from remote field, back to the command side. When server interface with it peripherals, the RS-232 serial data transfer standard is used, via this channel the command signals are implement to control the remote equipment. In order to enhance the ability of application an Infra-Red and a Radio wave transmitter receiver interface card are equipped.