تطوير وتصميم شبكة عصبية اصطناعية للتحكم الصوتي فينظومة التحكم

Abstract

Abstract This thesis has two main goals, the first goal is development and design artificial neural network architecture for specific application which is voice control, in addition to increase network generalization when it deals with new cases, this because human sound is not constant and vary each time he utterances the same word according to his health and emotional state. To achieve this goal, number of feed forward back propagation neural networks was built, and three types of transfer function was used which are Log sigmoid, Hyperbolic tangent sigmoid and Pure Liner to test performance for each of them, the experiences explained that Log sigmoid is much suitable for this application. Also this work follow effective manner in choosing numbers of layer and hidden nodes depending on trail and error but with specific strategy. The second goal is using the designed neural network to work as commands recognizer in voice control system, this system is a pressure control system which controls on petroleum pipelines and consist of pump, tank and electronic valve. Three experiments was applied to design this system, the designing on first experience depend on using isolated commands (Open, Close) and training neural network to recognize it, and then measured performance of the recognizer. The neural network here used log sigmoid for activate layer output and contain two hidden layer, number of nodes in them are 120 and 50 nodes. This design achieve performance ratio 98.5714%. The second designing using commands from two part (Open pump ,Close pump, Open Valve , Close valve ), the neural network used here has 70 nodes and one hidden layer between input and output layer. This design achieve perfonnance ratio 96.67%.The recognizer in last designing used phonemes of command to recognize it, this for make the system more general. The neural network used here has one hidden layer contain 100 nodes. This design achieve performance ratio only 23.3%. The three experiences were designed using MATLAB program, it used also for write preprocessing program which was use to extract word features.