Desktop Control System with Voice Recognition by Using Hopfield Neural Network

Abstract

This paper describe the used of Hopfield neural networks for voice recognition. Speech (voice) recognition is multileveled pattern recognition tasks and neural networks are good at pattern recognition; many early researchers naturally tried applying neural networks to speech recognition. Hopfield neural network is a simple feedback network which is able to store patterns in a manner rather similar to the brain – the full pattern can be recovered if the network is presented with only partial information. There is a degree of stability in the system, the recalled pattern is not too badly corrupted and the network can respond with a best guess. Pattern storage is generally accomplished by a feedback network consisting of processing units. The stable states of the network represent the stored patterns. Voice recognition is used for controlling the icon from the desktop and office applications. The user speaks to the computer with the desire command that is the user’s training commands. Then the system understands the commands and is in many application areas especially for the handicapped person.