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Desktop Control System with Voice Recognition by Using Hopfield Neural Network

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dc.contributor.author Swe, Khaing War
dc.contributor.author Khin, Thuzar
dc.date.accessioned 2019-07-24T15:58:53Z
dc.date.available 2019-07-24T15:58:53Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1252
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Fifth Local Conference on Parallel and Soft Computing en_US
dc.subject Neural Network en_US
dc.subject Hopfield-network en_US
dc.subject Voice Recognition en_US
dc.title Desktop Control System with Voice Recognition by Using Hopfield Neural Network en_US
dc.type Article en_US


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