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.
