Speech Recognition Using a Neural Network
by Andrey Pilipchak Advisors: Dr. T. Stewart and Dr. I. S. Ahn In this paper, a neural network architecture is presented for speech
recognition. A library of two words is created by capturing male and female
8-bit voice data using a SoundBlaster sound card on an IBM-PC. The captured
data are sent through four different band-pass filters for feature extraction
of each word presented. Then the band-pass filter outputs are put through
two cascaded low-pass filters resulting in down-sampling. The low-pass
filter outputs are presented to an error backpropagation neural network
for training. MATLAB, a mathematical software environment, is used for
the training and testing of the algorithm. The trained neural network performs
reliably distinguishing the two words regardless of speaker and gender.
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