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Summary: COMBINING NEURAL NETWORKS AND HIDDEN MARKOV MODELS
M
FOR CONTINUOUS SPEECH RECOGNITION
ichael Cohen*, David Rumelhart**, Nelson Morgan***,
*
Horacio Franco*, Victor Abrash*, and Yochai Konig***
Speech Research Program, SRI International, Menlo Park, CA 94025
*
** Stanford University, Dept. of Psychology, Stanford, CA 94305
** Intl. Computer Science Inst., 1947 Center Street, Suite 600, Berkeley, CA 94704
W
ABSTRACT
e present a speakerindependent, continuousspeech recog
(
nition system based on a hybrid multilayer perceptron
MLP)/hidden Markov model (HMM). The system com
e
bines the advantages of both approaches by using MLPs to
stimate the statedependent observation probabilities of an
e
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