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dc.contributor.advisorTummala, Murali
dc.contributor.authorLe, Chau Giang
dc.dateJune 1993
dc.date.accessioned2014-03-26T23:23:19Z
dc.date.available2014-03-26T23:23:19Z
dc.date.issued1993-06
dc.identifier.urihttp://hdl.handle.net/10945/39805
dc.description.abstractThe primary objective of this research is to explore how a back- propagation neural network (BNN) can be applied to isolated-word speech recognition. Simulation results show that a BNN provides an effective approach for small vocabulary systems. The recognition rate reaches 100% for a 5-word system and 94% for a 10-word system. The general techniques developed in this thesis can be further extended to other applications, such as sonar target recognition, missile seeking and tracking functions in modern weapon systems, and classification of underwater acoustic signals.en_US
dc.description.urihttp://archive.org/details/applicationofbac1094539805
dc.format.extent38 p.en_US
dc.language.isoen_US
dc.publisherMonterey, California. Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleApplication of a back-propagation neural network to isolated-word speech recognitionen_US
dc.typeThesisen_US
dc.contributor.secondreaderTherrien, Charles W.
dc.contributor.corporateNaval Postgraduate School (U.S.)
dc.contributor.departmentElectrical and Computer Engineering
dc.subject.authorBNN (back-propagation neural networken_US
dc.subject.authorIsolated-word speechen_US
dc.description.serviceLieutenant, United States Navyen_US
etd.thesisdegree.nameM.S. in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.description.distributionstatementApproved for public release; distribution is unlimited.


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