Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition

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dc.contributor.author Leung, KF
dc.contributor.author Leung, FHF
dc.contributor.author Lam, HK
dc.contributor.author Ling, SH
dc.date.accessioned 2012-02-02T09:29:46Z
dc.date.issued 2007-05
dc.identifier.citation Neural Computing and Applications, 2007, 16 (4-5), pp. 419 - 431
dc.identifier.issn 0941-0643
dc.identifier.other C1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/15121
dc.description.abstract This paper presents the recognition of speech commands using a modified neural fuzzy network (NFN). By introducing associative memory (the tuner NFN) into the classification process (the classifier NFN), the network parameters could be made adaptive to changing input data. Then, the search space of the classification network could be enlarged by a single network. To train the parameters of the modified NFN, an improved genetic algorithm is proposed. As an application example, the proposed speech recognition approach is implemented in an eBook experimentally to illustrate the design and its merits. © Springer-Verlag London Limited 2007.
dc.language eng
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon 10.1007/s00521-006-0068-4
dc.rights The original publication is available at www.springerlink.com en_US
dc.title Application of a modified neural fuzzy network and an improved genetic algorithm to speech recognition
dc.type Journal Article
dc.description.version Published
dc.parent Neural Computing and Applications
dc.journal.volume 4-5
dc.journal.volume 16
dc.journal.number 4-5 en_US
dc.publocation New York en_US
dc.identifier.startpage 419 en_US
dc.identifier.endpage 431 en_US
dc.cauo.name FEIT. A/DRsch Ctre for Health Technologies en_US
dc.conference Verified OK en_US
dc.for 0801 Artificial Intelligence and Image Processing
dc.personcode 106694
dc.percentage 100 en_US
dc.classification.name Artificial Intelligence and Image Processing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity WOS:000247428700009 en_US
dc.description.keywords Controllers; DesignNeural network ? Genetic algorithm, Fuzzy logic, Speech recognition, Pattern recognition en_US
dc.description.keywords Science & Technology
dc.description.keywords Life Sciences & Biomedicine
dc.description.keywords Medicine, Legal
dc.description.keywords Legal Medicine
dc.description.keywords MEDICINE, LEGAL
dc.description.keywords Fingerprints
dc.description.keywords Cyanoacrylate
dc.description.keywords Infrared
dc.description.keywords Chemical imaging
dc.description.keywords Polymer banknotes
dc.description.keywords Forensic science
dc.description.keywords FT-IR SPECTROSCOPY
dc.description.keywords INFRARED-SPECTROSCOPY
dc.description.keywords CYANOACRYLATE ADHESIVE
dc.description.keywords ALUMINUM SURFACE
dc.description.keywords FINGERPRINTS
dc.description.keywords ENHANCEMENT
dc.description.keywords POLYCYANOACRYLATE
dc.description.keywords GLUE
dc.description.keywords Controllers
dc.description.keywords DesignNeural network Æ Genetic algorithm, Fuzzy logic, Speech recognition, Pattern recognition
dc.description.keywords Fuzzy logic
dc.description.keywords Genetic algorithm
dc.description.keywords Neural network
dc.description.keywords Pattern recognition
dc.description.keywords Speech recognition
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
pubs.organisational-group /University of Technology Sydney/Strength - Health Technologies
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)


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