dc.contributor.authorTan, Chin Tuan.en_US
dc.date.accessioned2009-12-14T06:21:45Z
dc.date.available2009-12-14T06:21:45Z
dc.date.copyright1995en_US
dc.date.issued1995
dc.identifier.urihttp://hdl.handle.net/10356/19688
dc.description.abstractIn most speech recognition evaluation studies, the focus is usually on one single speech recognition technique such as Discrete Hidden Markov Modeling with codebooks of different sizes. Inter-technique comparison study using a com-mon database has not been systematically explored. In this thesis, a com-parative study on three speech recognition techniques namely, Dynamic Time Warping (DTW), Discrete Hidden Markov Modeling (DHMM) and Neural Net-work(Multilayer Perceptron) (NN(MLP)) was conducted using one common database.en_US
dc.format.extent189 p.
dc.language.isoen
dc.rightsNANYANG TECHNOLOGICAL UNIVERSITYen_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleComparison of speech recognition techniques in a noisy environmenten_US
dc.typeThesisen_US
dc.contributor.supervisorChang, Joseph Sylvester.en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMASTER OF ENGINEERING(EEE)en_US


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