1 AIT Asian Institute of Technology

Speech recognition based on Hidden Markov Model

AuthorNguyen Viet Dung
Call NumberAIT Thesis no.ISE-06-18
Subject(s)Speech perception

NoteA thesis report submitted in partial fulfillment of the requirements for the degree of Master of Engineering, School of Engineering and Technology
PublisherAsian Institute of Technology
Series StatementThesis ; no. ISE-06-18
AbstractOne concept of speech recognition is that the human utterance always contains statistical information, in which can be modeled by applying powerful mathematics. By using Hidden Markov Model approach, the speech recognition system has been implemented successfully. However, the incoming speech signal must be analyzed in the first step before going to any processing. The spectral analysis which includes Linear Predictive coding (LPC) and Vector Quantization methodology is selected for this purpose. The whole system was implemented on Matlab. With powerful tool in calculation, Matlab can solve complex mathematics problem in Hidden Markov Model. With the aim to control robot by speech, the system is speaker-dependent and has a vocabulary containing 20 English Words. The system performance efficiency is 86%
Year2006
Corresponding Series Added EntryAsian Institute of Technology. Thesis ; no. ISE-06-18
TypeThesis
SchoolSchool of Engineering and Technology (SET)
DepartmentDepartment of Industrial Systems Engineering (DISE)
Academic Program/FoSIndustrial Systems Engineering (ISE)
Chairperson(s)Manukid Parnichkun;
Examination Committee(s)Afzulpukar, Nitin V.;Bohez, Erik L. J.;
DegreeThesis (M.Eng.) - Asian Institute of Technology, 2006


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