A hybrid architecture for recognising speech signals in Malayalam

dc.contributor.guideDavid Peter S and Poulose, Jacob Ken_US
dc.coverage.spatialComputer Scienceen_US
dc.creator.researcherSonia Sunnyen_US
dc.date.accessioned2014-09-23T09:57:15Z
dc.date.available2014-09-23T09:57:15Z
dc.date.awarded14/03/2014en_US
dc.date.completed05/09/2013en_US
dc.date.issued2014-09-23
dc.date.registered14/6/2008en_US
dc.description.abstractnewline Speech is the primary most prominent and convenient means of communication in newlineaudible language Through speech people can express their thoughts feelings or perceptions by the articulation of words Human speech is a complex signal which is non stationary in nature It consists of immensely rich information about the words spoken accent attitude of the speaker expression intention sex emotion as well as style The main objective of Automatic Speech Recognition is to identify whatever people speak by means of newlinecomputer algorithms This enables people to communicate with a computer in a natural spoken language Automatic recognition of speech by machines has been one of the most exciting significant and challenging areas of research in the field of signal processing over the past five to six decades Despite the developments and intensive research done in this area the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam newlineen_US
dc.description.note-en_US
dc.format.accompanyingmaterialNoneen_US
dc.format.dimensions-en_US
dc.format.extent-en_US
dc.identifier.urihttp://hdl.handle.net/10603/25496
dc.languageEnglishen_US
dc.publisher.institutionDepartment of Computer Scienceen_US
dc.publisher.placeCochinen_US
dc.publisher.universityCochin University of Science and Technologyen_US
dc.relation-en_US
dc.rightsuniversityen_US
dc.source.universityUniversityen_US
dc.subject.keywordAutomatic Speech Recognitionen_US
dc.subject.keywordSpectral Feature Extractionen_US
dc.subject.keywordSpeech Recognition Systemsen_US
dc.subject.keywordSpeech Recognition System using LPCen_US
dc.subject.keywordSpeech Recognition System using MFCCen_US
dc.titleA hybrid architecture for recognising speech signals in Malayalamen_US
dc.title.alternative-en_US
dc.type.degreePh.D.en_US

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