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Improving searchability of automatically transcribed lectures through dynamic language modelling

dc.contributor.advisorMbogho, Audrey J Wen_ZA
dc.contributor.authorMarquard, Stephenen_ZA
dc.date.accessioned2015-01-02T09:26:51Z
dc.date.accessioned2018-11-26T13:53:27Z
dc.date.available2015-01-02T09:26:51Z
dc.date.available2018-11-26T13:53:27Z
dc.date.issued2012en_ZA
dc.identifier.citationMarquard, S. 2012. Improving searchability of automatically transcribed lectures through dynamic language modelling. Masters’ Thesis. University of Cape Town.
dc.identifier.urihttp://hdl.handle.net/11427/11050
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/11427/11050
dc.description.abstractRecording university lectures through lecture capture systems is increasingly common. However, a single continuous audio recording is often unhelpful for users, who may wish to navigate quickly to a particular part of a lecture, or locate a specific lecture within a set of recordings. A transcript of the recording can enable faster navigation and searching. Automatic speech recognition (ASR) technologies may be used to create automated transcripts, to avoid the significant time and cost involved in manual transcription.en_ZA
dc.language.isoengen_ZA
dc.subject.otherInformation Technologyen_ZA
dc.titleImproving searchability of automatically transcribed lectures through dynamic language modellingen_ZA
dc.typeThesisen_ZA
dc.type.qualificationlevelMastersen_ZA
dc.type.qualificationnameMPhilen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.departmentDepartment of Computer Scienceen_ZA


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