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dc.contributor.authorKaushik, M.-
dc.contributor.authorTrinkle, M.-
dc.contributor.authorHashemi-Sakhtsari, A.-
dc.identifier.citationProceedings of the 13th Australasian International Conference on Speech Science and Technology held in Melbourne, Victoria 14-16 December 2010 / M. Tabain, J. Fletcher, D. Grayden, J. Hajek and A. Butcher (eds.): pp.98-101-
dc.description.abstractUnlike rehearsed and prepared speech, spontaneous speech contains high occurrence of disfluencies, like repetitions, filled pauses, and hesitations. Disfluencies can seriously hamper the word recognition accuracy of an Automatic Speech Recogniser (ASR), by increasing word insertion and deletion and rejection rates. In this paper we introduce signal processing algorithms to automatically identify and remove repetitions and filled pauses from spontaneous speech before passing it to an ASR for transcription. The algorithms are tested with Dragon NaturallySpeaking Speech Recogniser and show significant improvements in the word recognition accuracy, and ensuing reductions in substitution and deletion and insertion errors.-
dc.description.statementofresponsibilityMayank Kaushik, Matthew Trinkle and Ahmad Hashemi-Sakhtsari-
dc.rightsCopyright 2010 ASSTA-
dc.subjectAutomatic Speech Recognition-
dc.subjectFilled pauses-
dc.subjectLPC Technique-
dc.titleAutomatic detection and removal of disfluencies from spontaneous speech-
dc.typeConference paper-
dc.contributor.conferenceAustralasian International Conference on Speech Science and Technology (13th : 2010 : Melbourne, Victoria)-
Appears in Collections:Aurora harvest 5
Electrical and Electronic Engineering publications

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