Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/565885
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dc.date.accessioned2024-05-22T05:23:22Z-
dc.date.available2024-05-22T05:23:22Z-
dc.identifier.urihttp://hdl.handle.net/10603/565885-
dc.description.abstractStress alters the speech production mechanism. Factors like emotion, cognitive load, pathology, noisy condition (Lombard effect), physical load, sleep deprivation, etc., affect speech production. Among these, speech under emotional, noisy, and pathological conditions are investigated extensively. Little light has been shed on speech under physical load conditions, called out-of-breath speech. Such evaluation of out-of-breath conditions can be used in context-aware speech interfaces to estimate the workload level, exercise intensity of an athlete, and physical fitness of a person.
dc.format.extent
dc.languageEnglish
dc.relation
dc.rightsself
dc.titleEvaluation of Out of Breath Speech Using Machine Learning Approaches
dc.title.alternative
dc.creator.researcherSahoo, Sibasis
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.description.note
dc.contributor.guideDandapat, Samarendra
dc.publisher.placeGuwahati
dc.publisher.universityIndian Institute of Technology Guwahati
dc.publisher.institutionDEPARTMENT OF ELECTRONICS AND ELECTRICAL ENGINEERING
dc.date.registered2016
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:DEPARTMENT OF ELECTRONICS AND ELECTRICAL ENGINEERING

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