Evaluation of Out of Breath Speech Using Machine Learning Approaches

dc.contributor.guideDandapat, Samarendra
dc.coverage.spatial
dc.creator.researcherSahoo, Sibasis
dc.date.accessioned2024-05-22T05:23:22Z
dc.date.available2024-05-22T05:23:22Z
dc.date.awarded2024
dc.date.completed2024
dc.date.registered2016
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.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensions
dc.format.extent
dc.identifier.urihttp://hdl.handle.net/10603/565885
dc.languageEnglish
dc.publisher.institutionDEPARTMENT OF ELECTRONICS AND ELECTRICAL ENGINEERING
dc.publisher.placeGuwahati
dc.publisher.universityIndian Institute of Technology Guwahati
dc.relation
dc.rightsself
dc.source.universityUniversity
dc.subject.keywordEngineering
dc.subject.keywordEngineering and Technology
dc.subject.keywordEngineering Electrical and Electronic
dc.titleEvaluation of Out of Breath Speech Using Machine Learning Approaches
dc.title.alternative
dc.type.degreePh.D.

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