Evaluation of Out-of-Breath Speech Using Machine Learning Approaches

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dc.contributor.authorSahoo, Sibasis
dc.date.accessioned2024-05-17T10:27:34Z
dc.date.available2024-05-17T10:27:34Z
dc.date.issued2024
dc.descriptionSupervisor: Dandapat, Samarendra
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.identifier.otherROLL NO.166302009
dc.identifier.urihttps://gyan.iitg.ac.in/handle/123456789/2614
dc.language.isoen
dc.relation.ispartofseriesTH-3341
dc.titleEvaluation of Out-of-Breath Speech Using Machine Learning Approaches
dc.typeThesis
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