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dc.contributor.advisor De Silva C
dc.contributor.author Fernando MLM
dc.date.accessioned 2022
dc.date.available 2022
dc.date.issued 2022
dc.identifier.citation Fernando, M.L.M. (2022). Intelligent deception detection for online interviews [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/21634
dc.identifier.uri http://dl.lib.uom.lk/handle/123/21634
dc.description.abstract When it comes to human communication, lying is a common practice. Recently, the detection of lies has become an important focus of judiciary, law enforcement, and security, interviews, etc.[1] Due COVID-19 the pandemic of interviews being conducted online; this is a main problem where a person may give false information specially in the visa applying process. Nonverbal behavior is constantly being transmitted by humans in opposition to spoken language. where visual and auditory cues like facial expressions, postures, gestures, and nonverbal vocal sounds can be used to detect deception intelligently. These human signals are known as deception indicators, and they are primarily associated with deceptive communication. The hiring of unskilled workers can eventually lead to a company's demise if an online interviewer exaggerates or fabricates his or her abilities. en_US
dc.language.iso en en_US
dc.subject INTELLIGENT DECEPTION DETECTION en_US
dc.subject ONLINE INTERVIEWS en_US
dc.subject FACIAL EXPRESSIONS en_US
dc.subject VOCAL EXPRESSIONS en_US
dc.subject INFORMATION TECHNOLOGY -Dissertation en_US
dc.subject COMPUTER SCIENCE & ENGINEERING -Dissertation en_US
dc.subject COMPUTER SCIENCE -Dissertation en_US
dc.title Intelligent deception detection for online interviews en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree MSc In Computer Science and Engineering en_US
dc.identifier.department Department of Computer Science and Engineering en_US
dc.date.accept 2022
dc.identifier.accno TH4987 en_US


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