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 |