Virtual Humans with Secrets: Learning to Detect Verbal Cues to Deception

Abstract

Virtual humans are animated, lifelike characters capable of free speech and nonverbal interaction with human users. In this paper, we describe the development of two virtual human characters for teaching the skill of deception detection. An accompanying tutoring system provides solicited hints on what to ask during an interview and unsolicited feedback that identifies properties of truthful and deceptive statements uttered by the characters. We present the results of an experiment comparing use of virtual humans with tutoring against a no-interaction (baseline) condition and a didactic condition. The didactic group viewed a slide show consisting of recorded videos along with descriptions of properties of deception and truth-telling. Results revealed that both groups significantly outperformed the no-interaction control group in a binary decision task to identify truth or deception in video statements. No significant differences were found between the training conditions.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2010
Accession Number
AD1160128

Entities

People

  • Christian A Meissner
  • H. Clifford Lane
  • Justin S. Albrechtsen
  • Mike Schneider
  • Stephen W. Michael

Organizations

  • University of Southern California

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automated Speech Recognition
  • Deception
  • Detection
  • Education
  • Feedback
  • Health Care
  • Human Behavior
  • Interviewing
  • Language
  • Law Enforcement
  • New York
  • Personality
  • Psychology
  • Social Psychology
  • Students
  • Training
  • United States
  • United States Government
  • Universities

Readers

  • Artificial Intelligence
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Cybersecurity.