2007 Presentations (Communicative Events)
Detecting Deception Using Critical Segments: Presentation Powerpoint Poster
We present an investigation of segments that map to GLOBAL LIES, that is, the intent to deceive with respect to salient topics of the discourse. We propose that identifying the truth or falsity of these CRITICAL SEGMENTS may be important in determining a speaker’s veracity over the larger topic of discourse. Further, answers to key questions, which can be identified a priori, may represent emotional and cognitive HOT SPOTS, analogous to those observed by psychologists who study gestural and facial cues to deception. We present results of experiments that use two different definitions of CRITICAL SEGMENTS and employ machine learning techniques that compensate for imbalances in the dataset. Using this approach, we achieve a performance gain of 23.8% relative to chance, in contrast with human performance on a similar task, which averages substantially below chance. We discuss the features used by the models, and consider how these findings can influence future research.
Files
- IS07-Enos.pdf application/pdf 419 KB Download File
More About This Work
- Academic Units
- Computer Science
- Publisher
- Interspeech 2007
- Published Here
- August 5, 2013
Notes
Presentation paper is available at http://hdl.handle.net/10022/AC:P:20108