A Multimodal Dataset for Deception Detection
Verónica Pérez-Rosas, Rada Mihalcea, Alexis Narvaez, Mihai Burzo
Abstract
This paper presents the construction of a multimodal dataset for deception detection, including physiological, thermal, and visual responses of human subjects under three deceptive scenarios. We present the experimental protocol, as well as the data acquisition process. To evaluate the usefulness of the dataset for the task of deception detection, we present a statistical analysis of the physiological and thermal modalities associated with the deceptive and truthful conditions. Initial results show that physiological and thermal responses can differentiate between deceptive and truthful states.- Anthology ID:
- L14-1673
- Volume:
- Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
- Month:
- May
- Year:
- 2014
- Address:
- Reykjavik, Iceland
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 3118–3122
- Language:
- URL:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/869_Paper.pdf
- DOI:
- Cite (ACL):
- Verónica Pérez-Rosas, Rada Mihalcea, Alexis Narvaez, and Mihai Burzo. 2014. A Multimodal Dataset for Deception Detection. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 3118–3122, Reykjavik, Iceland. European Language Resources Association (ELRA).
- Cite (Informal):
- A Multimodal Dataset for Deception Detection (Pérez-Rosas et al., LREC 2014)
- PDF:
- http://www.lrec-conf.org/proceedings/lrec2014/pdf/869_Paper.pdf