Multimodal Detection of Deception using Fusion of Reaction Time and P300 Component

Mohammadian, Amin; Abootalebi, Vahid; Moradi, Mohammad Hassan; Khalilzadeh, Mohammad A.

doi:10.1109/cibec.2008.4786064

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Cited by 4 publications

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“…Pennebaker and colleagues [11] report on a psycholinguistic study, where they conduct a qualitative analysis of true and false stories by using word counting tools. Studies have also been made in neuroscience, such as the one reported in [10], where EEG signals are used to predict deceit.…”

Section: Related Workmentioning

confidence: 99%

Automatic detection of deceit in verbal communication

Mihalcea

Pérez-Rosas

Burzo

2013

Proceedings of the 15th ACM on International Conference on Multimodal Interaction

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This paper presents experiments in building a classifier for the automatic detection of deceit. Using a dataset of deceptive videos, we run several comparative evaluations focusing on the verbal component of these videos, with the goal of understanding the difference in deceit detection when using manual versus automatic transcriptions, as well as the difference between spoken and written lies. We show that using only the linguistic component of the deceptive videos, we can detect deception with accuracies in the range of 52-73%.

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Section: Related Workmentioning

confidence: 99%

Automatic detection of deceit in verbal communication

Mihalcea

Pérez-Rosas

Burzo

2013

Proceedings of the 15th ACM on International Conference on Multimodal Interaction

View full text Add to dashboard Cite

show abstract

“…Pennebaker and colleagues [13] report on a psycholinguistic study, where they conduct a qualitative analysis of true and false stories by using word counting tools. Studies have also been made in neuroscience, such as the one reported in [11], where EEG signals are used to predict deceit.…”

Section: Related Workmentioning

confidence: 99%