Voting-based Multimodal Automatic Deception Detection

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  • DOI 10.48550/arxiv.2307.07516
  • OpenAlex ID W4384652125
  • Type Preprint
  • Language EN
  • Published 30 Jun 2023
  • Source arXiv (Cornell University)
  • Publisher Cornell University
  • Countries 1
  • Institutions 1
  • Added 19 Jul 2023
  • Updated 03 Oct 2026
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Voting-based Multimodal Automatic Deception Detection

Preprint 2023 EN Green

Automatic Deception Detection has been a hot research topic for a long time, using machine learning and deep learning to automatically detect deception, brings new light to this old field. In this paper, we proposed a voting-based method for automatic deception detection from videos using audio, visual and lexical features. Experiments were done on two datasets, the Real-life trial dataset by Mich…

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5 authors
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1 Lana Touma Arab International University (SY) —
2 Mohammad Al Horani Arab International University (SY) —
3 Manar Tailouni Arab International University (SY) —
4 Anas Dahabiah Arab International University (SY) —
5 Khloud Al Jallad —

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