Deception Detection Using Facial and Audio Transcript Features: A Review

Sheshang Degadwala and Radhika Thakkar

International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2024, vol. 10, issue 5, 36-46

Abstract: Deception detection through facial and audio transcript features has gained traction due to its potential in enhancing security and communication integrity. This review aims to consolidate existing research on leveraging facial and audio features for identifying deceptive behavior. The motivation behind this study is the increasing demand for reliable deception detection mechanisms in various domains, including security and psychology. Despite advancements, limitations persist in achieving high accuracy across diverse contexts and individual differences. The objective of this review is to evaluate the effectiveness of different methods used in detecting deception from facial expressions and audio cues, identifying strengths and weaknesses of each approach, and suggesting future directions for improving accuracy through advanced techniques.

Keywords: Deception Detection; Facial Features; Audio Transcripts; Machine Learning; Deep Learning; Multimodal Analysis; Feature Extraction (search for similar items in EconPapers)
Date: 2024
Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT2410584
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Persistent link: https://EconPapers.repec.org/RePEc:jbh:ijsrcs:v10:y2024:i5:id:291

DOI: 10.32628/CSEIT2410584

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