2023
DOI: 10.1007/s11042-023-16769-w
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Explainable Enhanced Recurrent Neural Network for lie detection using voice stress analysis

Fatma M. Talaat

Abstract: Lie detection is a crucial aspect of human interactions that affects everyone in their daily lives. Individuals often rely on various cues, such as verbal and nonverbal communication, particularly facial expressions, to determine if someone is truthful. While automated lie detection systems can assist in identifying these cues, current approaches are limited due to a lack of suitable datasets for testing their performance in real-world scenarios. Despite ongoing research efforts to develop effective and reliab… Show more

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Cited by 4 publications
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“…Impressively, the proposed ERNN achieves an accuracy of 77.3%. This finding holds significant relevance for voice stress analysis, indicating the potential to detect patterns in the voices of individuals experiencing stress [8]. Felipe and others construct a neural network to assess a person"s voice and classify his speech as reliable or not.…”
Section: Related Workmentioning
confidence: 99%
“…Impressively, the proposed ERNN achieves an accuracy of 77.3%. This finding holds significant relevance for voice stress analysis, indicating the potential to detect patterns in the voices of individuals experiencing stress [8]. Felipe and others construct a neural network to assess a person"s voice and classify his speech as reliable or not.…”
Section: Related Workmentioning
confidence: 99%