A Semi-Supervised Speech Deception Detection Algorithm Combining Acoustic Statistical Features and Time-Frequency Two-Dimensional Features [PDF]
Brain Sciences, 2023 Human lying is influenced by cognitive neural mechanisms in the brain, and conducting research on lie detection in speech can help to reveal the cognitive mechanisms of the human brain.
Hongliang Fu +4 more
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Multimodal machine learning for deception detection using behavioral and physiological data [PDF]
Scientific ReportsDeception detection is crucial in domains like national security, privacy, judiciary, and courtroom trials. Differentiating truth from lies is inherently challenging due to many complex, diversified behavioural, physiological and cognitive aspects ...
Gargi Joshi +17 more
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Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study [PDF]
JMIR AIBackgroundArtificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical documentation and decision-making. In parallel, AI-enabled deception detection, which leverages multimodal
Sayde Leya King +3 more
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A deception detection model by using integrated LLM with emotion features [PDF]
Scientific ReportsTraditional lie detection relies on the experience of human interrogators, making it susceptible to subjective factors and leading to misjudgments. To solve this problem, we propose an emotion-enhanced deception detection model, Lie Detection using ...
Chucheng Zhou +3 more
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Frontiers in Human Neuroscience, 2012 Both the ability to deceive others, and the ability to detect deception, have long been proposed to confer an evolutionary advantage. Deception detection has been studied extensively, and the finding that typical individuals fare little better than ...
Gordon R.T. Wright +2 more
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Self and other-perceived deception detection abilities are highly correlated but unassociated with objective detection ability: Examining the detection consensus effect [PDF]
Scientific ReportsSubjective lying rates are often strongly and positively correlated. Called the deception consensus effect, people who lie often tend to believe others lie often, too.
David M. Markowitz
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LegalEye: Multimodal Court Deception Detection Across Multiple Languages [PDF]
Behavioral SciencesThis study introduces LegalEye, a multimodal machine-learning model developed to detect deception in courtroom settings across three languages: English, Spanish, and Tagalog.
Rommel Isaac A. Baldivas +8 more
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Improved semi-supervised autoencoder for deception detection. [PDF]
PLoS ONE, 2019 Existing algorithms of speech-based deception detection are severely restricted by the lack of sufficient number of labelled data. However, a large amount of easily available unlabelled data has not been utilized in reality.
Hongliang Fu +4 more
doaj +2 more sources
Contextual considerations for deception production and detection in forensic interviews
Frontiers in Psychology, 2023 Most deception scholars agree that deception production and deception detection effects often display mixed results across settings. For example, some liars use more emotion than truth-tellers when discussing fake opinions on abortion, but not when ...
David M. Markowitz +3 more
doaj +1 more source
HOW PEOPLE [TRY TO] DETECT LIES IN EVERYDAY LIFE [PDF]
Trames, 2021 Laboratory-based deception-detection experiments often fail to capture the features of everyday life lie detection among ordinary citizens. In this study, we examined how people [try to] detect deception in real life.
Nuria Sánchez +2 more
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