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 +4 more sources
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
doaj +4 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Lying takes time : a meta-analysis on reaction time measures of deception [PDF]
, 2017 Lie detection techniques are frequently used, but most of them have been criticized for the lack of empirical support for their predictive validity and presumed underlying mechanisms.
Ben-Shakhar, Gershon +4 more
core +15 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
doaj +1 more source
Detecting Deceptive Behaviours through Facial Cues from Videos: A Systematic Review
Applied Sciences, 2023 Interest in detecting deceptive behaviours by various application fields, such as security systems, political debates, advanced intelligent user interfaces, etc., makes automatic deception detection an active research topic.
Arianna D’Ulizia +3 more
doaj +1 more source