Deception detection with machine learning: A systematic review and statistical analysis. [PDF]
Several studies applying Machine Learning to deception detection have been published in the last decade. A rich and complex set of settings, approaches, theories, and results is now available.
Constâncio AS+4 more
europepmc +2 more sources
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning [PDF]
Deception detection in conversations is a challenging yet important task, having pivotal applications in many fields such as credibility assessment in business, multimedia anti-frauds, and custom security. Despite this, deception detection research is hindered by the lack of high-quality deception datasets, as well as the difficulties of learning ...
Xiaobao Guo+5 more
arxiv +3 more sources
Over a few decades, a remarkable amount of research has been conducted in the field of speech signal processing particularly on deception detection for security applications.
Sinead V. Fernandes, Muhammad Sana Ullah
doaj +2 more sources
A Domain-Independent Holistic Approach to Deception Detection [PDF]
The deception in the text can be of different forms in different domains, including fake news, rumor tweets, and spam emails. Irrespective of the domain, the main intent of the deceptive text is to deceit the reader. Although domain-specific deception detection exists, domain-independent deception detection can provide a holistic picture, which can be ...
Sadat Shahriar+2 more
arxiv +3 more sources
The Polygraph and the Detection of Deception [PDF]
Over the last decade, Europe has seen a marked increase in the use of the polygraph for the detection of deception. Belgium and Finland nowadays regularly use polygraph tests in criminal investigations, and the United Kingdom and the Netherlands have adopted its use in the treatment and monitoring of sex offenders.
Ewout H. Meijer, Bruno Verschuère
openalex +6 more sources
You can’t kid a kidder: Association between production and detection of deception in an interactive deception task [PDF]
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
doaj +2 more sources
A Semi-Supervised Speech Deception Detection Algorithm Combining Acoustic Statistical Features and Time-Frequency Two-Dimensional Features [PDF]
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]
Deception 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
Veracity judgement, not accuracy: Reconsidering the role of facial expressions, empathy, and emotion recognition training on deception detection. [PDF]
People hold strong beliefs about the role of emotional cues in detecting deception. While research on the diagnostic value of such cues has been mixed, their influence on human veracity judgements is yet to be fully explored.
Zloteanu M+3 more
europepmc +2 more sources
Active Deception Detection [PDF]
Actively detecting deception requires (a) gathering information for fact-checking the communication content, (b) strategically prompting deception cues, and (c) encouraging honest admissions and discouraging continued deceit. Most deception-detection research, active or otherwise, finds that people are only slightly better than chance at correctly ...
Timothy R. Levine
openalex +2 more sources