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The Silent Talker Lie Detector

Silent Talker is a Lie Detector which observes and analyses non-verbal behaviour in the form of micro-gestures while a subject is being interviewed. It is grounded in the psychological theory that non-verbal behaviour is modified by a number of influences when a person is being deceptive. These include arousal ( in particular stress), cognitive load, duping delight and behaviour control.

Silent Talker was invented between 2000 and 2002 by a team at Manchester Metropolitan University by Zuhair Bandar, David McLean, James O’Shea and Janet Rothwell.

History

Following its invention, the Silent Talker Adaptive Psychological Profiling architecture with the specific instantiation as a lie detector, was patented internationally ^[1]. The Silent Talker Ltd. spinout company was formed to commercialise the invention and investment funding obtained. Technically, the code was ported to various programming languages and speeded up from near real-time to real-time response. An independent study (citation required) found evidence to support the hypothesis that Silent Talker is effective at detecting lying amongst psychopaths. A study is currently underway to adapt the technology to the measurement of comprehension amongst participants giving informed consent to take part in clinical trials.

Testing procedure

The subject of the interview is observed by one or more cameras (e.g. head-and-shoulders, full body view, thermal imaging camera), which input the video stream to a conventional computer. As the interview takes place, Silent talker’s model of truthful vs. deceptive behaviour is used to classify the answers to the questions as truthful or deceptive in real-time. This can be as a classification at the end of the answer to a question or as a continuous monitoring stream during the interview. No calibration is required to tune the system to individuals and no training of the interviewer is required to interpret the Silent Talker classifications.

Validity

Silent Talker is analogous to the manual frame-by-frame system established by Paul Ekman and used with Facial Action Coding for purely facial micro-gestures. The differences are: Silent Talker uses banks of Artificial Neural Network classifiers to identify features and microgestures. The microgestures are coded into channels over a time period. Finally, the relationships between events in the channels over the time period are analysed by Artificial Neural Networks to make the classification. The neural networks used were trained using video data collected from experiments and thus discovered which features weer important and the rlationships between them that discriminate between deceptive and truthful non-verbal behaviour. Silent Talker has been published in peer-reviewed journals for both the Psychology ^[2] and Artificial Intelligence ^[3] communities.

Countermeasures

As other lie detectors detect changes in stress, the most common approach is to disrupt this either by practicing calming techniques during lying or artificially raising stress during truth-telling. Because Silent Talker is based on a multi-factor model including cognitive load, duping delight and behaviour control, its inventors claim that it is robust to countermeasures. In fact it is believed that because a large number of channels are used, attempts at behaviour control will generate more incongruities between channels which can be detected. Further experimental trials are required to investigate this hypothesis.

Some reactions to Silent Talker

The Independent newspaper

http://www.independent.co.uk/news/science/truth-machine-means-liars-must-keep-a-straight-face-604482.html

The Guardian http://www.guardian.co.uk/politics/2003/jun/19/labour.comment

The Times http://www.timesonline.co.uk/tol/life_and_style/education/article438756.ece

BBC Radio 4 The material World http://www.bbc.co.uk/radio4/science/thematerialworld_20030130.shtml

BBC News http://news.bbc.co.uk/1/hi/england/2944563.stm

CBS News http://www.cbsnews.com/stories/2003/01/28/tech/main538242.shtml

ABC news http://www.abc.net.au/rn/scienceshow/stories/2009/2674304.htm

The Engineer http://www.theengineer.co.uk/in-depth/the-truth-will-out/278743.article

The Scottish Herald http://www.heraldscotland.com/truth-behind-an-industry-full-of-fibs-1.840722

The Futurist http://pqasb.pqarchiver.com/futurist/results.html?QryTxt=New+System+Reads+Body+Language.+The+Futurist Lie detector

References

^ Bandar,J., McLean,D., O’Shea, J. and Rothwell, J. ANALYSIS OF THE BEHAVIOUR OF A SUBJECT WO02087443, http://www.europatentbox.com/patent/EP1383430B1/claim/1934310.html
^ Rothwell, J. Bandar, Z. O’Shea, J. McLean, D. Silent talker: a new computer-based system for the analysis of facial cues to deception, Journal of Applied Cognitive Psychology, Volume 20, Issue 6, pages 757–777, September 2006. doi: 10.1002/acp.1204 Final article format: http://onlinelibrary.wiley.com/doi/10.1002/acp.1204/abstract
^ Rothwell, J. Bandar, Z. O’Shea, J. McLean, D. Charting the behavioural state of a person using a Backpropagation Neural Network. Journal of Neural Computing and Applications. DOI 10.1007/s00521-006-0055-9. 2006.

[1] Bandar,J., McLean,D., O’Shea, J. and Rothwell, J. ANALYSIS OF THE BEHAVIOUR OF A SUBJECT WO02087443, http://www.europatentbox.com/patent/EP1383430B1/claim/1934310.html

[2] Rothwell, J. Bandar, Z. O’Shea, J. McLean, D. Silent talker: a new computer-based system for the analysis of facial cues to deception, Journal of Applied Cognitive Psychology, Volume 20, Issue 6, pages 757–777, September 2006. doi: 10.1002/acp.1204 Final article format: http://onlinelibrary.wiley.com/doi/10.1002/acp.1204/abstract

[3] Rothwell, J. Bandar, Z. O’Shea, J. McLean, D. Charting the behavioural state of a person using a Backpropagation Neural Network. Journal of Neural Computing and Applications. DOI 10.1007/s00521-006-0055-9. 2006.

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