Audio Multi-Issue Deception Testing With Oculomotor Tracking
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Solution Overview
Problem
Existing deception detection technologies rely on examinees reading written text, limiting their application to those with reading ability and introducing examiner bias and fatigue.
Innovation Solution
An automated audio multi-issue comparison test (AMCT) using eye tracking and audio presentation of statements, allowing for deception detection without reading, with pre-test instructions and high-precision eye tracking to record ocular-motor responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If written text is used to present questions or statements to examinees, then the examinee can comprehend the material, but the application is limited to persons with reading ability
Solution Approach 1:
The patent replaces the visual-mechanical system of reading written text with an auditory system by using audio recording to present test questions and statements. This substitution allows examinees without reading ability to comprehend and respond to test material, thereby expanding the applicability of the deception detection system to a broader population while maintaining the integrity of the testing process
2Reliability
If examiners manually conduct deception detection testing, then they can provide guidance and support to examinees, but examiner fatigue and bias corrupt the testing process
Solution Approach 1:
The patent implements an automated testing system where the computerized platform independently presents test questions via audio recording, automatically records oculomotor measures through eye tracking technology, and processes responses without requiring continuous examiner intervention. This self-service approach eliminates examiner fatigue and bias from the testing process, ensuring consistent and objective deception detection across all examinees while maintaining ease of administration
Solution Approach 2:
The system incorporates automated feedback mechanisms where the computer immediately processes examinee responses and records oculomotor data, providing real-time feedback to maintain engagement. The automated feedback loop ensures consistent application of deception detection criteria without being influenced by examiner state, thereby improving reliability while reducing the burden on examiners
Data Source
AI summary
Automated audio multi-issue comparison test (AMCT) protocols for deception detection. In one exemplary embodiment, testing equipment that may include an eye tracking device, such as an infrared camera, computer, keyboard, mouse, chin rest, and audio output device (headphones or speaker) is used. A series of Agree and Disagree statements regarding issues of interest are presented to the examinee in an audio format as by text-to-speech narration. Each statement must include an introductory phrase, topic phrase and declaration phrase. As statements are presented, a neutral image is presented on a visual display, then replaced by an image prompting the examinee to provide a response when the statement concludes. The eye tracker measures and records eye movements during the test. At the conclusion, ocular-motor measures and test question responses are combined by means of a logistic regression equation to compute the probability of deception.