Lie Detection Based on Acoustic Analysis

Acoustic lie detection, prized for its covert nature and capability for remote processing, has spurred growing interest in acoustic features that can reliably aid in lie detection. In this study, the aim was to construct an acoustic polygraph based on a variety of phonetic and acoustic features rather than on electrodermal, cardiovascular, and respiratory values.

Sixty-two participants from the University of Science and Technology of China, aged 18-30 years old, were involved in the mock crime experiment and were randomly assigned to the innocent and guilty groups. We collected 31 deceptive and truthful audios to analyze the performance of voice onset time (VOT) in lie detection.

Our findings revealed that VOT performed well in lie detection. Both the average sensitivity and specificity of the area under the curve are 0.888, and its lower and upper confidence limit are up to 0.803 and 0.973 respectively at the 95% confidence level. Although the other acoustic features had a lower reference value, they also provided a general trend in the judgment of lie detection.

Our results suggested that some acoustic features can be effectively used as aids to lie detection. Through a similar approach, we will explore more acoustic and phonetic features that contribute to detecting lies in the future.