Automated Dyadic Data Recorder (ADDR) Framework and Analysis of Facial Cues in Deceptive Communication

Abstract

We developed an online framework that can automatically pair two crowd-sourced participants, prompt them to follow a research protocol, and record their audio and video on a remote server. The framework comprises two web applications: an Automatic Quality Gatekeeper for ensuring only high quality crowd-sourced participants are recruited for the study, and a Session Controller which directs participants to play a research protocol, such as an interrogation game. This framework was used to run a research study for analyzing facial expressions during honest and deceptive communication using a novel interrogation protocol. The protocol gathers two sets of nonverbal facial cues in participants: features expressed during questions relating to the interrogation topic and features expressed during control questions. The framework and protocol were used to gather 151 dyadic conversations (1.3 million video frames). Interrogators who were lied to expressed the smile-related lip corner puller cue more often than interrogators who were being told the truth, suggesting that facial cues from interrogators may be useful in evaluating the honesty of witnesses in some contexts. Overall, these results demonstrate that this framework is capable of gathering high quality data which can identify statistically significant results in a communication study.