Abstract
Transitioning from the military to the civilian lifestyle, especially for military veterans who decide to pursue careers in the civilian workforce, is often a difficult experience. The job interview, a task in which the interviewees meet and discuss their skills and career goals with strangers in a position of authority, is the first step of assimilation into the civilian workplace, which might cause them to experience nervousness or anxiety. This feeling of excessive stress may compromise the interviewee's performance, therefore potentially impeding their successful transition to the workforce. Intelligent interview training technologies would benefit from automated stress detection systems that could assist interviewees in better understanding causes and antecedents of stressors during their interaction with the interviewer. This paper examines self-reported and bio-behavioral measures of stress experienced during mock job interviews conducted with 24 U.S. military veterans. Self-reported measures were captured via a global measure of stress reported by the participant at the conclusion of the interview, and a continuous moment-to-moment annotation of stress resulting from the retrospective inspection of the interview video recording. Bio-behavioral indices of stress include physiological reactivity measures captured via electrodermal activity and electrocardiogram signals, as well as acoustic measures extracted from speech. Results indicate that physiological reactivity measures exhibit moderate-to-strong correlation with self-reported measures of stress, and can be thus used to estimate the self-reported stress measures. Augmenting the feature space with demographic and psychological traits can further improve the accurate detection of stress during the interviews.
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