Abstract

Job interviews are a predominant part of any hiring process to evaluate applicants. It is used to evaluate applicant's knowledge, skills, abilities, and behavior in order to select the most suited person for the job. Recruiters make their opinion, on the basis of both verbal and nonverbal communication of an interviewee. Our behavior and communication in daily life are cross-modal in nature. Facial expression, hand gestures and body postures are closely linked to speech and hence enrich the vocal content. Nonverbal communication plays an important role in what we are saying and what we actually mean to say. It carries relevant information that can reveal social construct of a person as diverse as his personality, state of mind, or job interview outcome; they convey information in parallel to our speech. In this paper, we present an automated, predictive expert system framework for the computational analysis of HR Job interviews. The system includes analysis of facial expression, language and prosodic details of the interviewees and thereby quantifies their verbal and nonverbal behavior. The system predicts the rating on the overall performance of the interviewee and on each behavior traits and hence predict their personality and hireability.

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