Role Focused Mock Interview System with Personalized Evaluation

Abstract

With the fierce competition in today’s job markets, many students find themselves having difficulties during the interview process due to nervousness, lack of confidence, and absence of real-time personalized feedback. Traditional interview practice tools and techniques are manual, biased, and ineffective in creating an environment close to the actual interviews. This paper provides an AI-driven mock interview tool that is capable of creating a true-to-life simulation environment and giving an objective assessment of candidates. Computer vision and speech recognition are employed in this tool to evaluate a candidate’s emotional state, confidence, and overall presentation skills through facial expression detection and speech analysis. Moreover, questions for each interview are automatically selected through Natural Language Processing algorithms based on candidates’ resumes or particular job descriptions. As a result, the created system is not only highly customizable but also provides personalized feedback on each candidate’s performance without reliance on human evaluators.