AI-Enhanced HR Interview Simulation for Realistic Candidate Assessment

This research study proposes an AI application for a HR interview simulation system to improve candidate assessment. The proposed system is based on the recent AI technologies that generate questions out of the candidate's resume and job description as in the case of a real interview with the employer. AI technology not only do the questioning but also get the emotional analysis of the candidate through the interview by analyzing the tone of the candidate's voice and other factors. AI-based assessment captures both cognitive and affective performance, where the candidate's merit and quality are given a true measure. This means that the proposed system greatly enhances the capabilities of the HR teams to investigate massive numbers of candidates while reducing the biases associated with conventional pure human interviews. Further, this research study aims to explain the system's architecture, where facial expression analysis and voice sentiment analysis remain as the main components alongside reinforcement learning for question adaptation. With LLM-based approach, organizations can increase the efficiency of the hiring process, enrich candidates' experience, and make better decisions.