AI-Based Realistic HR Interview Simulator

Interview performance can be considered an essential factor of employability, and most job seekers cannot access realistic, adaptive interview preparation aids. The current AI-based HR interview systems are mainly aimed at candidate screening to hire and lack the interactive practice systems with extensive development capabilities. The following paper introduces a sophisticated AI-based HR interview simulator that is specifically developed and focused on interview preparation and covers the main shortcomings of the existing systems such as a lack of transparency, insufficient quality of feedback, a lack of multimodal analysis, and poor adaptability. The suggested system has Large Language Models (LLMs) and reinforcement learning to generate questions dynamically and context-sensitive, and Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Computer Vision to perform multimodal assessment. The system records cognitive and affective aspects of the interview performance based on the attention-based multimodal fusion and gives a transparent and hierarchical feedback to provide fair and inclusive interview preparation. The study would add to the provision of a thorough framework on responsible AI-based interview preparation, the importance of explainability, fairness, and holistic skill development. Active