AI-Powered Mock Interview Analyzer for Intelligent Candidate Evaluation

Authors:

M.S.B. Deepthi, Yasodha Relli, Adari Sri Hari Yaswanth, Gundu Dinesh Kumar, Mandala Prazna

MVGR College of Engineering, Vizianagaram, India

Abstract—The increasing competition in the job market has made interview preparation a critical aspect of career success. Traditional mock interview systems are often time-consuming, inconsistent, and lack personalized feedback. This paper presents an AI- Powered Mock Interview Analyzer that leverages Natural Language Processing (NLP) and Large Language Models (LLMs) to simulate real interview scenarios and provide intelligent evaluation.

The system dynamically generates technical and HR questions based on candidate profiles and evaluates responses for relevance, accuracy, grammar, fluency, and confidence. It integrates speech-to-text conversion for voice-based responses and employs facial emotion recognition using CNN and MobileNetV2 to assess non- verbal communication. The platform provides real-time feedback, performance scoring, and progress tracking through an interactive dashboard.

By combining AI-driven evaluation with user-friendly design, the proposed system enhances interview readiness, improves communication skills, and provides a scalable solution for personalized career preparation

Index Terms—Artificial Intelligence, Mock Interview, NLP, Large Language Models, Emotion Recognition, CNN, MobileNetV2, Recruitment Systems