Paper Title
Implementing AI-Based Mock Interview System Using Natural Language Processing

Abstract
Effective interview preparation requires both technical proficiency and strong communication skills; however, current resources often lack interactive, personalized feedback. The AI Mock Interview System addresses this gap through an intelligent, automated platform that simulates real-world interviews and delivers real-time evaluation. It features two key modules—Technical and HR Interviews—that assess user responses based on accuracy, clarity, problem-solving ability, and communication skills, including tone and structure. The system analyzes both spoken and written input using speech recognition and NLP techniques to generate detailed performance insights. Unlike traditional mock interviews dependent on human evaluators, this platform ensures consistency and fairness by offering automated, unbiased scoring and targeted feedback. It also provides personalized suggestions for improvement, allowing users to iteratively refine both hard and soft skills. Designed for students, professionals, and job seekers, the platform promotes confidence and readiness for actual interviews. With its scalable architecture and adaptive learning capabilities, the AI Mock Interview System transforms conventional interview preparation into an efficient, data-driven, and accessible experience—bridging the gap between technical knowledge and communication excellence in today’s competitive job landscape. Keywords - AI Mock Interview System, Interview Preparation, Real-time Feedback, Technical and HR Interviews, Communication Skills, NLP, Adaptive Learning