Abstract: This paper presents AI-PrepMate: AI-Assisted Mock Interview and Feedback System, an AI-powered mock interview application designed to enhance technical interview preparation through real-time feedback and performance evaluation. Built using React, TypeScript, Firebase, and Google Gemini AI, the system enables users to log in, create mock interviews, record responses, and receive AI-generated assessments. By leveraging natural language processing (NLP) and machine learning, the platform evaluates user responses against predefined criteria, providing structured feedback to improve interview readiness. Additionally, Firebase ensures seamless data storage and authentication via Clerk, making the system scalable and secure. The application is deployed on Firebase Hosting, ensuring real-world usability. This research explores the implementation process, technical challenges, and future enhancements to optimize AI-driven interview simulations for aspiring professionals.
Keywords: Mock interview system, Natural Language Processing (NLP), Google Gemini AI, AI-driven assessment, Automated interview feedback, Firebase cloud database, Scalable web application for interview practice AI-assisted learning and evaluation.
|
DOI:
10.17148/IJARCCE.2025.14392
