A Review Paper On AI-based Mock Interview System

Authors: Pushpa Chavan, Sandeep Jadhav

Country: India

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Abstract: The AI-based Mock Interview System is a smart and helpful platform designed to prepare users for real-life job interviews. It begins with a simple registration process where users create an account and log in securely. Once inside the system, users are asked to upload their resumes. The system carefully analyzes each resume to understand the user’s background, such as education, skills, experience, and areas of interest. This information helps the system customize the mock interview experience for each user, making it more relevant and useful. The interview process is divided into three main sections. The first is the HR or personality round, where users are asked questions like "Tell me about yourself" or "Why should we hire you?" This part focuses on building communication skills, boosting confidence, and improving how users present themselves. The second section is the technical round, where users are given questions related to their area of study or profession. This could be about programming, electronics, mechanical systems, or any other relevant topic. Users answer these questions, and the system evaluates their responses to test their technical knowledge and clarity. In the final section, users take an aptitude test to assess their logical thinking, problem-solving skills, and reasoning abilities. This part is very similar to what many companies use in their hiring process. After all the stages are completed, the system generates a detailed performance report. This report shows how well the user did in each round, highlighting both strengths and areas where improvement is needed. By using this system regularly, users can become more confident, improve their interview skills, and increase their chances of getting hired in real interviews.

Keywords: Mock Interview System, AI-Based Interview Preparation, Resume Analysis, Performance Evaluation Report.

Paper Id: 232839

Published On: 2025-12-04

Published In: Volume 13, Issue 6, November-December 2025

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