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GRENZE International Journal of Engineering and Technology Vol. 12 (2026), Issue 1

AI-Powered Mock Interview System and Resume Analyzer

Authors

Preeti Bailke, Jiya Bardiya, Shrirang Bhende, Yash Bhosale, Dhanashree Borkar

Abstract

In the current tough employment market being technically competent is not sufficient to succeed in a job interview. The soft skills like communication, confidence, and knowledge of the sphere are outstanding in evaluating candidates. We suggest designing an AIenabled Smart Resume Analyzer and Mock Interview Evaluation System to fill that gap and enable students and other job seekers to better prepare before an interview. This system combines the use of a resume analyzer, automated resume grading, a resume builder and an interview simulator that rates a user based on real-time feedback. The resume analyzer tool employs techniques to process the resume and grade it against keywords, job standard formatting and the criteria of Applicant Tracking Systems. The resume builder enables a user to make professional resumes through just filling his/her information into ready-made templates. The system as well provides intelligent video suggestions to make users ready to get the desired positions. The best part of the system is the AI-based mock interview that enables the user to experience a simulated interview using the selected level of experience (beginner, intermediate, or expert) and job domain. The module incorporates sentiment analysis, NLP, speech-to-text processing, and a semantic similarity score judging the responses of the user. The level of confidence is estimated on the basis of facial expression analysis and voice features, which provides detailed information about performance. It is a multi-featured platform that enables complex self-assessment and preparation and uses aspects of natural language processing, machine learning, and behavioral analysis. It makes the latter process more convenient, prompt, interesting, and customized by optimizing it with an automated awareness of learners.

Grenze ID: 01.GIJET.12.1.821
Pages: 4352 - 4358