Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{190743,
        author = {MOHAMMED MUBASHEER and ASIF HAKKI and CHANDAN GOWDA K S and NANDAN KUMAR L V and Dr. M. YASHODHA},
        title = {FULL-STACK AI INTERVIEW MOCKER},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {2992-2995},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190743},
        abstract = {The increasing competitiveness of the job market de-mands not only strong technical knowledge but also effective communication skills, confidence, and interview readiness. Traditional interview preparation methods often lack personalization and real-time feedback. This paper presents a Full-Stack AI Interview Mocker, an intelligent web-based application designed to provide automated and realistic mock interview experiences using artificial intelligence. The system integrates AI-driven question generation, voice-based response analy-sis, and performance evaluation. Experimental results indicate improved interview readiness and reduced anx-iety among users.},
        keywords = {Artificial Intelligence, Mock Interview System, Natural Language Processing, Speech-to-Text, Full-Stack Devel-opment},
        month = {January},
        }