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{199283,
        author = {Bojja Srija and T. Sukanya and Sarmishta Alli and Kocheruvu Sankeerthana and Gollapelly Rishwitha},
        title = {PrepGenie: A Voice-Interactive AI System for Mock Interviews and Automated Candidate Feedback},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {14085-14092},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199283},
        abstract = {Abstract-Practice Interview preparation takes much practice, communicating, and feedback, and in many cases, students and young workers do not have a chance to practice on a real interview. This paper suggests coming up with a voice interactive AI based interview practice tool named “PrepGenie”, which will be competent. of simulating interviewing and feed- backing. The tool will be made in such a way that the interviewee can tailor the interview, type of interview, job position, the technology stack, and the quantity of interview questions. The interview the speech-to-text feature of the tool will be used to start the completion of will. the interviewee will speak out the answers that will be followed. interview questions are being made by the large language model. regarding the stance of the interviewee. The tool will also be able to have feedback towards the end of the interview. session. The tool will be in a position to offer evaluations which are applicable, and emphasizing the strengths, weaknesses, of the interviewee. opportunities, and threats. The tool will also be capable of saving. the history of the interview session, therefore, assisting the interviewee to follow. the interview develops with time. The tool’s architecture will contain a web client, a server powered by node.js/express, WebSocket, AI, and database. The creation of the tool will be in a position to demonstrate. the feasibility of voice based conversational AI systems.},
        keywords = {Mock Interviews, Voice Interaction, Large Language Models, Speech-to-Text, Structured Feedback, WebSocket, Natural Language Processing, Prompt Engineering.},
        month = {April},
        }