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@article{198744,
        author = {Dr. M. V. Pradhan and Swaraj Sawant and Soham Manjare and Shivam Wayal and Uday Kunjir},
        title = {AI-Powered Mock Interview Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {13308-13314},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=198744},
        abstract = {Securing a technical role in the modern software industry requires navigating a gauntlet of high-stakes evaluations. While algorithmic problem-solving remains central, the ability to verbally articulate complex system logic under pressure is equally critical. Unfortunately, quality preparation ecosystems are largely gated behind expensive paywalls involving human mock-interviewers, while free alternatives fail to simulate the psychological friction of a genuine interview room. We introduce InterviewAI, a highly accessible, automated SaaS platform engi-neered to democratize elite interview preparation. By coupling the semantic reasoning capabilities of Google Gemini with native browser hardware APIs (WebRTC and Web Speech), the system facilitates a rigorous, time-bound verbal assessment. Candidates must navigate a heavily curated domain-specific question bank while subjected to strict tab-switch proctoring. The underlying cognitive layer bypasses legacy keyword-matching algorithms, opting instead to evaluate the transcribed responses dynamically across technical accuracy and communication clarity. Empirical trials demonstrate that InterviewAI achieves a tight grading correlation with senior human engineers while delivering actionable, multi-rubric feedback in under four seconds.},
        keywords = {Mock Interview, Large Language Models, Generative AI, WebRTC, Continuous Proctoring, Next.js, Algorithmic Assessment, Natural Language Processing.},
        month = {April},
        }