AI-Driven Web Application for Real-Time Student Interview Training

  • Unique Paper ID: 180648
  • Volume: 12
  • Issue: 1
  • PageNo: 1773-1777
  • Abstract:
  • This paper explores the development and implementation of an AI-powered mock interview system tailored for candidates aiming to improve their technical interview skills. Our system provides a realistic and interactive experience by conducting video interviews, generating dynamic questions based on user responses, and offering spoken feedback. Additionally, it includes roadmaps for various technology stacks and allows users to view testimonials to stay motivated. By leveraging React, Node.js, and AWS, the platform ensures a seamless, scalable experience that effectively supports career development. Preliminary testing indicates that this system can significantly improve interview readiness and self- confidence.

Copyright & License

Copyright © 2025 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.

BibTeX

@article{180648,
        author = {Mann Monpara and Shruti Amrutkar and Kunal Puri and Gajanan Rathod and Prof. N. H. Deshpande},
        title = {AI-Driven Web Application for Real-Time Student Interview Training},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1773-1777},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180648},
        abstract = {This paper explores the development and 
implementation of an AI-powered mock interview system 
tailored for candidates aiming to improve their technical 
interview skills. Our system provides a realistic and 
interactive experience by conducting video interviews, 
generating dynamic questions based on user responses, 
and offering spoken feedback. Additionally, it includes 
roadmaps for various technology stacks and allows users 
to view testimonials to stay motivated. By leveraging 
React, Node.js, and AWS, the platform ensures a 
seamless, scalable experience that effectively supports 
career development. Preliminary testing indicates that 
this system can significantly improve interview readiness 
and self- confidence.},
        keywords = {AI-Based Mock Interview, Real-Time  Feedback, Technical Skill Assessment, Machine  Learning, Natural Language Processing, Roadmap for  Technology Stacks, Video Interview Analysis, Spoken  Feedback Mechanism, Cloud Infrastructure (AWS),  User Engagement in Interview Training},
        month = {June},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 12
  • Issue: 1
  • PageNo: 1773-1777

AI-Driven Web Application for Real-Time Student Interview Training

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