AI Powered Virtual Job Interview Simulation System

References

[1] Si, J., Song, J., Woo, M., Kim, D., Lee, Y., & Kim, S. (2023). Generative AI Models for Virtual Interviewers: Applicability and Performance Comparison. IEEE International Conference on Innovation, Communication and Engineering.

[2] Swaraj, G., Kumar, B. N., Himavanth, B., Reddy, S. P., Anoop, S., & Jayasree, K. R. (2023). An Interactive Interview Bot for Human Resource Interviewing. 14th International Conference on Computing Communication and Networking Technologies (ICCCNT).

[3] Dissanayake, D. Y., Amalya, V., Dissanayaka, R., Lakshan, L., Samarasinghe, P., Nadeeshani, M., & Samarasinghe, P. (2021). AI-based Behavioral Analyses for Interviews/Viva. 16th International Conference on Industrial and Information Systems (ICIIS).

[4] Jin, X., Bian, Y., Geng, W., Chen, Y., Chu, K., Hu, H., Liu, J., Shi, Y., & Yang, C. (2019). Developing an Agent-based Virtual Interview Training System for College Students with High Shyness Level. IEEE Conference on Virtual Reality and 3D User Interfaces.

[5] Suen, H. Y., Hung, K. E., & Lin, C. L. (2019). TensorFlow-based Automatic Personality Recognition Used in Asynchronous Video Interviews. IEEE Access, 7, 61018–61023.

[6] Zhang, H., Jolfaei, A., & Alazab, M. (2019). A Face Emotion Recognition Method Using Convolutional Neural Network and Image Edge Computing. IEEE Access, 7, 159081–159089.

[7] Suen, H. Y., Hung, K. E., & Lin, C. L. (2019). Chatbot Use Intention Analysis: A Personality Perspective. IEEE Access, 7, 153932–153940. 58

[8] Suen, H. Y., Hung, K. E., & Lin, C. L. (2019). A Large-Scale Study on the Personality Traits and Interview Performance of Job Candidates. IEEE Access, 7, 116645–116656.

[9] Suen, H. Y., Hung, K. E., & Lin, C. L. (2019). An Empirical Study on the Effect of Personality Traits on Job Interview Performance. IEEE Access, 7, 116657–116668.

[10] Suen, H. Y., Hung, K. E., & Lin, C. L. (2019). A Study on the Effect of Personality Traits on Job Interview Performance Using Machine Learning. IEEE Access, 7, 116669–116680.

@article{1712321,
      author = {E. Elancheziyan M. E., (Ph.D), Vishnu A, Sanjay K C, Thayanithimaran V},
      title = {AI Powered Virtual Job Interview Simulation System},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {1680-1690},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712321.pdf},
      abstract = {This project presents an advanced AI-powered recruitment and evaluation platform designed to modernize traditional hiring and certification processes. The system integrates automated resume analysis, intelligent question generation, and real-time facial verification to ensure a secure and efficient candidate assessment experience. Candidates begin by uploading their resumes, which are processed using GPT-4 to extract key skills and generate personalized interview questions. The platform conducts dynamic, adaptive questioning based on user responses, creating a more relevant and engaging evaluation flow. A built-in facial recognition module enhances security by continuously verifying candidate identity and detecting potential impersonation attempts. Additionally, the system provides instant feedback, enabling candidates to identify strengths and areas for improvement. With its automated workflow, high accuracy, and enhanced fraud prevention, this platform significantly reduces recruiter workload and improves the overall hiring experience. The solution is scalable, user-friendly, and suitable for recruitment, skill certification, and virtual job interview environments.},
      keywords = {AI Recruitment, GPT-4, Resume Analysis, Virtual Interview, Facial Recognition, Dynamic Questioning, Candidate Evaluation, Automated Hiring System.},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712321}
  }