AI Based Mock Interview Evaluator
Mr. Purushottam S. Chavan
Department of Computer Technology
K. K. WAGH POLYTECHNIC, Nashik pschavan@kkwagh.edu.in
Mr. Jayesh T. Derle
Department of Mechanical Engineering
K. K. WAGH POLYTECHNIC, Nashik jtderle@kkwagh.edu.in
Sejal Mahadu Sonawane
Department of Computer Technology
K. K. WAGH POLYTECHNIC, Nashik sejalsonawane415@gmail.com
Prashik Laxman Pawar
Department of Computer Technology
K. K. WAGH POLYTECHNIC, Nashik pawarprashik78@gmail.com
Kalyani Dinkar Thakur
Department of Computer Technology
K. K. WAGH POLYTECHNIC, Nashik tkalyani014@gmail.com
Renuka Sukdev Sathe
Department of Computer Technology
K. K. WAGH POLYTECHNIC, Nashik renukasathe30@gmail.com
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Abstract –
The integration of Artificial Intelligence (AI) in the realm of recruitment has led to the development of innovative tools aimed at optimizing the interview process. This paper presents an AI-based mock interview evaluator, designed to assess candidate responses effectively in simulated interview scenarios. Leveraging machine learning algorithms and natural language processing techniques, the system offers real-time feedback to candidates, enhancing the interview experience and providing valuable insights for self-improvement.
The mock interview evaluator provides candidates with the option to choose between video and audio interviews, catering to individual preferences and facilitating a seamless user experience. During the interview, the system analyzes facial expressions in real-time, capturing emotional cues that contribute to a comprehensive evaluation of candidate performance.
Upon completion of the interview, candidates receive immediate feedback, accompanied by visual representations of their performance compared to previous interviews. These visualizations aid in identifying areas for improvement and tracking progress over time.
Key Words: Artificial Intelligence, Mock Evaluator, CNN, Pydub