AI Based Mock Interview Evaluator
Ms.Nishigandha N.Shevkar, Amit Morade , Atharva Gadekar , Kamaldeep Waghdare, Chaitanya Kumavat
1. Ms.Nishigandha N.Shevkar, lecturer, Computer Engineering, Mahavir Polytechnic, Nashik
2. Mr. Amit Morade, Student, Information technology, Mahavir Polytechnic, Nashik
3. Mr. Atharva Gadekar , Student, Information technology, Mahavir Polytechnic, Nashik
4. Mr. Kamaldeep Waghdare, Student, Information technology, Mahavir Polytechnic, Nashik
5. Mr.Chaitanya Kumavat, Student , Information technology, Mahavir Polytechnic, Nashik
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Abstract – The integration of Artificial Intelligence (AI) in the recruitment process has led to the development of advanced tools aimed at enhancing interview assessment and candidate evaluation. This paper introduces an AI-driven mock interview evaluator designed to simulate real-world interview scenarios while providing comprehensive performance analysis. Utilizing machine learning algorithms and natural language processing (NLP) techniques, the system delivers real-time feedback to candidates, facilitating a more effective and insightful interview preparation experience.
The proposed system supports both video and audio-based interview modes, offering flexibility to accommodate individual preferences and ensuring a seamless user experience. During the interview, real-time facial expression analysis captures emotional cues, contributing to a holistic evaluation of candidate demeanor and engagement.
Upon completion, candidates receive instant feedback along with detailed performance visualizations, enabling comparative analysis across multiple interview sessions. These insights help candidates identify strengths, pinpoint areas for improvement, and track their progress over time, ultimately enhancing their readiness for real-world job interviews.
Key Words: Artificial Intelligence, Mock Evaluator, CNN, Pydub, Real-Time Camera, Neural Networks, Web Interface
