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AI-POWERED SMART INTERVIEW ASSISTANT WITH REAL-TIME FEEDBACK AND SCORE PREDICTION
Dr. Umma Habiba, Jeni Pragashini J, Kayathri A, Yogalakshmi M
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Abstract: The rapid growth of Artificial Intelligence has created new opportunities to improve traditional interview preparation methods. Many students struggle with confidence, communication and evaluating the quality of their responses during job interviews. This paper proposes an AI-Powered Smart Interview Assistant that evaluates candidate responses and provides real-time feedback and score prediction using machine learning and natural language processing techniques. The proposed system allows candidates to answer interview questions through text or voice input. The system analyzes the responses using natural language processing methods to evaluate relevance, grammar, semantic similarity and communication quality. A machine learning model then predicts the interview score based on extracted linguistic and contextual features. The system was tested with different categories of answers including relevant, irrelevant, short and filler-based responses. Experimental results show that the proposed system achieves model accuracy between 88 percent and 92 percent while maintaining an average response time of less than three - five seconds. The speech recognition component achieves approximately 90 percent accuracy in converting spoken responses into text. The system provides immediate suggestions that help candidates improve communication skills, reduce interview anxiety and enhance overall interview readiness. The proposed framework demonstrates the potential of artificial intelligence in building intelligent training tools that support career preparation and professional development.
Keywords: Artificial Intelligence, Interview Assistant, Natural Language Processing, Machine Learning, Speech Recognition, Score Prediction
How to Cite:
[1] Dr. Umma Habiba, Jeni Pragashini J, Kayathri A, Yogalakshmi M, “AI-POWERED SMART INTERVIEW ASSISTANT WITH REAL-TIME FEEDBACK AND SCORE PREDICTION,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2026.155140
