International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Volume 8 Issue 1
January-February 2026

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Real-time interview analysis using Deep-Learning

Author(s) Prof. Rucha Abhishek Agrawal, Mr. Arvind Hariharan, Mr. Omkar Dipak Atkari, Mr. Sujal Kiritkumar Ghogare, Mr. Suyash Rajesh Ghorpade
Country India
Abstract Traditional interviews often lack objectivity and fail to provide candidates with constructive, real-time feedback, resulting in inconsistent evaluation outcomes. Moreover, human bias and subjectivity in assessment can significantly affect the fairness of recruitment and skill evaluation processes .To address these limitations, this study proposes an intelligent, adaptive system capable of analyzing both verbal and non-verbal cues during interviews using deep learning methodologies. The proposed system employs computer vision techniques for facial emotion recognition and natural language processing (NLP) for dynamic, context-aware question generation ..By capturing real-time video input, detecting emotional expressions through facial landmarks, and assessing responses using semantic and sentiment analysis, the system aims to emulate human interviewer behavior while providing objective feedback and performance analytics .This approach enhances candidate evaluation accuracy and transparency, enabling scalable applications in HR automation, mock interview simulations, and behavioral assessment platforms.
Keywords Deep Learning, Natural Language Processing, Sentiment Analysis, Speech Recognition, Real-Time Evaluation, Automated Interview System, Candidate Profiling, Emotion Detection.
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-02-04
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.67359
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