Authors :K. R. Rajput, A. J. Kharade, A. P. Pawar, T. S. Wakhare,Prof. D. D. Ahir
DOI :10.46335/IJIES.2025.10.6.6
Abstract – The recruitment landscape has traditionally relied on manual assessments, often prone to biases and inefficiencies, making it challenging to evaluate candidates objectively. While modern recruitment has embraced asynchronous video interviews (AVI) for convenience, they lack the personal interaction of traditional methods, leading to gaps in assessing soft skills like personality traits. The Automatic Personality Recognition (APR) system bridges this gap by leveraging multimodal data—text, audio, and visuals—to evaluate candidates based on the Big Five personality traits. Using advanced deep learning techniques, the system processes recorded interviews to generate personality scores, enabling unbiased and scalable assessments. The APR system maintains candidate confidentiality and empowers recruiters with data-driven insights, enhancing decision-making while addressing the limitations of both traditional and modern recruitment processes.
