Video based Interview Assessment System

Video based Interview Assessment System

Abhijit Darade, Ayush Kamble, Anushka Satav, Prof. Rasika Ransing

Dept. of Information Technology

Vidyalankar Institute of Technology

Mumbai, India

Abstract — The evolving job interview landscape, driven by technological advancements, has given rise to a pressing challenge in effectively assessing candidates in the era of virtual interviews and remote hiring. To address this, a video-based IAS is introduced, offering a comprehensive solution by integrating innovative features. IAS leverages cutting-edge technologies to analyze audio tones, enhancing the evaluation of candidates' communication skills by assessing confidence and clarity. The system incorporates facial sentiment analysis to gauge emotional expressions, providing insights into interviewee engagement and enthusiasm. IAS streamlines the hiring process by automating candidate comparisons, thereby saving recruiters valuable time. In essence, IAS represents a holistic and efficient approach to modernizing the interviewing and hiring process, revolutionizing candidate evaluation and selection in the digital age.

Keywords—Interview Assessment System (IAS), Convolutional Neural Networks (CNN),  Deep Learning, Machine Learning.