http://hdl.handle.net/123456789/9931 HR Interview Rating Prediction System 2026-04-16T18:13:50Z http://hdl.handle.net/123456789/9932 HR Interview Rating Prediction System Alex, Nivya The most important criteria for selecting a candidate is interview. Here I proposed a predictive system that helps to predict the hire ability and rate different traits of the interviews. The paper which I referred for the developed system is camera. The system can also be used for a fully automated screening of candidates in online interviews. It helps for initial shortlisting of suitable candidates for further domain specific evaluation. To build such an automated predictive system, the first step is data gathering. Here the system analyses the facial expression, hand gestures and body postures with vocal content. Then extracting the features like verbal, visual and audio cues. The next step is to test different classification algorithm to create a predictive model for the system that would classify and rate different traits of individuals. The system produce a verity of result from single personality trait to the overall hireability recommendation of candidate. The CNN architecture is used for feature extraction in the system. The SVR algorithm is used as the predictive framework for create the model. Also statistical results are produced by the system. The proposed system produces the user interface results which helps the interviewer to observe in real time. Finally, at the end of interview the system make predictions and produces a series of ratings to interviewer based on various parameters like visible, calmness, eye contact, friendliness etc. The system is an automated expertise system which predicts the overall and recommended ratings of the interviewee. 2022-06-11T00:00:00Z