Virtual Mock Interview Assistant

Abstract

In this paper, we are exploring state-of-the- art models in multimodal emotion recognition. We choose to investigate video inputs and construct an ensemble model that collects data from all of these sources and presents it in a clear and understandable manner. The project's goal is to extract useful information from a variety of sources, including video inputs. The goal is to compile this data and present it in such a way that its meaning is apparent and understandable to others. The goal of this project is to help the user discover their strengths and flaws in order to prepare for an interview. The purpose is to help the user succeed in an interview by educating them about their personality and coaching them on the precise personality features and adjustments they need to succeed (of organisation of their choice.). The paper describes a method for creating artificial conversational agents and bots that employ actual human video. This approach differs from others in that it starts with real human examples and builds artificial behaviours from there, rather than artificial agents building the real interaction. In terms of behaviour and emotion, Video Bot might be considered a substitute for human beings; it is conceivable to create a video that behaves like a individual human for all the practical reasons. This method also reveals some of the difficulties encountered during the Video Bot's preparation for the interview.