AI-based Confidence Level Estimation System

Confidence is an important quality that everyone should strive to possess. It is belief in oneself and one’s abilities. Estimation of human confidence using artificial intelligence (AI) is a growing area of research that seeks to develop algorithm and model. Using machine learning algorithms, this system can accurately estimate a person’s level of confidence. The system considers various factors such as face-direction, facial expression, eye movement and speech patterns to determine the confidence level of the speaker. This research is motivated by the potential applications of this technology in field of recruitment, education, and neuroscience. Proposed system will be trained on large datasets of individuals with varying levels of confidence to improve its accuracy and performance. The output will be categorical value that represents the confidence level of the individual, which can be used to evaluate their performance in various settings, such as job interviews, public speaking& many more. Our system will also be able to provide explanations for its predictions, enabling users to understand how the system arrived at its confidence level estimation. This abstract provides an overview of the current state of the art in this field and discusses some of the challenges and opportunities that lie ahead. Overall, our proposed AI-based Confidence level Estimator has a potential in the field of decision making, and we believe that it has significant role for behavioral analysis in the domain of AI.