Intelligent and Personalized Factoid Question and Answer System

The current era of information technology revolutions needs rapid progress of digital transformation. Question-answer system is one such remarkable intelligent application based on artificial intelligence that analyzes and processes human interactions, either spoken or written. Question-answer systems have been proven a very effective way of providing 24-hour interaction service that is interacting with end-users thru digital devices as if the user is interacting with a real human being. This application has found its major utilization in answering customers' queries in almost every business ranging from government to non-profit sectors and from very small to large organizations. Many chatbot frameworks are available that are either code-based or interface-based. However, they lack the usefulness of personal touch in communication. Thus, to have better customer interactions in the form of question-answers and improved personalization, this paper proposes a face recognition-based chatbot system utilizing the natural language processing toolkit with python. The proposed method implements a tailored user-centric approach to a simplistic version of the Question-answer system by implementing machine learning models for Face Recognition which rely on Local Binary patterns and HAAR Classifications. The method trains and maintains a unique dataset mapped to each user associated with the user's biometric identification. This chatbot focuses on speech synthesis and language processing to retrieve queries of each user based on their unique dataset.