A SURVEY OF NATURAL LANGUAGE AND COMPUTER VISION METHODS FOR PRESENTATION ENHANCEMENT

Abstract

Natural Language Processing (NLP) and Computer Vision (CV) are revolutionizing the presentation user experience for both designers and presenters. This systematic review examines how NLP and CV are used together to increase the quality of presentation, their interactivity, and engagement with the audience. NLP enables features such as on-demand speech recognition, translation, content summarization, and communication with chatbots, allowing presenters to interact effectively with diverse audiences. At the same time, “CV capabilities” support gesture understanding, tracking of facial expression, eye-tracking and augmented reality display, allowing the person presenting their material to assess the interest of the audience and adjust presentation accordingly. The combination of the technologies involved facilitates the creation of smart presentation aid and reactive systems that dynamically fit and customize the presentation process according to the live response. This review classifies and critically analyzes the recent works' contributions in the two fields, which find application in education, business and conjecture situations in the field of public speaking. It also highlights the increasing need to design multimodal AI systems to combine linguistic and visual types of communication and interaction. The study concludes by delineating critical methodologies, tools and system architectures behind these developments, which point to the revolutionary impact NLP-CV unification may have in the future of intelligent, user-focused presentation systems.