Natural Language Processing-Driven Text-to-Animation Framework

Animations are highly effective tools for illustrating concepts, conveying messages, and engaging audiences, particularly in educational settings for children. Despite their potential, creating engaging and visually appealing animations presents significant challenges. This process requires expertise in various software tools, substantial computational resources for rendering, and careful selection of music, sound effects, and backgrounds, all of which demand considerable time and effort. To address these challenges, this research study proposes a comprehensive framework that leverages multiple interconnected subsystems to streamline the animation development process from input text driven by natural language processing. The framework generates relevant 2D textures, sound effects, narration, character selection, and animations by utilizing advanced natural language processing models. It further incorporates camera motions and lighting, seamlessly integrating these elements into dynamic animations. This approach aims to simplify the animation creation process, making it more accessible and efficient.