AUTOMATED VEDIO GENERATOR

Abstract

With the rapid advancement of artificial intelligence, automated content generation has become a significant area of research. This project proposes an Automated Video Generator system that converts textual input into engaging video content using Natural Language Processing (NLP) and multimedia processing techniques. The system takes user input in the form of text or keywords and generates a video by combining relevant images, audio narration, and transitions. The proposed system utilizes NLP techniques to process and structure input text, text-to-speech (TTS) for generating voice narration, and image/video synthesis for visual representation. Machine learning models are used to select relevant visuals based on context. The system automates the entire video creation process, reducing manual effort and time. Experimental results show that the system can generate meaningful and coherent videos suitable for applications such as education, marketing, and storytelling. The proposed solution provides a scalable and efficient approach to automated multimedia content generation.