Text to Video Generation using Natural Language Processing and Machine Learning

Press Reports in general have been published in text based format for a vast period of time, although the old way of publishing reports may have been effective initially, it has led to a decrease in audience engagement and attention span. The study offers a novel solution to the problem of users’ attention spans getting shorter. Therefore, to retain user engagement and increase content quality, the proposed solution aims to create an automated system that uses press reports to generate dynamic video content. This technology improves user comprehension and engagement by utilizing audio-visual synthesis and natural language processing techniques. The models that are implemented have performed well during the Testing Phase by showing an average accuracy of 82 percentage from the NLP Large Language Models and 89 percentage from the Machine Learning Models and the outcomes reveal increased knowledge retention and user engagement. Finally, this study offers a novel method of communication by automatically converting press releases into videos for maximum viewer engagement.

I. Introduction

In an era of reducing attention spans and increasing content demands, the distribution of information is undergoing significant changes. The engagement rates of individuals with different forms of content has undergone rapid shift in trends which has been shown in Fig. 1. There’s demand to move press releases beyond their conventional text-based format because they are essential for official communication and are handled by organizations such as the Press Information Bureau and Media Channels. By addressing the shorter attention spans of the audience, this study aims to bridge the gap between traditional text-based reports and modern preferences, emphasizing visually appealing content. Our goal is to create a software that makes it simple to turn unattractively written press releases into interesting videos, so that communication tactics can be easily adjusted to fit consumer habits. The project acknowledges the widespread use of video and aims to streamline communication workflows through automation, utilizing Natural Language Processing (NLP) algorithms and Artificial Intelligence (AI) methodologies. By transforming press releases into visually appealing videos, the project aims to boost user engagement and addresses communication issues in the era of information technology.