Paper Title
“AI ENHANCED SPORTS HIGHLIGHT GENERATION FOR DIGITAL PLATFORM”

Abstract
In the modern era of digital media, the demand for real-time and engaging sports content has grown exponentially. This project proposes an AI enhanced sports highlight generation for digital platform designed to automate the process of extracting key moments from sportsvideos using deep learning, computer vision, and natural language processing techniques. The system employs Convolutional Neural Networks (CNNs) and action recognitionmodels like Long Short-Term Memory (LSTM) networks and Transformers to detect significant events such as goals, wickets, or other turning points in a match. Additionally, motion tracking and scene change detection using OpenCV help in identifying dynamic moments with high engagement potential. To enhance the accessibility and storytelling of the highlights, Natural Language Processing (NLP) isusedto extract matchcommentaryandgeneratereal-time subtitles.Thecollecteddata is then compiled into short, appealing video summaries optimized for social media platforms such as Instagram, YouTube Shorts, and TikTok. This automated solution significantly reduces manual labor, speeds up content creation, and provides broadcasters, content creators, and fans with a powerful tool for instantaneous and impactful sports media generation.