Player Tracking-Integrated Soccer Game Commentary Generation

Author(s)	Adarsh Vijayakumar, Amal Toms, Dr. Senthil Vadivu
Country	India
Abstract	Soccer commentary enhances the viewing experience by providing real-time analysis, context, and engagement. However, manually generating accurate and engaging commentary requires deep domain knowledge and quick decision-making. With advancements in computer vision and natural language processing (NLP), automated soccer commentary has gained attention. This research proposes a player tracking-integrated soccer game commentary generation framework, which integrates player tracking data, visual inputs, and textual information to generate real-time, context-aware commentary. By leveraging state-of-the-art tracking algorithms, multimodal data fusion, and advanced language models, the system aims to improve the accuracy, relevance, and engagement of automated commentary.
Keywords	Soccer Commentary, Player Tracking, Multimodal Fusion, Real-Time Commentary, Natural Language Generation
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 2, April-June 2025
Published On	2025-04-07
Cite This	Player Tracking-Integrated Soccer Game Commentary Generation - Adarsh Vijayakumar, Amal Toms, Dr. Senthil Vadivu - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3312
DOI	https://doi.org/10.71097/IJSAT.v16.i2.3312
Short DOI	https://doi.org/g9drdb

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