Automated cricket commentary generation using deep learning
Debabrata Ghosh, Chiranjib Ghosh, Prabhat Dey, Avsaf Ali, Manvi Bohra, Indrajeet Kumar, Noor Mohd · AIP conference proceedings · 2024
This work presents an automated and novel system for cricket commentary generation by the introduction of event driven approach and image captioning features.The presented system uses artificial intelligence and machine learning (ML) based methods to investigate real-time match data and generate real-time commentary by Image Captioning technique.For this purpose, deep neural network-based models and digital image processing techniques are used to detect the significant moments in the real-time match and generate commentary based on these real-time match events.The proposed method has been assessed using a dataset of 2 hours live cricket matches of India and England.After processing the match video, it has been observed that the developed model is successfully able to generate high-quality real-time commentary with a significant amount of accuracy.By commissioning leading-edge deep neural network-based model, the developed model determines the fitness to generate subtitles that are not only precise but also contextually appropriate, and efficiently apprehending the essence of the input frames.