Deep Learning-LSTM based Football Commentary Generation and PCFG based Event Generation Dependent on User Input

Live commentary is a pivotal element of sports broadcasting, furnishing real- time updates and analysis to enhance the viewing experience. This exploration paper presents a new approach for live commentary generation using intermittent Neural Networks (RNN). This exploration opens up new avenues for automated live commentary systems, offering real- time updates that allure cult and elevate the sports broadcasting experience The suggested RNN model is trained on a huge dataset of actual match data leveraging the successional character of sporting events. The RNN-LSTM armature is intended to detect temporal correlations in sporting events and generate contextually consistent commentary