We present a novel commentator system that learns language from sportscasts of simulated soccer games. The system learns to parse and generate commentaries without any engineered knowledge about the English language. Training is done using only ambiguous supervision in the form of textual human commentaries and simulation states of the soccer games. The system simultaneously tries to establish correspondences between the commentaries and the simulation states as well as build a translation model. We also present a novel algorithm, Iterative Generation Strategy Learning (IGSL), for deciding which events to comment on. Human evaluations of the generated commentaries indicate they are of reasonable quality compared to human commentaries.

PDF

In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.

@inproceedings{chen:icml08, title={Learning to Sportscast: A Test of Grounded Language Acquisition}, author={David L. Chen and Raymond J. Mooney}, booktitle={Proceedings of the 25th International Conference on Machine Learning (ICML)}, month={July}, address={Helsinki, Finland}, url="http://www.cs.utexas.edu/users/ai-lab?chen:icml08", year={2008} }

Slides (PPT) Video