Automated Event Recognition for Football Commentary Generation

Automated Event Recognition for Football Commentary Generation

Maliang Zheng (University of York, UK) and Daniel Kudenko (University of York, UK)
DOI: 10.4018/978-1-4666-0029-4.ch019
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Abstract

The enjoyment of many games can be enhanced by in-game commentaries. In this paper, the authors focus on the automatic generation of commentaries for football games, using Championship Manager as a case study. The basis of this approach is a real-time mapping of game states to commentary concepts, such as “dangerous situation for team A”. While in some cases it is feasible to provide such a mapping by hand-coding, in some cases it is not straight-forward because the meaning of the concepts cannot be easily formalized. In these cases, the authors propose to use inductive learning techniques that learn such a mapping from annotated game traces.
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Championship Manager

This section briefly summarizes our experimental domain, the Championship Manager game (CM1) 2008, presenting both the trace data specification and the game log simulation aspects.

Within CM, football matches are simulated. Similar to a real football match, there are four officials operating on the field and two teams competing to get the ball into the opposing goal. Each team comprises a maximum of eleven players; but the substitution is unlimited during the play.

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