DocumentCode :
62252
Title :
Automated Story Selection for Color Commentary in Sports
Author :
Lee, Gene ; Bulitko, Vadim ; Ludvig, Elliot A.
Author_Institution :
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
Volume :
6
Issue :
2
fYear :
2014
fDate :
Jun-14
Firstpage :
144
Lastpage :
155
Abstract :
Automated sports commentary is a form of automated narrative. Sports commentary exists to keep the viewer informed and entertained. One way to entertain the viewer is by telling brief stories relevant to the game in progress. We present a system called the sports commentary recommendation system (SCoReS) that can automatically suggest stories for commentators to tell during games. Through several user studies, we compared commentary using SCoReS to three other types of commentary and show that SCoReS adds significantly to the broadcast across several enjoyment metrics. We also collected interview data from professional sports commentators who positively evaluated a demonstration of the system. We conclude that SCoReS can be a useful broadcast tool, effective at selecting stories that add to the enjoyment and watchability of sports. SCoReS is a step toward automating sports commentary and, thus, automating narrative.
Keywords :
humanities; recommender systems; sport; SCoReS; automated narrative; automated sport commentary; automated story selection; brief story telling; color commentary; professional sport commentators; sport commentary recommendation system; sport enjoyment; sport watchability; Artificial intelligence; Color; Games; Image color analysis; Sports equipment; Training data; Vectors; Artificial intelligence; automated narrative; information retrieval;
fLanguage :
English
Journal_Title :
Computational Intelligence and AI in Games, IEEE Transactions on
Publisher :
ieee
ISSN :
1943-068X
Type :
jour
DOI :
10.1109/TCIAIG.2013.2275199
Filename :
6571237
Link To Document :
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