• 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