LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

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Title Determining the Tolerance of Text-handling Tasks for MT Output

Authors White John (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, white_john@prc.com)
Doyon Jennifer (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, doyon_jennifer@prc.com)
Talbott Susan (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, talbott_susan@prc.com)

Keywords Evaluation, Exercise(s), Machine Translation, Text-Handling tasks, Topic(s) of Interest, Users

Session Session EO1 - Evaluation of Machine Translation

Abstract With the explosion of the internet and access to increased amounts of information provided by international media, the need to process this abundance of information in an efficient and effective manner has become critical. The importance of machine translation (MT) in the stream of information processing has become apparent. With this new demand on the user community comes the need to assess an MT system before adding such a system to the user’s current suite of text-handling applications. The MT Functional Proficiency Scale project has developed a method for ranking the tolerance of a variety of information processing tasks to possibly poor MT output. This ranking allows for the prediction of an MT system’s usefulness for particular text-handling tasks.

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Title	Determining the Tolerance of Text-handling Tasks for MT Output
Authors	White John (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, white_john@prc.com) Doyon Jennifer (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, doyon_jennifer@prc.com) Talbott Susan (Litton PRC, 1500 PRC Drive, McLean, Virginia, USA, talbott_susan@prc.com)
Keywords	Evaluation, Exercise(s), Machine Translation, Text-Handling tasks, Topic(s) of Interest, Users
Session	Session EO1 - Evaluation of Machine Translation
Abstract	With the explosion of the internet and access to increased amounts of information provided by international media, the need to process this abundance of information in an efficient and effective manner has become critical. The importance of machine translation (MT) in the stream of information processing has become apparent. With this new demand on the user community comes the need to assess an MT system before adding such a system to the user’s current suite of text-handling applications. The MT Functional Proficiency Scale project has developed a method for ranking the tolerance of a variety of information processing tasks to possibly poor MT output. This ranking allows for the prediction of an MT system’s usefulness for particular text-handling tasks.