Evaluating an NLG System using Post-Editing

被引：0
|
作者：
Sripada, Somayajulu G. [1 ]
Reiter, Ehud [1 ]
Hawizy, Lezan [1 ]
机构：
[1] Univ Aberdeen, Dept Comp Sci, Aberdeen AB24 3UE, Scotland
来源：
19TH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-05) | 2005年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Computer-generated texts, whether from Natural Language Generation (NLG) or Machine Translation (MT) systems, are often post-edited by humans before being released to users. The frequency and type of post-edits is a measure of how well the system works, and can be used for evaluation. We describe how we have used post-edit data to evaluate SUMTIME-MOUSAM, an NLG system that produces weather forecasts.
引用
收藏
页码：1700 / 1701
页数：2
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