ORANGE 论文

2004引用 302
Natural Language Processing TechniquesTopic ModelingAdvanced Text Analysis Techniques

详细信息

发表日期
2004-01-01
发表年份
2004

关键词

Natural Language Processing TechniquesTopic ModelingAdvanced Text Analysis Techniques

摘要

Comparisons of automatic evaluation metrics for machine translation are usually conducted on corpus level using correlation statistics such as Pearson's product moment correlation coefficient or Spearman's rank order correlation coefficient between human scores and automatic scores. However, such comparisons rely on human judgments of translation qualities such as adequacy and fluency. Unfortunately, these judgments are often inconsistent and very expensive to acquire. In this paper, we introduce a new evaluation method, Orange, for evaluating automatic machine translation evaluation metrics automatically without extra human involvement other than using a set of reference translations. We also show the results of comparing several existing automatic metrics and three new automatic metrics using Orange.