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A computational approach to detecting collocation errors in the writing of non-native speakers of English

机译:检测非英语母语者写作中搭配错误的一种计算方法

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This paper describes the first prototype of an automated tool for detecting collocation errors in texts written by non-native speakers of English. Candidate strings are extracted by pattern matching over POS-tagged text. Since learner texts often contain spelling and morphological errors, the tool attempts to automatically correct them in order to reduce noise. For a measure of collocation strength, we use the rank-ratio statistic calculated over one billion words of native-speaker texts. Two human annotators evaluated the system's performance. We report the overall results, as well as detailed error analyses, and discuss possible improvements for the future.
机译:本文介绍了一种自动工具的原型,该工具可用于检测由非英语母语人士撰写的文本中的搭配错误。通过在POS标记文本上进行模式匹配来提取候选字符串。由于学习者文本通常包含拼写和形态错误,因此该工具会尝试自动更正它们以减少噪音。为了衡量搭配强度,我们使用了超过10亿个母语文本的排名比率统计数据。两名人工注释者评估了系统的性能。我们报告总体结果以及详细的错误分析,并讨论未来可能的改进。

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