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LeBLEU: N-gram-based Translation Evaluation Score for Morphologically Complex Languages

机译:LeBLEU:基于N-gram的形态复杂语言的翻译评估得分

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摘要

This paper describes the LeBLEU evaluation score for machine translation, submitted to WMT15 Metrics Shared Task. LeBLEU extends the popular BLEU score to consider fuzzy matches between word n-grams. While there are several variants of BLEU that allow to non-exact matches between words either by character-based distance measures or morphological preprocessing, none of them use fuzzy comparison between longer chunks of text. The results on WMT data sets show that fuzzy n-gram matching improves correlations to human evaluation especially for highly compounding languages.
机译:本文介绍了提交给WMT15指标共享任务的机器翻译的LeBLEU评估得分。 LeBLEU扩展了流行的BLEU分数,以考虑单词n-gram之间的模糊匹配。尽管BLEU有多种变体,可以通过基于字符的距离度量或形态学预处理来实现单词之间的不完全匹配,但它们都没有在较长的文本块之间使用模糊比较。 WMT数据集上的结果表明,模糊n-gram匹配可改善与人类评估的相关性,尤其是对于高度复合的语言。

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