Abstract
We present a method for evaluating the quality of Machine Translation (MT) output, using labelled dependencies produced by a Lexical-Functional Grammar (LFG) parser. Our dependency-based method, in contrast to most popular string-based evaluation metrics, does not unfairly penalize perfectly valid syntactic variations in the translation, and the addition of WordNet provides a way to accommodate lexical variation. In comparison with other metrics on 16,800 sentences of Chinese-English newswire text, our method reaches high correlation with human scores.
Cite
CITATION STYLE
Owczarzak, K., van Genabith, J., & Way, A. (2007). Labelled dependencies in machine translation evaluation. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 104–111). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1626355.1626369
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