Document-level machine translation evaluation metrics enhanced with simplified lexical chain

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Abstract

Document-level Machine Translation (MT) has been drawing more and more attention due to its potential of resolving sentencelevel ambiguities and inconsistencies with the benefit of wide-range context. However, the lack of simple yet effective evaluation metrics largely impedes the development of such document-level MT systems. This paper proposes to improve traditional MT evaluation metrics by simplified lexical chain, modeling document-level phenomena from the perspectives of text cohesion. Experiments show the effectiveness of such method on evaluating document-level translation quality and its potential of integrating with traditional MT evaluation metrics to achieve higher correlation with human judgments.

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APA

Gong, Z., & Zhou, G. (2015). Document-level machine translation evaluation metrics enhanced with simplified lexical chain. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9362, pp. 396–403). Springer Verlag. https://doi.org/10.1007/978-3-319-25207-0_35

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