Automated paraphrase lattice creation for hyter machine translation evaluation

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Abstract

We propose a variant of a well-known machine translation (MT) evaluation metric, HyTER (Dreyer and Marcu, 2012), which exploits reference translations enriched with meaning equivalent expressions. The original HyTER metric relied on hand-crafted paraphrase networks which restricted its applicability to new data. We test, for the first time, HyTER with automatically built paraphrase lattices. We show that although the metric obtains good results on small and carefully curated data with both manually and automatically selected substitutes, it achieves medium performance on much larger and noisier datasets, demonstrating the limits of the metric for tuning and evaluation of current MT systems.

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APA

Apidianaki, M., Wisniewski, G., Cocos, A., & Callison-Burch, C. (2018). Automated paraphrase lattice creation for hyter machine translation evaluation. In NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference (Vol. 2, pp. 480–485). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/n18-2077

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