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Linguistic evaluation for the 2021 state-of-the-art Machine Translation systems for German to English and English to German

Vivien Macketanz; Eleftherios Avramidis; Shushen Manakhimova; Sebastian Möller
In: Proceedings of the Sixth Conference on Machine Translation. Conference on Machine Translation (WMT-2021), Online, Pages 1059-1073, Association for Computational Linguistics, 11/2021.


We are using a semi-automated test suite in order to provide a fine-grained linguistic evaluation for state-of-the-art machine translation systems. The evaluation includes 18 German to English and 18 English to German systems, submitted to the Translation Shared Task of the 2021 Conference on Machine Translation. Our submission adds up to the submissions of the previous years by creating and applying a wide-range test suite for English to German as a new language pair. The fine-grained evaluation allows spotting significant differences between systems that cannot be distinguished by the direct assessment of the human evaluation campaign. We find that most of the systems achieve good accuracies in the majority of linguistic phenomena but there are few phenomena with lower accuracy, such as the idioms, the modal pluperfect and the German resultative predicates. Two systems have significantly better test suite accuracy in macro-average in every language direction, Online-W and Facebook-AI for German to English and VolcTrans and Online-W for English to German. The systems show a steady improvement as compared to previous years.


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