TransQuest at WMT2020: Sentence-Level Direct Assessment

Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov

    Research output: Chapter in Book/Published conference outputConference publication


    This paper presents the team TransQuest’s participation in Sentence-Level Direct Assessment shared task in WMT 2020. We introduce a simple QE framework based on cross-lingual transformers, and we use it to implement and evaluate two different neural architectures. The proposed methods achieve state-of-the-art results surpassing the results obtained by OpenKiwi, the baseline used in the shared task. We further fine tune the QE framework by performing ensemble and data augmentation. Our approach is the winning solution in all of the language pairs according to the WMT 2020 official results.
    Original languageEnglish
    Title of host publicationFifth Conference on Machine Translation
    PublisherAssociation for Computational Linguistics (ACL)
    Publication statusPublished - Nov 2020
    Event5th Conference on Machine Translation -
    Duration: 19 Nov 202020 Nov 2020


    Conference5th Conference on Machine Translation
    Abbreviated titleWMT 20

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