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This paper presents the team TransQuest's participation in Sentence-LevelDirect Assessment shared task in WMT 2020. We introduce a simple QE frameworkbased on cross-lingual transformers, and we use it to implement and evaluatetwo different neural architectures. The proposed methods achievestate-of-the-art results surpassing the results obtained by OpenKiwi, thebaseline used in the shared task. We further fine tune the QE framework byperforming ensemble and data augmentation. Our approach is the winning solutionin all of the language pairs according to the WMT 2020 official results.

TransQuest at WMT2020: Sentence-Level Direct Assessment