论文标题
WMT2020的TransQuest：句子级直接评估
TransQuest at WMT2020: Sentence-Level Direct Assessment
论文作者
论文摘要
本文介绍了TransQuest在WMT 2020中参与句子级直接评估共享任务的参与。我们介绍了一个基于跨语言变压器的简单量化QE框架，我们使用它来实现和评估两种不同的神经体系结构。所提出的方法达到了最先进的结果，该结果超过了共享任务中使用的基线Openkiwi获得的结果。我们通过执行集合和数据增强来进一步调整量化量化宽松框架。根据WMT 2020官方结果，我们的方法是所有语言对的获胜解决方案。
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.
