NICT Kyoto Submission for the WMT’20 Quality Estimation Task: Intermediate Training for Domain and Task Adaptation

AbstractThis paper describes the NICT Kyoto submission for the WMT’20 Quality Estimation (QE) shared task. We participated in Task 2: Word and Sentence-level Post-editing Effort, which involved Wikipedia data and two translation directions, namely English-to-German and English-to-Chinese. Our approach is based on multi-task fine-tuned cross-lingual language models (XLM), initially pre-trained and further domain-adapted through intermediate training using the translation language model (TLM) approach complemented with a novel self-supervised learning task which aim is to model errors inherent to machine translation outputs. Results obtained on both word and sentence-level QE show that the proposed intermediate training method is complementary to language model domain adaptation and outperforms the fine-tuning only approach.