Yujia Liu


2021

pdf bib
HW-TSC’s Participation at WMT 2021 Quality Estimation Shared Task
Yimeng Chen | Chang Su | Yingtao Zhang | Yuxia Wang | Xiang Geng | Hao Yang | Shimin Tao | Guo Jiaxin | Wang Minghan | Min Zhang | Yujia Liu | Shujian Huang
Proceedings of the Sixth Conference on Machine Translation

This paper presents our work in WMT 2021 Quality Estimation (QE) Shared Task. We participated in all of the three sub-tasks, including Sentence-Level Direct Assessment (DA) task, Word and Sentence-Level Post-editing Effort task and Critical Error Detection task, in all language pairs. Our systems employ the framework of Predictor-Estimator, concretely with a pre-trained XLM-Roberta as Predictor and task-specific classifier or regressor as Estimator. For all tasks, we improve our systems by incorporating post-edit sentence or additional high-quality translation sentence in the way of multitask learning or encoding it with predictors directly. Moreover, in zero-shot setting, our data augmentation strategy based on Monte-Carlo Dropout brings up significant improvement on DA sub-task. Notably, our submissions achieve remarkable results over all tasks.