TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task

Xin Ge, Ke Wang, Jiayi Wang, Nini Xiao, Xiangyu Duan, Yu Zhao, Yuqi Zhang


Abstract
This paper describes the joint submission of Alibaba and Soochow University to the WMT 2022 Shared Task on Translation Suggestion (TS). We participate in the English to/from German and English to/from Chinese tasks. Basically, we utilize the model paradigm fine-tuning on the downstream tasks based on large-scale pre-trained models, which has recently achieved great success. We choose FAIR’s WMT19 English to/from German news translation system and MBART50 for English to/from Chinese as our pre-trained models. Considering the task’s condition of limited use of training data, we follow the data augmentation strategies provided by Yang to boost our TS model performance. And we further involve the dual conditional cross-entropy model and GPT-2 language model to filter augmented data. The leader board finally shows that our submissions are ranked first in three of four language directions in the Naive TS task of the WMT22 Translation Suggestion task.
Anthology ID:
2022.wmt-1.123
Volume:
Proceedings of the Seventh Conference on Machine Translation (WMT)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Venue:
WMT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1198–1204
Language:
URL:
https://aclanthology.org/2022.wmt-1.123
DOI:
Bibkey:
Cite (ACL):
Xin Ge, Ke Wang, Jiayi Wang, Nini Xiao, Xiangyu Duan, Yu Zhao, and Yuqi Zhang. 2022. TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1198–1204, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task (Ge et al., WMT 2022)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2022.wmt-1.123.pdf