TermMind: Alibaba’s WMT21 Machine Translation Using Terminologies Task Submission

Ke Wang, Shuqin Gu, Boxing Chen, Yu Zhao, Weihua Luo, Yuqi Zhang


Abstract
This paper describes our work in the WMT 2021 Machine Translation using Terminologies Shared Task. We participate in the shared translation terminologies task in English to Chinese language pair. To satisfy terminology constraints on translation, we use a terminology data augmentation strategy based on Transformer model. We used tags to mark and add the term translations into the matched sentences. We created synthetic terms using phrase tables extracted from bilingual corpus to increase the proportion of term translations in training data. Detailed pre-processing and filtering on data, in-domain finetuning and ensemble method are used in our system. Our submission obtains competitive results in the terminology-targeted evaluation.
Anthology ID:
2021.wmt-1.85
Volume:
Proceedings of the Sixth Conference on Machine Translation
Month:
November
Year:
2021
Address:
Online
Venues:
EMNLP | WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
851–856
Language:
URL:
https://aclanthology.org/2021.wmt-1.85
DOI:
Bibkey:
Cite (ACL):
Ke Wang, Shuqin Gu, Boxing Chen, Yu Zhao, Weihua Luo, and Yuqi Zhang. 2021. TermMind: Alibaba’s WMT21 Machine Translation Using Terminologies Task Submission. In Proceedings of the Sixth Conference on Machine Translation, pages 851–856, Online. Association for Computational Linguistics.
Cite (Informal):
TermMind: Alibaba’s WMT21 Machine Translation Using Terminologies Task Submission (Wang et al., WMT 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.wmt-1.85.pdf