LUL’s WMT22 Automatic Post-Editing Shared Task Submission

Xiaoying Huang, Xingrui Lou, Fan Zhang, Tu Mei


Abstract
By learning the human post-edits, the automatic post-editing (APE) models are often used to modify the output of the machine translation (MT) system to make it as close as possible to human translation. We introduce the system used in our submission of WMT’22 Automatic Post-Editing (APE) English-Marathi (En-Mr) shared task. In this task, we first train the MT system of En-Mr to generate additional machine-translation sentences. Then we use the additional triple to bulid our APE model and use APE dataset to further fine-tuning. Inspired by the mixture of experts (MoE), we use GMM algorithm to roughly divide the text of APE dataset into three categories. After that, the experts are added to the APE model and different domain data are sent to different experts. Finally, we ensemble the models to get better performance. Our APE system significantly improves the translations of provided MT results by -2.848 and +3.74 on the development dataset in terms of TER and BLEU, respectively. Finally, the TER and BLEU scores are improved by -1.22 and +2.41 respectively on the blind test set.
Anthology ID:
2022.wmt-1.68
Volume:
Proceedings of the Seventh Conference on Machine Translation (WMT)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Editors:
Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
689–693
Language:
URL:
https://aclanthology.org/2022.wmt-1.68
DOI:
Bibkey:
Cite (ACL):
Xiaoying Huang, Xingrui Lou, Fan Zhang, and Tu Mei. 2022. LUL’s WMT22 Automatic Post-Editing Shared Task Submission. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 689–693, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
LUL’s WMT22 Automatic Post-Editing Shared Task Submission (Huang et al., WMT 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.wmt-1.68.pdf