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
Correct Metadata for
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)
- 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:
- 1198–1204
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.123/
- DOI:
- 10.18653/v1/2022.wmt-1.123
- 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)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.wmt-1.123.pdf
Export citation
@inproceedings{ge-etal-2022-tsmind,
title = "{TSM}ind: {A}libaba and Soochow University{'}s Submission to the {WMT}22 Translation Suggestion Task",
author = "Ge, Xin and
Wang, Ke and
Wang, Jiayi and
Xiao, Nini and
Duan, Xiangyu and
Zhao, Yu and
Zhang, Yuqi",
editor = {Koehn, Philipp and
Barrault, Lo{\"i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Jimeno Yepes, Antonio and
Kocmi, Tom and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Popel, Martin and
Turchi, Marco and
Zampieri, Marcos},
booktitle = "Proceedings of the Seventh Conference on Machine Translation (WMT)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.wmt-1.123/",
doi = "10.18653/v1/2022.wmt-1.123",
pages = "1198--1204",
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."
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%0 Conference Proceedings %T TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task %A Ge, Xin %A Wang, Ke %A Wang, Jiayi %A Xiao, Nini %A Duan, Xiangyu %A Zhao, Yu %A Zhang, Yuqi %Y Koehn, Philipp %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Jimeno Yepes, Antonio %Y Kocmi, Tom %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Popel, Martin %Y Turchi, Marco %Y Zampieri, Marcos %S Proceedings of the Seventh Conference on Machine Translation (WMT) %D 2022 %8 December %I Association for Computational Linguistics %C Abu Dhabi, United Arab Emirates (Hybrid) %F ge-etal-2022-tsmind %X 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. %R 10.18653/v1/2022.wmt-1.123 %U https://aclanthology.org/2022.wmt-1.123/ %U https://doi.org/10.18653/v1/2022.wmt-1.123 %P 1198-1204
Markdown (Informal)
[TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task](https://aclanthology.org/2022.wmt-1.123/) (Ge et al., WMT 2022)
- TSMind: Alibaba and Soochow University’s Submission to the WMT22 Translation Suggestion Task (Ge et al., WMT 2022)
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.