Abstract
This paper describes anonymous submission to the WMT 2022 Quality Estimation shared task. We participate in Task 1: Quality Prediction for both sentence and word-level quality prediction tasks. Our system is a multilingual and multi-task model, whereby a single system can infer both sentence and word-level quality on multiple language pairs. Our system’s architecture consists of Pretrained Language Model (PLM) and task layers, and is jointly optimized for both sentence and word-level quality prediction tasks using multilingual dataset. We propose novel auxiliary tasks for training and explore diverse sources of additional data to demonstrate further improvements on performance. Through ablation study, we examine the effectiveness of proposed components and find optimal configurations to train our submission systems under each language pair and task settings. Finally, submission systems are trained and inferenced using K-folds ensemble. Our systems greatly outperform task organizer’s baseline and achieve comparable performance against other participants’ submissions in both sentence and word-level quality prediction tasks.- Anthology ID:
- 2022.wmt-1.59
- 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:
- 627–633
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.59
- DOI:
- Cite (ACL):
- Seunghyun Lim and Jeonghyeok Park. 2022. Papago’s Submission to the WMT22 Quality Estimation Shared Task. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 627–633, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Papago’s Submission to the WMT22 Quality Estimation Shared Task (Lim & Park, WMT 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.wmt-1.59.pdf