Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation
Longyue Wang, Siyou Liu, Chenyang Lyu, Wenxiang Jiao, Xing Wang, Jiahao Xu, Zhaopeng Tu, Yan Gu, Weiyu Chen, Minghao Wu, Liting Zhou, Philipp Koehn, Andy Way, Yulin Yuan
Abstract
Translating literary works has perennially stood as an elusive dream in machine translation (MT), a journey steeped in intricate challenges. To foster progress in this domain, we hold a new shared task at WMT 2023, the second edition of the Discourse-Level Literary Translation. First, we (Tencent AI Lab and China Literature Ltd.) release a copyrighted and document-level Chinese-English web novel corpus. Furthermore, we put forth an industry-endorsed criteria to guide human evaluation process. This year, we totally received 10 submissions from 5 academia and industry teams. We employ both automatic and human evaluations to measure the performance of the submitted systems. The official ranking of the systems is based on the overall human judgments. In addition, our extensive analysis reveals a series of interesting findings on literary and discourse-aware MT. We release data, system outputs, and leaderboard at https://www2.statmt.org/wmt24/literary-translation-task.html.- Anthology ID:
- 2024.wmt-1.58
- Volume:
- Proceedings of the Ninth Conference on Machine Translation
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Barry Haddow, Tom Kocmi, Philipp Koehn, Christof Monz
- Venue:
- WMT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 699–700
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.wmt-1.58/
- DOI:
- 10.18653/v1/2024.wmt-1.58
- Cite (ACL):
- Longyue Wang, Siyou Liu, Chenyang Lyu, Wenxiang Jiao, Xing Wang, Jiahao Xu, Zhaopeng Tu, Yan Gu, Weiyu Chen, Minghao Wu, Liting Zhou, Philipp Koehn, Andy Way, and Yulin Yuan. 2024. Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation. In Proceedings of the Ninth Conference on Machine Translation, pages 699–700, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation (Wang et al., WMT 2024)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.wmt-1.58.pdf