Abstract
Multilingual neural machine translation can translate unseen language pairs during training, i.e. zero-shot translation. However, the zero-shot translation is always unstable. Although prior works attributed the instability to the domination of central language, e.g. English, we supplement this viewpoint with the strict dependence of non-centered languages. In this work, we propose a simple, lightweight yet effective language-specific modeling method by adapting to non-centered languages and combining the shared information and the language-specific information to counteract the instability of zero-shot translation. Experiments with Transformer on IWSLT17, Europarl, TED talks, and OPUS-100 datasets show that our method not only performs better than strong baselines in centered data conditions but also can easily fit non-centered data conditions. By further investigating the layer attribution, we show that our proposed method can disentangle the coupled representation in the correct direction.- Anthology ID:
- 2022.coling-1.467
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 5251–5265
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.467
- DOI:
- Cite (ACL):
- Zhi Qu and Taro Watanabe. 2022. Adapting to Non-Centered Languages for Zero-shot Multilingual Translation. In Proceedings of the 29th International Conference on Computational Linguistics, pages 5251–5265, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Adapting to Non-Centered Languages for Zero-shot Multilingual Translation (Qu & Watanabe, COLING 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.coling-1.467.pdf
- Code
- zhiqu22/adapnoncenter
- Data
- OPUS-100