Abstract
Multilingual neural machine translation (M-NMT) has recently shown to improve performance of machine translation of low-resource languages. Thanks to its implicit transfer-learning mechanism, the availability of a highly resourced language pair can be leveraged to learn useful representation for a lower resourced language. This work investigates how a low-resource translation task can be improved within a multilingual setting. First, we adapt a system trained on multiple language directions to a specific language pair. Then, we utilize the adapted model to apply an iterative training-inference scheme [1] using monolingual data. In the experimental setting, an extremely low-resourced Basque-English language pair (i.e., ≈ 5.6K in-domain training data) is our target translation task, where we considered a closely related French/Spanish-English parallel data to build the multilingual model. Experimental results from an i) in-domain and ii) an out-of-domain setting with additional training data, show improvements with our approach. We report a translation performance of 15.89 with the former and 23.99 BLEU with the latter on the official IWSLT 2018 Basque-English test set.- Anthology ID:
- 2018.iwslt-1.24
- Volume:
- Proceedings of the 15th International Conference on Spoken Language Translation
- Month:
- October 29-30
- Year:
- 2018
- Address:
- Brussels
- Editors:
- Marco Turchi, Jan Niehues, Marcello Frederico
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- International Conference on Spoken Language Translation
- Note:
- Pages:
- 160–165
- Language:
- URL:
- https://aclanthology.org/2018.iwslt-1.24
- DOI:
- Cite (ACL):
- Surafel M. Lakew and Marcello Federico. 2018. Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018. In Proceedings of the 15th International Conference on Spoken Language Translation, pages 160–165, Brussels. International Conference on Spoken Language Translation.
- Cite (Informal):
- Adapting Multilingual NMT to Extremely Low Resource Languages FBK’s Participation in the Basque-English Low-Resource MT Task, IWSLT 2018 (Lakew & Federico, IWSLT 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2018.iwslt-1.24.pdf