Learning Translations via Matrix Completion
Derry Tanti Wijaya, Brendan Callahan, John Hewitt, Jie Gao, Xiao Ling, Marianna Apidianaki, Chris Callison-Burch
Abstract
Bilingual Lexicon Induction is the task of learning word translations without bilingual parallel corpora. We model this task as a matrix completion problem, and present an effective and extendable framework for completing the matrix. This method harnesses diverse bilingual and monolingual signals, each of which may be incomplete or noisy. Our model achieves state-of-the-art performance for both high and low resource languages.- Anthology ID:
- D17-1152
- Volume:
- Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Venue:
- EMNLP
- SIG:
- SIGDAT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1452–1463
- Language:
- URL:
- https://aclanthology.org/D17-1152
- DOI:
- 10.18653/v1/D17-1152
- Cite (ACL):
- Derry Tanti Wijaya, Brendan Callahan, John Hewitt, Jie Gao, Xiao Ling, Marianna Apidianaki, and Chris Callison-Burch. 2017. Learning Translations via Matrix Completion. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, pages 1452–1463, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Learning Translations via Matrix Completion (Wijaya et al., EMNLP 2017)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/D17-1152.pdf