Abstract
We present two problems for statistically extracting bilingual lexicon: (1) How can noisy parallel corpora be used? (2) How can non-parallel yet comparable corpora be used? We describe our own work and contribution in relaxing the constraint of using only clean parallel corpora. DKvec is a method for extracting bilingual lexicons, from noisy parallel corpora based on arrival distances of words in noisy parallel corpora. Using DKvec on noisy parallel corpora in English/Japanese and English/Chinese, our evaluations show a 55.35% precision from a small corpus and 89.93% precision from a larger corpus. Our major contribution is in the extraction of bilingual lexicon from non-parallel corpora. We present a first such result in this area, from a new method-Convec. Convec is based on context information of a word to be translated.- Anthology ID:
- 1998.amta-papers.1
- Volume:
- Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers
- Month:
- October 28-31
- Year:
- 1998
- Address:
- Langhorne, PA, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Springer
- Note:
- Pages:
- 1–17
- Language:
- URL:
- https://link.springer.com/chapter/10.1007/3-540-49478-2_1
- DOI:
- Cite (ACL):
- Pascale Fung. 1998. A statistical view on bilingual lexicon extraction. In Proceedings of the Third Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 1–17, Langhorne, PA, USA. Springer.
- Cite (Informal):
- A statistical view on bilingual lexicon extraction (Fung, AMTA 1998)
- PDF:
- https://link.springer.com/chapter/10.1007/3-540-49478-2_1