Projects per year
Abstract
We investigate three methods for integrating an unsupervised transliteration model into an end-to-end SMT system. We induce a transliteration model from parallel data and use it to translate OOV words. Our approach is fully unsupervised and language independent. In the methods to integrate transliterations, we observed
improvements from 0.23-0.75 (∆ 0.41) BLEU points across 7 language pairs. We
also show that our mined transliteration corpora provide better rule coverage and
translation quality compared to the gold standard transliteration corpora.
improvements from 0.23-0.75 (∆ 0.41) BLEU points across 7 language pairs. We
also show that our mined transliteration corpora provide better rule coverage and
translation quality compared to the gold standard transliteration corpora.
Original language | English |
---|---|
Title of host publication | Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2014, April 26-30, 2014, Gothenburg, Sweden |
Pages | 148-153 |
Number of pages | 6 |
Publication status | Published - 2014 |
Fingerprint
Dive into the research topics of 'Integrating an Unsupervised Transliteration Model into Statistical Machine Translation'. Together they form a unique fingerprint.Projects
- 1 Finished
-
EU-Bridge
Renals, S. (Principal Investigator), King, S. (Co-investigator), Koehn, P. (Co-investigator) & Osborne, M. (Co-investigator)
1/02/12 → 31/01/15
Project: Research