Experiments in domain adaptation for statistical machine translation (2007)
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| Venue: | Prague, Czech Republic. Association for Computational Linguistics |
| Citations: | 43 - 2 self |
BibTeX
@INPROCEEDINGS{Schroeder07experimentsin,
author = {Josh Schroeder},
title = {Experiments in domain adaptation for statistical machine translation},
booktitle = {Prague, Czech Republic. Association for Computational Linguistics},
year = {2007},
pages = {224--227}
}
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Abstract
The special challenge of the WMT 2007 shared task was domain adaptation. We took this opportunity to experiment with various ways of adapting a statistical machine translation systems to a special domain (here: news commentary), when most of the training data is from a different domain (here: European Parliament speeches). This paper also gives a description of the submission of the University of Edinburgh to the shared task. 1 Our framework: the Moses MT system The open source Moses (Koehn et al., 2007) MT system was originally developed at the University
Citations
| 434 | Moses: Open source toolkit for statistical machine translation - Koehn, Hoang, et al. - 2007 |
| 282 | Lattice-based minimum error rate training for statistical machine translation - Macherey, Och, et al. - 2008 |
| 65 | Clause restructuring for statistical machine translation - Collins, Koehn, et al. - 2005 |
| 34 | Edinburgh system description for the 2005 IWSLT speech translation evaluation - Koehn, Axelrod, et al. - 2005 |
| 30 | Statistical Phrase based Translation - Koehn, Och, et al. - 2003 |
| 10 | CCG supertags in factored statistical machine translation - Birch, Osborne, et al. - 2007 |
