| Abstract | Data selection has been demonstrated to be an effective approach to addressing the lack of high-quality bitext for statistical machine translation in the domain of interest. |
| Conclusion | our methods into domain adaptation task of statistical machine translation in model level. |
| Introduction | Statistical machine translation depends heavily on large scale parallel corpora. |
| Training Data Selection Methods | Translation model is a key component in statistical machine translation . |
| Introduction | In particular, we use topic models to aid statistical machine translation (Koehn, 2009, SMT). |
| Topic Models for Machine Translation | 2.1 Statistical Machine Translation |
| Topic Models for Machine Translation | Statistical machine translation casts machine translation as a probabilistic process (Koehn, 2009). |
| Abstract | In this paper, we propose a sense-based translation model to integrate word senses into statistical machine translation . |
| Introduction | Therefore a natural assumption is that word sense disambiguation (WSD) may contribute to statistical machine translation (SMT) by providing appropriate word senses for target translation selection with context features (Carpuat and Wu, 2005). |
| Introduction | 'or Statistical Machine Translation |
| Abstract | In this paper, we report our preliminary efforts in building an English-Turkish parallel treebank corpus for statistical machine translation . |
| Introduction | For example, EuroParl corpus (Koehn, 2002), one of the biggest parallel corpora in statistical machine translation , contains 22 languages (but not Turkish). |
| Introduction | In this study, we report our preliminary efforts in constructing an English-Turkish parallel treebank corpus for statistical machine translation . |