The KIT-LIMSI Translation System for WMT 2014
By Quoc-Khanh Do, Teresa Herrmann, Jan Niehues, Alexander Allauzen, François Yvon, A. Waibel. 2014
3 citations recorded by the source corpus.
This paper describes the joined submission of LIMSI and KIT to the Shared Translation Task for the German-toEnglish direction. The system consists of a phrase-based translation system using a pre-reordering approach. The baseline system already includes several models like conventional language models on different word factors and a discriminative word lexicon. This system is used to generate a k-best list. In a second step, the list is reranked using SOUL language and translation models (Le et al., 2011). Originally, SOUL translation models were applied to n-gram-based translation systems that use tuples as translation units instead of phrase pairs. In this article, we describe their integration into the KIT phrase-based system. Experimental results show that their use can yield significant improvements in terms of BLEU score.
Subfields: Natural Language Processing
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In Natural Language Processing
- Philipp Koehn
- Lucia Specia
- Ondrej Bojar
- Barry Haddow
- Matt Post
- Christof Monz
- Rico Sennrich
- Graham Neubig
Citations in the corpus
- Findings of the 2014 Workshop on Statistical Machine Translation (2014, methodology): “A rank range was collected for each system across these folds; the average value was used to order the systems, and a 95% confidence interval across these ranks was used to organize the systems into equivalence classes containing systems with over-18 lapping ranges.”