LIMSI @ WMT'12

This paper describes LIMSI's submissions to the shared translation task. We report results for French-English and German-English in both directions. Our submissions use n-code, an open source system based on bilingual n-grams. In this approach, both the translation and target language models are estimated as conventional smoothed n-gram models; an approach we extend here by estimating the translation probabilities in a continuous space using neural networks. Experimental results show a significant and consistent BLEU improvement of approximately 1 point for all conditions. We also report preliminary experiments using an "on-the-fly" translation model.

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