Achraf Ben Romdhane


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Phrase-based language modelling for statistical machine translation
Achraf Ben Romdhane | Salma Jamoussi | Abdelmajid Ben Hamadou | Kamel Smaïli
Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign

In this paper, we present our submitted MT system for the IWSLT2014 Evaluation Campaign. We participated in the English-French translation task. In this article we focus on one of the most important component of SMT: the language model. The idea is to use a phrase-based language model. For that, sequences from the source and the target language models are retrieved and used to calculate a phrase n-gram language model. These phrases are used to rewrite the parallel corpus which is then used to calculate a new translation model.