The use of morphology is particularly interesting in the context of statistical machine translation in order to reduce data sparseness and compensate a lack of training corpus. In this work, we propose several approaches to introduce morphology knowledge into a standard phrase-based machine translation system. We provide word segmentation using two different tools (COGROO and MORFESSOR) which allow reducing the vocabulary and data sparseness. Then, to these segmentations we add the

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... information of a POS language model. We combine all these approaches using a Minimum Bayes Risk strategy. Experiments show significant improvements from the enhanced system over the baseline system on the Brazilian-Portuguese/English language pair. Finally, we report a case study of the impact of enhancing the statistical machine translation system with morphology in a cross-language application system such as ONAIR which allows users to look for information in video fragments through queries in natural language.