Statistical methods have proven to be very effective when addressing linguistic problems, specially when dealing with Machine Translation. Nevertheless, Statistical Machine Translation effectiveness is limited to situations where large amounts of training data are available. Therefore, the broader the coverage of a SMT system is, the better the chances to get a reasonable output are. In this paper we propose a method to improve quality of translations of a phrase-based Machine Translation system by extending phrase-tables with the use of translation paraphrases learned from a third language. Our experiments were done translating from Spanish to English pivoting through French.
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