An open-source toolkit for integrating shallow-transfer rules into phrase-based statistical machine translation
Víctor M. Sánchez-Cartagena, Felipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz · RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2012
In this paper, we present an open-source toolkit to enrich a phrase-based statistical machine translation system (Moses) with phrase pairs generated from the linguistic resources of a shallow-transfer rule-based machine translation system (Apertium). A system built with this toolkit was not outperformed by any other participant in the shared translation task of the Sixth Workshop on Statistical Machine Translation (WMT 11) for the Spanish–English language pair. Statistical machine translation (SMT) (Koehn, 2010) systems are very attractive because they may be built with little human effort when enough monolingual and bilingual corpora are available. However, bilingual corpora are not always easy to harvest, and they may not even exist for some language pairs. On the contrary, rule-based machine translation