Enriching a statistical machine translation system trained on small parallel corpora with rule-based bilingual phrases
Víctor M. Sánchez-Cartagena, Felipe Sánchez-Martínez, Juan Antonio Pérez-Ortiz · Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante) · 2011
In this paper, we present a new hybridisation approach consisting of enriching the phrase table of a phrase-based statistical machine translation system with bilingual phrase pairs matching structural transfer rules and dictionary entries from a shallowtransfer rule-based machine translation system. We have tested this approach on different small parallel corpora scenarios, where pure statistical machine translation systems suffer from data sparseness. The results obtained show an improvement in translation quality, specially when translating out-of-domain texts that are well covered by the shallow-transfer rule-based machine translation system we have used. 1