Passive and pervasive use of a bilingual dictionary in statistical machine translation

Abstract

There are two primary approaches to the use bilingual dictionary in statistical machine translation: (i) the passive approach of appending the parallel training data with a bilingual dictionary and (ii) the pervasive approach of enforcing translation as per the dictionary entries when decoding. Previous studies have shown that both approaches provide external lexical knowledge to statistical machine translation thus improving translation quality. We empirically investigate the effects of both approaches on the same dataset and provide further insights on how lexical information can be reinforced in statistical machine translation.