Pivot-based Machine Translation between Statistical and Black Box systems
Antonio Toral · 2012
This paper presents a novel approach to pivot-based machine translation (MT): while the state-of-the-art uses two statistical systems, this proposal treats the second system as a black box. Our approach effecively provides pivot-based MT to target languages for which no suitable bilingual corpora are available to build statistical systems, as long as any other kind of MT system is available. We experiment with an algorithm that uses two features to find the best translation: the translation score provided by the first system and fluency of the final translation. Despite its simplicity, this approach yields significant improvements over the baseline, which translates the source sentences using the two MT systems sequentially. We have experimented with two scenarios, technical documentation in Romance languages and newswire in Slavic languages, obtaining 11.88 % and 13.32 % relative improvements in terms of BLEU, respectively. 1