Document-specific statistical machine translation for improving human translation productivity

Abstract

We present two long term studies of the productivity of human translators by augmenting an existing Translation Memory system with Document-Specific Statistical Machine Translation. While the MT Post-Editing approach represents a significant change to the current practice of human translation, the two studies demonstrate a significant increase in the productivity of human translators, on the order of about 50% in the first study and of 68% in the second study conducted a year later. Both studies used a pool of 15 translators and concentrated on English-Spanish translation of IBM content in a production Translation Services Center. © 2012 Springer-Verlag.