Fourteen Light Tasks for comparing Analogical and Phrase-based Machine Translation

In this study we compare two machine translation devices on twelve machine translation medicaldomain specific tasks, and two transliteration tasks, altogether involving twelve language pairs, including English-Chinese and English-Russian, which do not share the same scripts. We implemented an analogical device and compared its performance to the state-of-the-art phrase-based machine translation engine Moses. On most translation tasks, the analogical device outperforms the phrase-based one, and several combinations of both systems significantly outperform each system individually. For the sake of reproducibility, we share the datasets used in this study.