In this paper, we report an analysis of the strengths and weaknesses of several Machine Translation (MT) engines implementing the three most widely used paradigms. The analysis is based on a manually built test suite that comprises a large range of linguistic phenomena. Two main observations are on the one hand the striking improvement of an commercial online system when turning from a phrase-based to a neural engine and on the other hand that the successful translations of neural MT systems sometimes bear resemblance with the translations of a rule-based MT system.
No takes yet. Share an insight, caveat, or question.
Burchardt et al. (2017) studied this question.
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: