On the Role of Translations in State‐of‐the‐Art Statistical Machine Translation

Abstract

Abstract For the state‐of‐the‐art in Machine Translation (MT) to advance, we contend that Statistical MT (SMT) practitioners will have to collaborate with linguists and translators. This has not happened to date for two main reasons: (i) there remain many translators – and even more surprisingly, many experienced MT protagonists – who find the basic model of SMT very difficult to understand; and (ii) while current approaches to MT depend entirely on the availability of large quantities of translated data, very little thought is given to the process by which the data were produced and the kinds of phenomena that are known to exist in real‐translated texts. We argue that much light can be shed on these by looking at the areas of contrastive linguistics and translation studies. In this paper, we describe how central linguists and translators are to the MT process, so that SMT developers and researchers may better understand how to include these previously neglected groups in continuing to advance the state‐of‐the‐art. In a companion paper, we describe the workings of SMT in language that is understandable to linguists and translators. If these constituencies are to make an impact in the field of MT, they need to know how their input is used by the SMT systems, and how they can help in the data annotation phase which is crucial if greater strides are to be made than heretofore.