Learner Translations in Contrast

This article reports on a contrastive descriptive study of learner translations into Basque and Spanish of the same source text originally written in English. It is a preliminary case study with a twofold aim: first, to bring to contrast translations into different target languages (TLs) that have been produced under the same circumstances; and two, to identify and test the usefulness of corpus metadata in the interpretation of the translation product. The study was conducted within the framework of the MUST (MUltilingual Student Translation) project. Accordingly, all learner translations were first aligned, and then annotated with regard to three different error categories: transfer, language, and meta-text. The juxtaposition and contrast of the translational phenomena identified in each target language showed that the Basque data set reveals more language-related problems, while the Spanish data set features slightly more transfer-related errors. In interpreting the results, we benefited from the learners’ metadata our MUST corpora are enriched with. In particular, we observed that those learners who considered Basque to be their one and only mother tongue performed the best in terms of language.