The Multilingual Student Translation corpus: a resource for translation teaching and research

Abstract

The Multilingual Student Translation (MUST) corpus is a corpus of translations produced by foreign language learners or trainee translators collected collaboratively by a large number of partner teams internationally. The corpus represents a prime example of community sourcing, as the data are collected and shared by the members of the MUST network. Two key characteristics of the corpus are that it involves a large number of language pairs and that each text is accompanied by a rich set of standardized metadata related to the source texts, the translation tasks and the students. The web interface on which the corpus is stored allows the data to be aligned and annotated with a purpose-built translation annotation system. The resulting corpus data lend themselves to a range of applications (translator training, materials design, pedagogical lexicography) and can also be used to advance empirical research in corpus-based translation studies.