| Sumario: | Around the world, a growing interest has been seen in learner translator corpora, which are invaluable resources for teaching and research. This paper introduces a new resource to support researchers from different interdisciplinary areas such as computational linguistics, descriptive translation studies, computer-aided translation technology, Arabic machine translation applications, cognitive science, and translation pedagogy. Motivated by the lack of learner translator resources that provide data about learners of translation from and into Arabic, the undergraduate learner translator corpus (ULTC) is an ongoing, error-tagged sentence-aligned parallel corpus of English, Arabic, and French, with Arabic as its main language. The present corpus, consisting of parallel texts of female learners of translation from English or French into Arabic, is the first of its kind in terms of the languages represented, tasks covered, and number of students involved. It is also unique in terms of combining many complementary corpora of cross-lingual data, each of which has its own web-based query interface and corpus analysis tools. This paper describes the ULTC compilation process, preliminary findings, and planned future expansion and research.
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