LeConTra : a learner corpus of English-to-Dutch news translation

Publication type
C1
Publication status
Published
Authors
Vanroy, B., & Macken, L.
Editor
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélane Mazo, Jan Odijk and Stelios Piperidis
Series
PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2022)
Pagination
1807-1816
Publisher
European Language Resources Association (ELRA) (Marseille, France)
Conference
13th Conference on Language Resources and Evaluation (LREC 2022) (Marseille, France)
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Abstract

We present LeConTra, a learner corpus consisting of English-to-Dutch news translations enriched with translation process data. Three students of a Master's programme in Translation were asked to translate 50 different English journalistic texts of approximately 250 tokens each. Because we also collected translation process data in the form of keystroke logging, our dataset can be used as part of different research strands such as translation process research, learner corpus research, and corpus-based translation studies. Reference translations, without process data, are also included. The data has been manually segmented and tokenized, and manually aligned at both segment and word level, leading to a high-quality corpus with token-level process data. The data is freely accessible via the Translation Process Research DataBase, which emphasises our commitment of distributing our dataset. The tool that was built for manual sentence segmentation and tokenization, Mantis, is also available as an open-source aid for data processing.