Lapshinova-Koltunski, Ekaterina ORCID: 0000-0002-5618-8087, Popović, Maja ORCID: 0000-0001-8234-8745 and Koponen, Maarit ORCID: 0000-0002-6123-5386 (2022) DiHuTra: a parallel corpus to analyse differences between human translations. In: 13th Language Resources and Evaluation Conference, 20-25 June 2022, Marseille, France.
Abstract
This paper describes a new corpus of human translations which contains both professional and students translations. The data consists of English sources — texts from news and reviews — and their translations into Russian and Croatian, as well as of the subcorpus containing translations of the review texts into Finnish. All target languages represent mid-resourced and less or mid-investigated ones. The corpus will be valuable for studying variation in translation as it allows a direct comparison between human translations of the same source texts. The corpus will also be a valuable resource for evaluating machine translation systems. We believe that this resource will facilitate understanding and improvement of the quality issues in both human and machine translation. In the paper, we describe how the data was collected, provide information on translator groups and summarise the differences between the human translations at hand based on our preliminary results with shallow features.
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | translation; human translation; parallel corpus; multilingual corpus; multilinguality; Russian; Croatian; Finnish; translation variation; news translation; review translation |
Subjects: | Computer Science > Machine translating Humanities > Translating and interpreting |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing Research Initiatives and Centres > ADAPT |
Published in: | Proceedings of the Thirteenth Language Resources and Evaluation Conference. . European Language Resources Association. |
Publisher: | European Language Resources Association |
Official URL: | https://aclanthology.org/2022.lrec-1.186 |
Copyright Information: | © European Language Resources Association (ELRA) |
ID Code: | 28366 |
Deposited On: | 25 May 2023 11:51 by Maja Popovic . Last Modified 25 May 2023 11:51 |
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