Soares, F. orcid.org/0000-0002-2837-1853, Rebechi, R. and Stevenson, M. orcid.org/0000-0002-9483-6006 (2020) SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts. Genomics and Informatics, 18 (2). e21. ISSN 2234-0742
Abstract
Scientific research is mostly published in English, regardless of the researcher's nationality. However, this growing practice impairs or hinders the comprehension of professionals who depend on the results of these studies to provide adequate care for their patients. We suggest that machine translation (MT) can be used as a way of providing useful translation for biomedical articles, even though the translation itself may not be fluent. To tackle possible mistranslation that can harm a patient, we resort to crowd-sourced validation of translations. We developed a prototype of MT validation and edition, where users can vote for that translation as valid, or suggest modifications (i.e., post-editing the MT). A glossary match system is also included, aiming at terminology consistency.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020, Korea Genome Organization. This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | crowdsourcing; linguistics; machine translation; medical informatics applications; PubMed |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 23 Mar 2022 16:58 |
Last Modified: | 25 Mar 2022 04:15 |
Status: | Published |
Publisher: | Korea Genome Organization |
Refereed: | Yes |
Identification Number: | 10.5808/gi.2020.18.2.e21 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:185028 |