SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
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 tr...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
BioMed Central
2020-06-01
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| Series: | Genomics & Informatics |
| Subjects: | |
| Online Access: | http://genominfo.org/upload/pdf/gi-2020-18-2-e21.pdf |
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| Summary: | 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. |
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| ISSN: | 2234-0742 |