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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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Detalles Bibliográficos
Autores principales: Soares, Felipe, Rebechi, Rozane, Stevenson, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korea Genome Organization 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362948/
https://www.ncbi.nlm.nih.gov/pubmed/32634875
http://dx.doi.org/10.5808/GI.2020.18.2.e21
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author Soares, Felipe
Rebechi, Rozane
Stevenson, Mark
author_facet Soares, Felipe
Rebechi, Rozane
Stevenson, Mark
author_sort Soares, Felipe
collection PubMed
description 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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spelling pubmed-73629482020-07-23 SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts Soares, Felipe Rebechi, Rozane Stevenson, Mark Genomics Inform Application Note 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. Korea Genome Organization 2020-06-15 /pmc/articles/PMC7362948/ /pubmed/32634875 http://dx.doi.org/10.5808/GI.2020.18.2.e21 Text en (c) 2020, Korea Genome Organization (CC) 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.
spellingShingle Application Note
Soares, Felipe
Rebechi, Rozane
Stevenson, Mark
SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title_full SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title_fullStr SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title_full_unstemmed SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title_short SciBabel: a system for crowd-sourced validation of automatic translations of scientific texts
title_sort scibabel: a system for crowd-sourced validation of automatic translations of scientific texts
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7362948/
https://www.ncbi.nlm.nih.gov/pubmed/32634875
http://dx.doi.org/10.5808/GI.2020.18.2.e21
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