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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
Descripción
Sumario: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.