PHAST: A Collaborative Machine Translation and Post-editing Tool for Public Health

نویسندگان

  • Kristin Dew
  • Anne M. Turner
  • Loma Desai
  • Nathalie Martin
  • Adrian Laurenzi
چکیده

This paper describes a novel collaborative machine translation (MT) plus post-editing system called PHAST (Public Health Automatic System for Translation, phastsystem.org), tailored for use in producing multilingual education materials for public health. Its collaborative features highlight a new approach in public health informatics: sharing limited bilingual translation resources via a groupware system. We report here on the design methods and requirements used to develop PHAST and on its evaluation with potential public health users. Our results indicate such a system could be a feasible means of increasing the production of multilingual public health materials by reducing the barriers of time and cost. PHAST's design can serve as a model for other communities interested in assuring the accuracy of MT through shared language expertise.

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عنوان ژورنال:
  • AMIA ... Annual Symposium proceedings. AMIA Symposium

دوره 2015  شماره 

صفحات  -

تاریخ انتشار 2015