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

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.

[1]  Jeffrey Heer,et al.  The efficacy of human post-editing for language translation , 2013, CHI.

[2]  Katrin Kirchhoff,et al.  Evaluating Groupware Prototypes with Discount Methods , 2015, CSCW Companion.

[3]  Eric M. Cheng,et al.  Primary Language and Receipt of Recommended Health Care Among Hispanics in the United States , 2007, Journal of General Internal Medicine.

[4]  Marc Dymetman,et al.  A Statistical Machine Translation Primer , 2009 .

[5]  Carl Gutwin,et al.  The mechanics of collaboration: developing low cost usability evaluation methods for shared workspaces , 2000, Proceedings IEEE 9th International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WET ICE 2000).

[6]  K. J. Vicente,et al.  Cognitive Work Analysis: Toward Safe, Productive, and Healthy Computer-Based Work , 1999 .

[7]  Katrin Kirchhoff,et al.  A comparison of human and machine translation of health promotion materials for public health practice: time, costs, and quality. , 2014, Journal of public health management and practice : JPHMP.

[8]  Katrin Kirchhoff,et al.  Integrated post-editing and translation management for lay user communities , 2013, MTSUMMIT.

[9]  Jana Bradley,et al.  Modeling public health interventions for improved access to the gray literature. , 2005, Journal of the Medical Library Association : JMLA.

[10]  Benjamin B. Bederson,et al.  Translation by iterative collaboration between monolingual users , 2010, HCOMP '10.

[11]  N. Peña-Purcell,et al.  Hispanics' use of Internet health information: an exploratory study. , 2008, Journal of the Medical Library Association : JMLA.

[12]  Christine Chambers Goodman.  The Civil Rights Act , 1964, Social Service Review.

[13]  Philipp Koehn,et al.  Findings of the 2014 Workshop on Statistical Machine Translation , 2014, WMT@ACL.

[14]  Jennifer Doyon,et al.  Automated Machine Translation Improvement Through Post-Editing Techniques: Analyst and Translator Experiments , 2008, AMTA.

[15]  A. Cardelle,et al.  The Quality of Spanish Health Information Websites , 2005 .

[16]  Leiyu Shi,et al.  The influence of English proficiency on access to care , 2009, Ethnicity & health.

[17]  Jeff Allen.  Postediting: an integrated part of a translation software program , 2001 .

[18]  Chhandasi Pandya,et al.  Limited English Proficient Individuals in the United States: Number, Share, Growth, and Linguistic Diversity. LEP Data Brief. , 2011 .

[19]  Julie A. Kientz,et al.  A web-based collaborative translation management system for public health workers , 2013, CHI Extended Abstracts.

[20]  Miles Osborne,et al.  Statistical Machine Translation , 2010, Encyclopedia of Machine Learning and Data Mining.

[21]  Katrin Kirchhoff,et al.  Modeling workflow to design machine translation applications for public health practice , 2015, J. Biomed. Informatics.

[22]  Jeffrey Heer,et al.  Predictive translation memory: a mixed-initiative system for human language translation , 2014, UIST.

[23]  Amittai Axelrod,et al.  Application of statistical machine translation to public health information: a feasibility study , 2011, J. Am. Medical Informatics Assoc..

[24]  Toru Ishida,et al.  Collaborative translation by monolinguals with machine translators , 2009, IUI.