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DOI: 10.14569/IJARAI.2016.050404
PDF

Multiple-Language Translation System Focusing on Long-distance Medical and Outpatient Services

Author 1: Rena Aierken
Author 2: Li Xiao
Author 3: Su Sha
Author 4: Dawa Yidemucao

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 5 Issue 4, 2016.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: For people living in the countryside, an effective long-distance medical and health service is very important. People living in western China, especially, require convenient communication in their native language with doctors working in a modern city. To address this problem, a multiple-language translation system for long-distance medical and outpatient services is discussed. This system initially provides a table containing basic information including disease names and symptoms for different medical classifications, and then translates the sentences selected from the table automatically using a machine translation system. Finally, a PDF file is created for the doctor and the patient. In this paper, the system construction and evaluation of the machine translation are introduced.

Keywords: questionnaire for outpatient cases; Chinese Uyghur language; medical Chinese-Minority language parallel corpus; statistical machine translation

Rena Aierken, Li Xiao, Su Sha and Dawa Yidemucao, “Multiple-Language Translation System Focusing on Long-distance Medical and Outpatient Services” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(4), 2016. http://dx.doi.org/10.14569/IJARAI.2016.050404

@article{Aierken2016,
title = {Multiple-Language Translation System Focusing on Long-distance Medical and Outpatient Services},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2016.050404},
url = {http://dx.doi.org/10.14569/IJARAI.2016.050404},
year = {2016},
publisher = {The Science and Information Organization},
volume = {5},
number = {4},
author = {Rena Aierken and Li Xiao and Su Sha and Dawa Yidemucao}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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