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Enabling Medical Translation for Low-Resource Languages

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Computational Linguistics and Intelligent Text Processing (CICLing 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9624))

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Abstract

We present research towards bridging the language gap between migrant workers in Qatar and medical staff. In particular, we present the first steps towards the development of a real-world Hindi-English machine translation system for doctor-patient communication. As this is a low-resource language pair, especially for speech and for the medical domain, our initial focus has been on gathering suitable training data from various sources. We applied a variety of methods ranging from fully automatic extraction from the Web to manual annotation of test data. Moreover, we developed a method for automatically augmenting the training data with synthetically generated variants, which yielded a very sizable improvement of more than 3 BLEU points absolute.

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Notes

  1. 1.

    http://qatar-weill.cornell.edu.

  2. 2.

    http://www.universaldoctor.com.

  3. 3.

    http://medibabble.com.

  4. 4.

    http://www.canopyapps.com.

  5. 5.

    http://mavroinc.com/medical.html.

  6. 6.

    http://duochart.com.

  7. 7.

    http://www.khresmoi.eu.

  8. 8.

    http://www.wikipedia.org.

  9. 9.

    http://www.wiktionary.org.

  10. 10.

    http://www.omegawiki.org.

  11. 11.

    https://github.com/tesseract-ocr.

  12. 12.

    http://www.opensubtitles.com.

  13. 13.

    http://www.ncbi.nlm.nih.gov/mesh.

  14. 14.

    EMILLE contains about 12,000 sentences of comparable data in Hindi and Urdu. We were able to align about 7,000 sentences to build an Urdu-to-Hindi system.

  15. 15.

    We used mkcls to cluster the data into 50 clusters.

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Acknowledgments

The authors would like to thank Naila Khalisha and Manisha Bansal for their contributions towards the project.

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Authors and Affiliations

  1. Qatar Computing Research Institute, HBKU, Doha, Qatar

    Ahmad Musleh, Nadir Durrani, Irina Temnikova, Preslav Nakov & Stephan Vogel

  2. Texas A&M University in Qatar, Doha, Qatar

    Osama Alsaad

Authors
  1. Ahmad Musleh
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  2. Nadir Durrani
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  3. Irina Temnikova
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  4. Preslav Nakov
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  5. Stephan Vogel
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Corresponding author

Correspondence to Nadir Durrani .

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Editors and Affiliations

  1. CIC, Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

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Musleh, A., Durrani, N., Temnikova, I., Nakov, P., Vogel, S., Alsaad, O. (2018). Enabling Medical Translation for Low-Resource Languages. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science(), vol 9624. Springer, Cham. https://doi.org/10.1007/978-3-319-75487-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-75487-1_1

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