Enabling medical translation for low-resource languages

Ahmad Musleh, Nadir Durrani*, Irina Temnikova, Preslav Nakov, Stephan Vogel, Osama Alsaad

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationComputational Linguistics and Intelligent Text Processing - 17th International Conference, CICLing 2016, Revised Selected Papers
EditorsAlexander Gelbukh
PublisherSpringer Verlag
Pages3-16
Number of pages14
ISBN (Print)9783319754864
DOIs
Publication statusPublished - 2018
Event17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016 - Konya, Turkey
Duration: 3 Apr 20169 Apr 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9624 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing 2016
Country/TerritoryTurkey
CityKonya
Period3/04/169/04/16

Keywords

  • Doctor-patient communication
  • Hindi
  • Machine translation
  • Medical translation
  • Resource-poor languages

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