1887
Volume 9, Issue 1
  • ISSN 2211-3711
  • E-ISSN: 2211-372X
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Abstract

Abstract

This article contributes to the discussion on fairness and ethics in MT by highlighting efforts that have been made to use MT for the humanitarian purpose of increasing access to information for groups that are underserved. The article provides an overview of example projects in which MT has been implemented for this purpose in three contexts: civic participation, public health and safety, and media and culture. In addition, the article examines some of the ethical issues surrounding efforts to use MT for accessibility, including issues of quality, acceptability, and the need to involve stakeholders in development.

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2020-08-17
2020-09-26
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References

  1. Ansari, Aimee, and Rebecca Petras
    2018 “Gamayun: The Language Equality Initiative.” Translators Without Borders. Accessed15 October 2019, https://translatorswithoutborders.org/wp-content/uploads/2018/03/Gamayun-Language-Equality-Initiative-March-2018.pdf
    [Google Scholar]
  2. Aymerich, Julia, and Hermes Camelo
    2009 “The Machine Translation Maturity Model at PAHO.” InProceedings of the Twelfth Machine Translation Summit, 403–409.
    [Google Scholar]
  3. Biel, Łucja, and Vilelmini Sosoni
    2017 “The Translation of Economics and the Economics of Translation.” Perspectives25 (3): 351–361. doi:  10.1080/0907676X.2017.1313281
    https://doi.org/10.1080/0907676X.2017.1313281 [Google Scholar]
  4. Birch, Alexandra, Barry Haddow, Ivan Tito, Antonio Valerio Miceli Barone, Rachel Bawden, Felipe Sánchez-Martínez, Mikel L. Forcada, Miguel Esplà-Gomis, Víctor M. Sánchez-Cartagena, Juan Antonio Pérez-Ortiz, Wilker Aziz, Andrew Secker, and Peggy van der Kreeft
    2019 “Global Under-Resourced Media Translation (GoURMET).” InProceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks, 122. European Association for Machine Translation.
    [Google Scholar]
  5. Birch, Alexandra, Juliane Ried, Colin Davenport, Matthias Huck, and David Mareček
    2018 “D5.6: Report on Third Year’s Evaluation.” Health In My Language Project. www.himl.eu/files/D5.6_Final_Evaluation.pdf
    [Google Scholar]
  6. Blench, Michael
    2008 “Global Public Health Intelligence Network (GPHIN).” InEighth Conference of the Association for Machine Translation in the Americas.
    [Google Scholar]
  7. Bouillon, Pierrette, Johanna Gerlach, Hervé Spechbach, Nikos Tsourakis, and Sonia Halimi
    2017 “BabelDr vs Google Translate: A User Study at Geneva University Hospitals (HUG).” InThe 20th Annual Conference of the European Association for Machine Translation: User Studies and Project/Product Descriptions, 47–52.
    [Google Scholar]
  8. Bowker, Lynne
    2009 “Can Machine Translation Meet the Needs of Official Language Minority Communities in Canada? A Recipient Evaluation.” Linguistica Antverpiensia New Series-Themes in Translation Studies8: 123–155.
    [Google Scholar]
  9. Bowker, Lynne, and Jairo Buitrago Ciro
    2015 “Investigating the Usefulness of Machine Translation for Newcomers at the Public Library.” Translation and Interpreting Studies10 (2): 165–186. doi:  10.1075/tis.10.2.01bow
    https://doi.org/10.1075/tis.10.2.01bow [Google Scholar]
  10. Braeckman, Karel, Simon Debacq, Harri Kiiskinen, Nico Oorts, Lauri Saarikoski, Raphaël Troncy, Wim Van Lancker, Dieter Van Rijsselbergen, Maarten Verwaest, and Kim Viljanen
    2019 “D6.4 Specification of the Data Interchange Format, Intermediate Version.” MeMAD Project. https://memad.eu/wp-content/uploads/D6.4-Specification-of-the-data-interchange-format-intermediate-version-version-1.0.pdf
    [Google Scholar]
  11. Bywood, Lindsay, Panayota Georgakopoulou, and Thierry Etchegoyhen
    2017 “Embracing the Threat: Machine Translation as a Solution for Subtitling.” Perspectives: Studies in Translatology25 (3): 492–508. doi:  10.1080/0907676X.2017.1291695
    https://doi.org/10.1080/0907676X.2017.1291695 [Google Scholar]
  12. Carbonell, Jaime G., Alon Lavie, Lori Levin, and Alan W. Black
    2006 “Language Technologies for Humanitarian Aid.” InTechnology for Humanitarian Action, edited byKevin M. Cahill, 111–138. New York, USA: Fordham University Press & The Center for International Health and Cooperation.
    [Google Scholar]
  13. Castilho, Sheila, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley, and Andy Way
    2017 “Is Neural Machine Translation the New State of the Art?” The Prague Bulletin of Mathematical Linguistics108 (1): 109–120. doi:  10.1515/pralin‑2017‑0013
    https://doi.org/10.1515/pralin-2017-0013 [Google Scholar]
  14. Council of Europe
    Council of Europe 1950 “European Convention on Human Rights (European Convention for the Protection of Human Rights and Fundamental Freedoms, as Amended by Protocols Nos. 11 and 14).” Accessed20 February 2020, https://www.echr.coe.int/Documents/Convention_ENG.pdf
  15. Das, Prithwijit, Anna Kuznetsova, Meng’ou Zhu, and Ruth Milanaik
    2019 “Dangers of Machine Translation: The Need for Professionally Translated Anticipatory Guidance Resources for Limited English Proficiency Caregivers.” Clinical Pediatrics58 (2): 247–249. doi:  10.1177/0009922818809494
    https://doi.org/10.1177/0009922818809494 [Google Scholar]
  16. Dew, Kristin N., Anne M. Turner, Yong K. Choi, Alyssa Bosold, and Katrin Kirchhoff
    2018 “Development of Machine Translation Technology for Assisting Health Communication: A Systematic Review.” Journal of Biomedical Informatics85 (July): 56–67. doi:  10.1016/j.jbi.2018.07.018
    https://doi.org/10.1016/j.jbi.2018.07.018 [Google Scholar]
  17. European Commission
    European Commission 2010 “Translation at the European Commission – a History.” Luxembourg. doi:  10.2782/16417
    https://doi.org/10.2782/16417 [Google Scholar]
  18. European Commission
    European Commission 2012 “Special Eurobarometer 386: Europeans and Their Languages.” Accessed20 February 2020, https://ec.europa.eu/public_opinion/archives/ebs/ebs_386_en.pdf
  19. European Commission
    European Commission 2015 “Directive of the European Parliament and the Council on the approximation of the laws, regulations and administrative provisions of the Member States as regards the accessibility requirements for products and services.” Accessed20 February 2020, https://eur-lex.europa.eu/eli/dir/2019/882/oj
  20. Federici, Federico M. and Sharon O’Brien
    2020Translation in Cascading Crises. London: Routledge.
    [Google Scholar]
  21. García, Ignacio
    2011 “Translating by Post-Editing: Is It the Way Forward?” Machine Translation25 (3): 217–237. doi:  10.1007/s10590‑011‑9115‑8
    https://doi.org/10.1007/s10590-011-9115-8 [Google Scholar]
  22. Gazzola, Michele, and François Grin
    2013 “Is ELF More Effective and Fair than Translation? An Evaluation of the EU’s Multilingual Regime.” International Journal of Applied Linguistics23 (1): 93–107. doi:  10.1111/ijal.12014
    https://doi.org/10.1111/ijal.12014 [Google Scholar]
  23. Ghandour-Demiri, Nada
    2017 “Language & Comprehension Barriers in Greece’s Migration Crisis: A Study on the Multitude of Languages and Comprehension of Material Provided to Refugees and Migrants in Greece.” Translators without Borders and Save the Children. Accessed1st March 2020, https://resourcecentre.savethechildren.net/node/12449/pdf/language-comprehension-barriers.pdf
    [Google Scholar]
  24. Hu, Ke, and Patrick Cadwell
    2016 “A Comparative Study of Post-Editing Guidelines.” InProceedings of the 19th Annual Conference of the European Association for Machine Translation, EAMT 2016, 346–53.
    [Google Scholar]
  25. Hutchins, William John
    1986Machine Translation: Past, Present, Future. Chichester: Ellis Horwood.
    [Google Scholar]
  26. 2010 “Machine Translation: A Concise History.” Journal of Translation Studies. Special Issue: The Teaching of Computer-Aided Translation. 13 (1–2): 29–70.
    [Google Scholar]
  27. IEEE
    IEEE 2017 “Ethically Aligned Design: A Vision for Prioritizing Human Well-Being with Autonomous and Intelligent Systems.” The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems. https://ethicsinaction.ieee.org/#read
    [Google Scholar]
  28. Jönsson, Arne
    2016 “DigInclude – Digital Inclusion in the Networked Society for Groups with Special Needs (Proposal for Vinnova).” Reference accessed1st March 2020, https://liu.se/en/research/diginclude
  29. Kirchhoff, Katrin, Anne M. Turner, Amittai Axelrod, and Francisco Saavedra
    2011 “Application of Statistical Machine Translation to Public Health Information: A Feasibility Study.” Journal of the American Medical Informatics Association18 (4): 473–478. doi:  10.1136/amiajnl‑2011‑000176
    https://doi.org/10.1136/amiajnl-2011-000176 [Google Scholar]
  30. Koponen, Maarit, and Leena Salmi
    2015 “On the Correctness of Machine Translation: A Machine Translation Post-Editing Task.” Journal of Specialised Translation23: 118–36.
    [Google Scholar]
  31. Laurenzi, Adrian, Megumu Brownstein, Anne M. Turner, Julie A. Kientz, and Katrin Kirchhoff
    2013 “A Web-Based Collaborative Translation Management System for Public Health Workers.” InConference on Human Factors in Computing Systems – Proceedings, 511–516. doi:  10.1145/2468356.2468446
    https://doi.org/10.1145/2468356.2468446 [Google Scholar]
  32. Liu, Chao-Hong
    (ed) 2018 “(LoResMT 2018) Technologies for MT of Low Resource Languages 2018.” InThe 13th Conference of the Association for Machine Translation in the Americas, 1–62. Boston, Massachusetts, USA: Association for Machine Translation in the Americas.
    [Google Scholar]
  33. Liu, Chao-Hong, and Alina Karakanta
    (eds) 2019 “(LoResMT 2019) The Second Workshop on Technologies for MT of Low Resource Languages.” InMachine Translation Summit XVII, 1–77. Machine Translation Summit.
    [Google Scholar]
  34. Martindale, Marianna J., and Marine Carpuat
    2018 “Fluency Over Adequacy: A Pilot Study in Measuring User Trust in Imperfect MT.” InProceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Papers), 13–25.
    [Google Scholar]
  35. Martindale, Marianna, Marine Carpuat, Kevin Duh, and Paul McNamee
    2019 “Identifying Fluently Inadequate Output in Neural and Statistical Machine Translation.” InProceedings of Machine Translation Summit XVII Volume 1: Research Track, 233–243. European Association for Machine Translation.
    [Google Scholar]
  36. Matamala, Anna, Andreu Oliver, Aitor Álvarez, and Andoni Azpeitia
    2015 “The Reception of Intralingual and Interlingual Automatic Subtitling: An Exploratory Study within the HBB4ALL Project.” InProceedings of the 37th Conference Translating and the Computer, edited byJoão Esteves-Ferreira, Juliet Macan, Ruslan Mitkov, and Olaf-Michael Stefanov, 12–17. ASLING.
    [Google Scholar]
  37. Matamala, Anna, and Carla Ortiz-Boix
    2016 “Accessibility and Multilingualism: An Exploratory Study on the Machine Translation of Audio Descriptions.” Trans20: 11–24. doi:  10.24310/TRANS.2016.v0i20.2059
    https://doi.org/10.24310/TRANS.2016.v0i20.2059 [Google Scholar]
  38. Melby, Alan K., and C Terry Warner
    1995The Possibility of Language: A Discussion of the Nature of Language, with Implications for Human and Machine Translation. Amsterdam/Philadelphia: John Benjamins. 10.1075/btl.14
    https://doi.org/10.1075/btl.14 [Google Scholar]
  39. Melero, Maite, Antoni Oliver, and Toni Badia
    2006 “Automatic Multilingual Subtitling in the ETITLE Project.” InProceedings of Translating and the Computer28, 1–18.
    [Google Scholar]
  40. Miyata, Rei, Anthony Hartley, Cécile Paris, Midori Tatsumi, and Kyo Kageura
    2015 “Japanese Controlled Language Rules to Improve Machine Translatability of Municipal Documents.” InMT SummitXV, 90–103.
    [Google Scholar]
  41. Miyata, Rei, Anthony Hartley, Kyo Kageura, Cécile Paris, Masao Utiyama, and Sumita Eiichiro
    2016 “MuTUAL: A Controlled Authoring Support System Enabling Contextual Machine Translation.” InCOLING 2016, 35–39.
    [Google Scholar]
  42. O’Mathúna, Dónal, Carla Parra Escartín, Helena Moniz, Jay Marlowe, Matthew Hunt, Eric DeLuca, Federico Federici, and Sharon O’Brien
    2019 “Ethics Recommendations for Crisis Translation Settings.” INTERACT: The International Network in Crisis Translation.
    [Google Scholar]
  43. Ortiz-Boix, Carla, and Anna Matamala
    2017 “Assessing the Quality of Post-Edited Wildlife Documentaries.” Perspectives: Studies in Translatology25 (4): 571–593. doi:  10.1080/0907676X.2016.1245763
    https://doi.org/10.1080/0907676X.2016.1245763 [Google Scholar]
  44. Parra Escartín, Carla and Helena Moniz
    2020 “Ethical Considerations on the use of Machine Translation and Crowdsourcing in Cascading Crises.” InTranslation in Cascading Crises, edited byFederico M. Federici and Sharon O’Brien, 132–151. London: Routledge.
    [Google Scholar]
  45. Piperidis, Stelios, Iason Demiros, Prokopis Prokopidis, Peter Vanroose, Anja Hoethker, Walter Daelemans, Elsa Sklavounou, Manos Konstantinou, and Yannis Karavidas
    2004 “Multimodal Multilingual Resources in the Subtitling Process.” InFourth International Conference on Language Resources and Evaluation (LREC 2004). ELRA.
    [Google Scholar]
  46. Plitt, Mirko, and François Masselot
    2010 “A Productivity Test of Statistical Machine Translation Post-Editing in a Typical Localisation Context.” The Prague Bulletin of Mathematical Linguistics93: 7–16. doi:  10.2478/v10108‑010‑0010‑x
    https://doi.org/10.2478/v10108-010-0010-x [Google Scholar]
  47. Pouliquen, Bruno, Cecilia Elizalde, Marcin Junczys-Dowmunt, Christophe Mazene, and José Garcia-Verdugo
    2013 “Large-Scale Multiple Language Translation Accelerator at the United Nations.” InProceedings of the XIV Machine Translation Summit, 345–351.
    [Google Scholar]
  48. Somers, Harold
    1997 “Machine Translation and Minority Languages.” InTranslating and the Computer 19: Papers from the Aslib Conference Held on 13 & 14 November 1997, 1–13. Aslib.
    [Google Scholar]
  49. Tiilikka, Päivi
    2013 “Access to Information as a Human Right in the Case Law of the European Court of Human Rights.” Journal of Media Law5 (1): 79–103. doi:  10.5235/17577632.5.1.79
    https://doi.org/10.5235/17577632.5.1.79 [Google Scholar]
  50. Turner, Anne M., Margo Bergman, Megumu Brownstein, Kate Cole, and Katrin Kirchhoff
    2014 “A Comparison of Human and Machine Translation of Health Promotion Materials for Public Health Practice: Time, Costs, and Quality.” Journal of Public Health Management Practices20 (5): 523–29. https://pubmed.ncbi.nlm.nih.gov/24084391/. 10.1016/j.physbeh.2017.03.040
    https://doi.org/10.1016/j.physbeh.2017.03.040 [Google Scholar]
  51. Turner, Anne M., Yong K. Choi, Kristin Dew, Ming-Tse Tsai, Alyssa L. Bosold, Shuyang Wu, Donahue Smith, and Hendrika Meischke
    2019 “Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study.” JMIR Public Health and Surveillance5 (1): e11171. doi:  10.2196/11171
    https://doi.org/10.2196/11171 [Google Scholar]
  52. UNESCO Executive Board
    UNESCO Executive Board 2007 “Report by the Director-General on the Execution of the Programme Adopted by the General Conference: Intersectoral Mid-Term Strategy on Languages and Multilingualism.”
    [Google Scholar]
  53. United Nations
    United Nations 1948 “Universal Declaration of Human Rights.”
    [Google Scholar]
  54. Vasconcellos, Muriel, and Marjorie León
    1985 “SPANAM and ENGSPAN: Machine Translation at the Pan American Health Organization.” Computational Linguistics11 (2–3): 122–136.
    [Google Scholar]
  55. Vasiljevs, Andrejs, Rihards Kalnins, Marcis Pinnis, and Raivis Skadins
    2014 “Machine Translation for E-Government – the Baltic Case.” InProceedings of the 11th Conference of the Association for Machine Translation in the Americas, Vol. 2: MT Users Track, 181–193.
    [Google Scholar]
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