Skip to main content
SpringerLink
Log in

Multilingual Communication via Best-Balanced Machine Translation

  • Research Paper
  • Published:
New Generation Computing Aims and scope Submit manuscript

Abstract

It is known that creative ideas are often generated by correspondents from different cultures, but it remains true that distance still matters due to the language barrier. To enhance multilingual communication, this paper proposes the model of best-balanced machine translation. Our model is based on the quality of messages among participants (assumed to have different levels of language skill) and takes not only machine translation quality but also users’ language skill into account. We provide a method to select languages to be used with machine translators, and a way of creating the best-balanced communication environment. Many studies have addressed machine translation with the goal of helping the non-native speaker to understand what was said. Our approach is totally differently, since we focus on helping the non-native speaker by enhancing the opportunity to join in the conversation. We conduct an experiment and find that this model allows machine translation technologies to benefit multilingual communication while making best use of the participants’ different language skills. The proposed model addresses the talkativeness of the participants. It also improves communication by reducing serious machine translation errors and the number of conversation breakdowns.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Ishida, T.: Intercultural collaboration and support systems: a brief history. In: International conference on principles and practice of multi-agent systems. Springer International Publishing, Phuket. pp. 3–19, (2016) https://doi.org/10.1007/978-3-319-44832-9_1

    Chapter  Google Scholar 

  2. David, C.: English as a global language. Cambridge University Press, Cambridge (1997)

    Google Scholar 

  3. Henderson, J.K.: Language diversity in international management teams. Int. Stud. Manag. Organ. 35, 66–82 (2005)

    Google Scholar 

  4. Morita, D., Ishida, T.: Collaborative translation by monolinguals with machine translators. In: 14th international Conference on Intelligent User Interfaces (IUI ‘09), pp. 361–366. ACM, New York (2009) https://doi.org/10.1145/1502650.1502701

  5. Yamashita, N., Echenique, A., Ishida, T., Hautasaari, A.: Lost in transmittance: how transmission lag enhances and deteriorates multilingual collaboration. In: 16th ACM Conference on computer supported cooperative work and social computing (CSCW 2013), pp. 923–934. ACM, Texas (2013) https://doi.org/10.1145/2441776.2441881

  6. Gao, G., Yamashita, N., Hautasaari A.M., Fussell, S.R.: Improving multilingual collaboration by displaying how non-native speakers use automated transcripts and bilingual dictionaries. In: 33rd Annual ACM Conf. on human factors in computing systems, pp. 3463–3472. ACM, Seoul (2015) https://doi.org/10.1145/2702123.2702498

  7. Toyama, T., Sonntag, D., Dengel, A., Matsuda, T., Iwamura, M., Kise, K.: A mixed reality head-mounted text translation system using eye gaze input. In: 15th International Conference on intelligent user interfaces (IUI ‘10), pp. 329–334, ACM, Haifa (2014) https://doi.org/10.1145/2557500.2557528

  8. Aiken, M.: Transterpreting multilingual electronic meetings. Int. J. Manag. Inf. Syst. 13(1), 35–46 (2009). https://doi.org/10.19030/ijmis.v13i1.4940

    Article  MathSciNet  Google Scholar 

  9. Fellbaum, C.: WordNet. Theory and applications of ontology: computer applications, pp. 231–234. Springer, Dordrecht (2010). https://doi.org/10.1007/978-90-481-8847-5_10

    Book  Google Scholar 

  10. Yamashita, N., Ishida, T.: Effects of machine translation on collaborative work. In: computer supported cooperative work and social computing 2006 (CSCW 2006), pp. 515–524. ACM, Alberta (2006) https://doi.org/10.1145/1180875.1180955

  11. Morita, D., Ishida, T.: Collaborative translation by monolinguals with machine translators. Procs. 14th IUI, pp. 361–366 (2009)

  12. Bramantoro, A., Ishida, T.: User-centered QoS in combining web services for interactive domain. In: 5th International Conference on semantics, knowledge and grid, pp. 41–48. IEEE Press, Guangdong (2009) https://doi.org/10.1109/skg.2009.106

  13. Lafferty, J.C, Eady, P.M., Elmers, J.: The desert survival problem. Exp. Learn. Methods Michigan (1974)

  14. Fermilab Project ARISE. http://ed.fnal.gov/arise/guide.html

  15. NASA. http://www.nasa.gov/audience/foreducators/5-8/features/F_Exploration_Then_and_Now.html

  16. Ishida, T.: The language grid: service-oriented collective intelligence for language resource interoperability. Springer Science & Business Media, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21178-2_1

    Book  Google Scholar 

  17. Cambridge Assessment. http://www.cambridgeenglish.org/exams-and-tests/cefr/

  18. ETS. https://www.ets.org/toefl/institutions/scores/compare/

  19. Callison-Burch, C., Fordyce, C., Koehn, P., Monz, C., and Schroeder, J.: (Meta-)evaluation of machine translation. In: 2nd Workshop on statistical machine translation, pp. 136–158. ACM, Prague (2007) https://doi.org/10.3115/1626394.1626403

  20. Linguistic Data Consortium: Linguistic data annotation specification: assessment of fluency and adequacy in translations. Tech. Rep. (2005)

Download references

Acknowledgements

This research was partially supported by a Grant-in-Aid for Scientific Research (S) (24220002, 2012–2016) from Japan Society for the Promotion of Science (JSPS), and the Leading Graduates Schools Program, “Collaborative Graduate Program in Design” by the Ministry of Education, Culture, Sports, Science and Technology, Japan.

Author information

Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Yoshidahonmachi, Sakyo Ward, Kyoto, Kyoto Prefecture, Japan

    Mondheera Pituxcoosuvarn & Toru Ishida

Authors
  1. Mondheera Pituxcoosuvarn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Toru Ishida
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mondheera Pituxcoosuvarn.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pituxcoosuvarn, M., Ishida, T. Multilingual Communication via Best-Balanced Machine Translation. New Gener. Comput. 36, 349–364 (2018). https://doi.org/10.1007/s00354-018-0041-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00354-018-0041-7

Keywords

Search

Navigation