Designing Protocols for Collaborative Translation

  • Daisuke Morita
  • Toru Ishida
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5925)


In this paper, we present a protocol for collaborative translation, where two non-bilingual people who use different languages collaborate to perform the task of translation using machine translation (MT) services. Members in one real life example of intercultural collaboration try to share information more effectively by modifying unnatural machine translated sentences manually and improving their fluency. However, there are two problems with this method: One is that poor quality of translation can induce misinterpretations, and the other is that phrases in the machine translated sentence that a person cannot make sense of remain unmodified. The proposed protocol is designed to solve these problems. More concretely, one person, who handles the source language and knows the original sentence (source language side), evaluates the adequacy between the original sentence and the translation of the sentence modified to be fluent by the other person, who handles the target language (target language side). In addition, by determining whether the meaning of the machine translated sentence is understandable, it is ensured that the two non-bilingual people do above tasks properly. As a result, this protocol 1) improves MT quality; and 2) terminates successfully only when the translation result becomes adequate and fluent. The experiment results show that when the protocol terminates successfully, the quality of the translation increases to about 83 percent in Japanese-English translation and 91 percent in Japanese-Chinese translation.


Machine Translation Design Protocol Native English Speaker Translation Result English Sentence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [Aiken 02]
    Aiken, M.: Multilingual communication in electronic meetings. ACM SIGGROUP Bulletin 23(1), 18–19 (2002)Google Scholar
  2. [Aiken 94]
    Aiken, M., Hwang, C., Paolillo, J., Lu, L.: A group decision support system for the asian pacific rim. Journal of International Information Management 3, 1–13 (1994)Google Scholar
  3. [Clark 91]
    Clark, H.H., Brennan, S.E.: Grounding in communication. In: Resnick, L.B., Levine, R.M., Teasley, S.D. (eds.) Perspectives on socially shared cognition, American Psychological Association, Washington, DC (1991)Google Scholar
  4. [Clark 81]
    Clark, H.H., Marshall, C.E.: Definite reference and mutual knowledge. Elements of discourse understanding, 10–63 (1981)Google Scholar
  5. [Clark 86]
    Clark, H.H., Wilkes-Gibbs, D.: Referring as a collaborative process. In: Cognition, pp. 1–39 (1986)Google Scholar
  6. [Halpern 90]
    Halpern, Y.J., Moses, Y.: Knowledge and Common Knowledge in a Distributed Environment. Journal of the ACM 37(3), 549–587 (1990)zbMATHCrossRefMathSciNetGoogle Scholar
  7. [Isaacs 87]
    Isaacs, E.A., Clark, H.H.: References in conversation between experts and novices. Journal of Experimental Psychology: General 16(1), 26–27 (1987)CrossRefGoogle Scholar
  8. [Ishida 06]
    Ishida, T.: Language grid: An infrastructure for intercultural collaboration. In: IEEE/IPSJ Symposium on Applications and the Internet (SAINT 2006), pp. 96–100 (2006)Google Scholar
  9. [Kim 02]
    Kim, K.J., Bonk, C.J.: Cross-cultural comparisons of online collaboration. Journal of Computer Mediated Communication 8(1) (2002)Google Scholar
  10. [Krauss 64]
    Krauss, R.M., Weinheimer, S.: Changes in reference phases as a function of frequency of usage in social interaction: A preliminary study. Psychonomic Science 1, 113–114 (1964)Google Scholar
  11. [Nomura 03]
    Nomura, S., Ishida, T., Yamashita, N., Yasuoka, M., Funakoshi, K.: Open source software development with your mother language: Intercultural collaboration experiment 2002. In: International Conference on Human-Computer Interaction (HCI 2003), vol. 4, pp. 1163–1167 (2003)Google Scholar
  12. [Ogden 03]
    Ogden, B., Warner, J., Jin, W., Sorge, J.: Information sharing across languages using mitre’s trim instant messaging (2003)Google Scholar
  13. [Takano 93]
    Takano, Y., Noda, A.: A temporary decline of thinking ability during foreign language processing. Journal of Corss-Cultural Psychology 24(4), 445–462 (1993)CrossRefGoogle Scholar
  14. [Tung 02]
    Tung, L.L., Quaddus, M.A.: Cultural differences explaining the differences in results in gss: implications for the next decade. Decision Support Systems 33(2), 177–199 (2002)CrossRefGoogle Scholar
  15. [Yamashita 06]
    Yamashita, N., Ishida, T.: Effects of machine translation on collaborative work. In: International Conference on Computer Supported Cooperative Work (CSCW 2006), pp. 512–523 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Daisuke Morita
    • 1
  • Toru Ishida
    • 1
  1. 1.Department of Social InformaticsKyoto UniversityKyotoJapan

Personalised recommendations