Abstract
Thanks to today’s technologies, the world’s borders have been fading away and intercultural collaboration has become easier and easier. Language and cultural differences are common problems in inter-cultural collaboration. Machine translation (MT) is now available to overcome the language barrier, so people can easily express and understand messages in different languages. However, misunderstandings often plague users from different cultures, especially in MT-mediated communication. To communicate productively, it is important to avoid such misunderstandings. One existing work proposed the idea of using automated cultural difference detection to warn the users of misunderstanding. However, no study has examined how such warnings affect the communication. To eliminate this gap, we conduct a controlled experiment on how users react to the warnings and what are the results in terms of communication. The results show that, with the data from cultural difference detection, warning the user of cultural misunderstanding can help reduce misunderstandings and increase awareness of cultural differences. The results of this experiment confirm the effectiveness of cultural misunderstanding alerts and suggest new directions in multilingual chat design.
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Notes
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Note that the translation output is likely to change from time to time since MT is always developing and the output also depends on the services selected.
References
Bailey, S.: Academic Writing: A Handbook for International Students. Taylor & Francis (2003). https://books.google.co.jp/books?id=SUeRAgAAQBAJ
Cho, H., Ishida, T., Yamashita, N., Inaba, R., Mori, Y., Koda, T.: Culturally-situated pictogram retrieval. In: Ishida, T., Fussell, S.R., Vossen, P.T.J.M. (eds.) IWIC 2007. LNCS, vol. 4568, pp. 221–235. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74000-1_17
Deutscher, G.: Through the Language Glass: Why the World Looks Different in Other Languages. Metropolitan Books, New York (2010)
Gookin, D.: Word 2013 For Dummies. For Dummies, Wiley (2013). https://books.google.co.jp/books?id=gxd6bMou76EC
Herring, C.: Does diversity pay?: race, gender, and the business case for diversity. Am. Sociol. Rev. 74(2), 208–224 (2009)
Hofstede, G.: Cultural dimensions in management and planning. Asia Pac. J. Manage. 1(2), 81–99 (1984)
Isahara, H., Bond, F., Uchimoto, K., Utiyama, M., Kanzaki, K.: Development of the Japanese wordnet. In: Sixth International Conference on Language Resources and Evaluation (2008)
Ishida, T., Murakami, Y., Lin, D., Nakaguchi, T., Otani, M.: Language service infrastructure on the web: the language grid. Computer 51(6), 72–81 (2018)
Kelley, J.F.: An iterative design methodology for user-friendly natural language office information applications. ACM Trans. Inf. Syst. (TOIS) 2(1), 26–41 (1984)
Lafferty, J.C., Pond, A.W.: The Desert Survival Situation: Problem: a Group Decision Making Experience for Examining and Increasing Individual and Team Effectiveness. Human Synergistics (1974)
Miller, G.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)
Nishimura, I., Murakami, Y., Pituxcoosuvarn, M.: Image-based detection criteria for cultural differences in translation. In: International Conference on Collaboration and Technology. Springer (2020)
Pituxcoosuvarn, M., Ishida, T.: Multilingual communication via best-balanced machine translation. New Gener. Comput. 36(4), 349–364 (2018)
Pituxcoosuvarn, M., Ishida, T., Yamashita, N., Takasaki, T., Mori, Y.: Machine translation usage in a children’s workshop. In: Egi, H., Yuizono, T., Baloian, N., Yoshino, T., Ichimura, S., Rodrigues, A. (eds.) CollabTech 2018. LNCS, vol. 11000, pp. 59–73. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98743-9_5
Pituxcoosuvarn, M., Lin, D., Ishida, T.: A method for automated detection of cultural difference based on image similarity. In: Nakanishi, H., Egi, H., Chounta, I.-A., Takada, H., Ichimura, S., Hoppe, U. (eds.) CRIWG+CollabTech 2019. LNCS, vol. 11677, pp. 129–143. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-28011-6_9
Yamashita, N., Inaba, R., Kuzuoka, H., Ishida, T.: Difficulties in establishing common ground in multiparty groups using machine translation. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 679–688. ACM (2009)
Yoshino, R., Hayashi, C.: An overview of cultural link analysis of national character. Behaviormetrika 29(2), 125–141 (2002)
Yoshino, T., Miyabe, M., Suwa, T.: A proposed cultural difference detection method using data from Japanese and Chinese wikipedia. In: 2015 International Conference on Culture and Computing (Culture Computing), pp. 159–166. IEEE (2015)
Acknowledgments
This research was partially supported by a Grant-in-Aid for Scientific Research (A) (17H00759, 2017–2020), a Grant-in-Aid for Scientific Research (B) (18H03341, 2018–2020), and a Grant-in-Aid Young Scientists (A) (17H04706, 2017–2020) from the Japan Society for the Promotion of Science (JSPS).
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Pituxcoosuvarn, M., Murakami, Y., Lin, D., Ishida, T. (2020). Effect of Cultural Misunderstanding Warning in MT-Mediated Communication. In: Nolte, A., Alvarez, C., Hishiyama, R., Chounta, IA., Rodríguez-Triana, M., Inoue, T. (eds) Collaboration Technologies and Social Computing . CollabTech 2020. Lecture Notes in Computer Science(), vol 12324. Springer, Cham. https://doi.org/10.1007/978-3-030-58157-2_8
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