Abstract
Machine translation (MT) has become useful in intercultural collaboration. However, for low-resource language (LRL) speakers, the translation accuracy possible might still be a burden to them. Previous studies showed that it is difficult for the minority and LRL speakers to participate in conversions. To solve this problem and create equal chance for team members to communicate, we aim at creating a facilitator agent that helps in supporting the LRL speakers or team members who might have problems joining the conversation. We achieve this by proposing the concept of a virtual facilitation agent that responds to and puts questions to the team members to support the discussion. Experiments on different facilitation strategies for discussion groups are conducted using our multilingual chat system.
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Acknowledgements
This research is partially supported by a Grant-in-Aid for Scientific Research (A) (17H00759, 2017–2020), a Grant-in-Aid for Scientific Research (B) (21H03561, 2021–2024) and a Grant-in-Aid for Early-Career Scientists (21K17794, 2021–2024) from the Japan Society for the Promotion of Sciences (JSPS).
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Pituxcoosuvarn, M., Motozawa, M., Murakami, Y., Yokote, S. (2022). Facilitator Agent to Support Low-Resource Language Speakers in MT-Mediated Communication. In: Wong, LH., Hayashi, Y., Collazos, C.A., Alvarez, C., Zurita, G., Baloian, N. (eds) Collaboration Technologies and Social Computing. CollabTech 2022. Lecture Notes in Computer Science, vol 13632. Springer, Cham. https://doi.org/10.1007/978-3-031-20218-6_16
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DOI: https://doi.org/10.1007/978-3-031-20218-6_16
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