Abstract
In an intercultural children collaboration using machine translation, the children of low-resource languages have difficulties in participating and engaging in conversations due to inaccuracy of machine translation for the low-resource languages. In order to facilitate and motivate speech for these children, we have focused on the facilitator’s utterances. To identify the facilitator’s speech patterns that encourage the responses of low-resource language speaking children, we need to annotate the actual conversation logs. However, the existing annotation scheme cannot be applied to facilitation utterances completely because it is a classification of speech patterns for general problem-solving purposes. In this study, we have identified the problems that occurred when applying the existing annotation schemes. In addition, we proposed and evaluated a new annotation rule of the existing annotation scheme for facilitation analysis.
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Acknowledgements
This research was partially supported by a Grant-in-Aid for Scientific Research (B) (21H03561, 2021–2024, 21H03556, 2021–2023) 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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Motozawa, M., Murakami, Y., Pituxcoosuvarn, M. (2022). Annotation References for Facilitation Analysis in Intercultural Collaboration. In: Rau, PL.P. (eds) Cross-Cultural Design. Applications in Business, Communication, Health, Well-being, and Inclusiveness. HCII 2022. Lecture Notes in Computer Science, vol 13313. Springer, Cham. https://doi.org/10.1007/978-3-031-06050-2_12
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