Designing a Data Corpus of Collaborative Group Tasks with the Members from Unbalanced Cultural Backgrounds

Kai-Yuan Ding, Hung-Hsuan Huang, Nicolas Berberich, Mineya Kaseda, K. Kuwabara, T. Nishida
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Abstract

According to current estimates, the population of Japan will continuously decrease to be less than 100 million from currently 126.4 million by 2053 [1]. In order to supplement the decreasing labor force, the Japanese government has stated to relax the regulations on introducing foreignworkers. Thus, an increase of foreignerworkers in Japanese society can be expected in the near future. In such a situation, foreigner workers are the minority and have to collaboratively work with Japanese colleagues who are the majority. Our project is aiming at developing an environment for both foreigner and Japanese people to practice collaborative work in an unbalanced situation, that is, Japanese people are the majority and the task itself is Japanese favored. This paper describes our design of an experiment to acquire multimodal sensory data in collaborative tasks with unbalanced composition of cultural backgrounds. These data are supposed to be used for developing foreigner / Japanese behavior generation / detection models in a training environment with virtual agents. From our knowledge, there is no such dataset available and we believe the data collected can provide valuable resources for developing tools in supporting unbalanced groups.
基于非平衡文化背景的协同小组任务数据库设计
根据目前的估计,到2053年,日本人口将从目前的1.264亿持续减少到不足1亿[1]。日本政府表示,为了补充日益减少的劳动力,将放宽引进外国工人的限制。因此,可以预见,在不久的将来,日本社会的外籍工人将会增加。在这种情况下,外籍员工是少数,必须与占多数的日本同事合作。我们的项目旨在创造一个外国人和日本人在不平衡的情况下进行协同工作的环境,即日本人占多数,任务本身是日本人喜欢的。本文描述了我们设计的一个实验,以获取多模态的感官数据在协作任务与不平衡的文化背景组成。这些数据应该用于在虚拟代理的训练环境中开发外国人/日本人的行为生成/检测模型。据我们所知,目前还没有这样的数据集,我们相信收集到的数据可以为开发支持不平衡群体的工具提供宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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