Designing chatbots that produce language that is natural and appropriate to a given context is critical in satisfying user expectations. Currently, little is known about how a chatbot's linguistic choices should be designed to conform with the language humans produce in similar contexts. In this paper, we draw on existing sociolinguistic theory to adapt a technique calledregister analysis to (a) characterize the linguistic register used by humans in a specific conversational context; and (b) drive chatbot language design. Our exploratory study investigates the application of register analysis for tourist assistants chatbots and shows how the results could be used to develop them to adopt the appropriate register.
{"title":"It's How You Say It: Identifying Appropriate Register for Chatbot Language Design","authors":"A. Chaves, E. Doerry, Jesse Egbert, M. Gerosa","doi":"10.1145/3349537.3351901","DOIUrl":"https://doi.org/10.1145/3349537.3351901","url":null,"abstract":"Designing chatbots that produce language that is natural and appropriate to a given context is critical in satisfying user expectations. Currently, little is known about how a chatbot's linguistic choices should be designed to conform with the language humans produce in similar contexts. In this paper, we draw on existing sociolinguistic theory to adapt a technique calledregister analysis to (a) characterize the linguistic register used by humans in a specific conversational context; and (b) drive chatbot language design. Our exploratory study investigates the application of register analysis for tourist assistants chatbots and shows how the results could be used to develop them to adopt the appropriate register.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126597635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Masaya Iwasaki, Jian Zhou, M. Ikeda, Yuya Onishi, T. Kawamura, Hideyuki Nakanishi
Robotic salespersons have been adopted by many shops. However, due to the weakness of their social presence, they are easily ignored by visitors. Thus, we focused on such robots' behaviors that can strengthen their social presence in a real-world shop. In this research, our goal is to develop a model that can obtain visitors' replies to the robot's utterances. For this reason, we conducted a laboratory experiment and two field experiments. In the laboratory experiment, we found that the robot's ability to express that it can understand the degree of visitors' attention to the robot is important for improving its social presence. Afterward, we developed an engagement estimation model (EEM) based on the findings obtained from the laboratory experiment. We defined visitors' engagement as the probability that the visitors will reply to the robot's utterances. The EEM estimates the engagement from the visitors' real-time nonverbal data. In a laboratory experiment, the situation of being in the laboratory can make the interaction between the participants and the robot unnatural. Therefore, we developed a model based on data of visitors' nonverbal cues in the field experiment and examined whether the model works effectively in the real-world environment. As a result, the automatic greeting mode based on the EEM facilitated the participant's reply to the robot. Thus, we considered that this is because the automatic greeting mode could make a decision of the robot's next behavior precisely. It can be considered that the visitors may feel as if the robot could understand their degree of attention to the robot when the robot greets the visitors based on the automatic greeting mode. Therefore, the automatic greeting mode based on the EEM worked effectively in a real-world environment and could strengthen its social presence.
{"title":"Acting as if Being Aware of Visitors' Attention Strengthens a Robotic Salesperson's Social Presence","authors":"Masaya Iwasaki, Jian Zhou, M. Ikeda, Yuya Onishi, T. Kawamura, Hideyuki Nakanishi","doi":"10.1145/3349537.3351893","DOIUrl":"https://doi.org/10.1145/3349537.3351893","url":null,"abstract":"Robotic salespersons have been adopted by many shops. However, due to the weakness of their social presence, they are easily ignored by visitors. Thus, we focused on such robots' behaviors that can strengthen their social presence in a real-world shop. In this research, our goal is to develop a model that can obtain visitors' replies to the robot's utterances. For this reason, we conducted a laboratory experiment and two field experiments. In the laboratory experiment, we found that the robot's ability to express that it can understand the degree of visitors' attention to the robot is important for improving its social presence. Afterward, we developed an engagement estimation model (EEM) based on the findings obtained from the laboratory experiment. We defined visitors' engagement as the probability that the visitors will reply to the robot's utterances. The EEM estimates the engagement from the visitors' real-time nonverbal data. In a laboratory experiment, the situation of being in the laboratory can make the interaction between the participants and the robot unnatural. Therefore, we developed a model based on data of visitors' nonverbal cues in the field experiment and examined whether the model works effectively in the real-world environment. As a result, the automatic greeting mode based on the EEM facilitated the participant's reply to the robot. Thus, we considered that this is because the automatic greeting mode could make a decision of the robot's next behavior precisely. It can be considered that the visitors may feel as if the robot could understand their degree of attention to the robot when the robot greets the visitors based on the automatic greeting mode. Therefore, the automatic greeting mode based on the EEM worked effectively in a real-world environment and could strengthen its social presence.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134149390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kazuhiro Mitsukuni, Jun Ichikawa, Yukari Hori, Y. Ikeno, Leblanc Alexandre, T. Kawamoto, N. Oka, Yukiko Nishizaki
Authors have conducted an observation experiment mainly on conversational play for creating the basic findings of childcare support by smart speakers. Our previous study analyzed children's attitudes and behaviors toward an utterance-output device during conversational play. In this experiment, the mother was beside her child, and the influence of the mother on the conversational play seemed to be great, but we have not been analyzed it yet. In this study, we analyzed the relationships between traits and behaviors of mothers, and children's conversational play. The results suggest that the more epistemic curiosity mothers are, the more children follow the instruction of an utterance-output device as third person, and that the more mothers prompt the conversational play toward their children, the less they react to phrases of the utterance-output device.
{"title":"Analysis of the Influence of Mothers' Traits and Behaviors on Children's Conversational Play with an Utterance-Output Device","authors":"Kazuhiro Mitsukuni, Jun Ichikawa, Yukari Hori, Y. Ikeno, Leblanc Alexandre, T. Kawamoto, N. Oka, Yukiko Nishizaki","doi":"10.1145/3349537.3352789","DOIUrl":"https://doi.org/10.1145/3349537.3352789","url":null,"abstract":"Authors have conducted an observation experiment mainly on conversational play for creating the basic findings of childcare support by smart speakers. Our previous study analyzed children's attitudes and behaviors toward an utterance-output device during conversational play. In this experiment, the mother was beside her child, and the influence of the mother on the conversational play seemed to be great, but we have not been analyzed it yet. In this study, we analyzed the relationships between traits and behaviors of mothers, and children's conversational play. The results suggest that the more epistemic curiosity mothers are, the more children follow the instruction of an utterance-output device as third person, and that the more mothers prompt the conversational play toward their children, the less they react to phrases of the utterance-output device.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115712293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, there has been a focus on educational support robots. In previous studies, robots providing educational support, based on cognitive apprenticeship theory, were reportedly effective in collaborative learning with learners. However, the robots were remote controlled. So no behavioral model was constructed of robots operating autonomously to provide educational support. Therefore, in this paper, we construct a behavioral model in which robots autonomously provide educational support based on the cognitive apprenticeship theory. In addition, through a comparative experiment with a behavioral model providing educational support in accordance with leaner requests, which is a conventional technique, we verify the effects of this behavioral model on university students.
{"title":"Construction of a Behavioral Model Based on Cognitive Apprenticeship Theory with an Educational Support Robot","authors":"Ryo Yoshizawa, Felix Jimenez, K. Murakami","doi":"10.1145/3349537.3352781","DOIUrl":"https://doi.org/10.1145/3349537.3352781","url":null,"abstract":"In recent years, there has been a focus on educational support robots. In previous studies, robots providing educational support, based on cognitive apprenticeship theory, were reportedly effective in collaborative learning with learners. However, the robots were remote controlled. So no behavioral model was constructed of robots operating autonomously to provide educational support. Therefore, in this paper, we construct a behavioral model in which robots autonomously provide educational support based on the cognitive apprenticeship theory. In addition, through a comparative experiment with a behavioral model providing educational support in accordance with leaner requests, which is a conventional technique, we verify the effects of this behavioral model on university students.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115840922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
How do we interact with mechanical systems such as PC, smartphone and so on? Users command something to the system, and the system always accepts and reacts it. That kind of relationship can be named "leader-follower" relationship. On the other hand, thinking about a scene that you have a walk in a park with your partner, there are neither a definite leader nor a follower. You and your partner co-adjust the walking direction and pace by considering each other's intention and feeling from implicit cues. Such relationship has "intersubjectivity" that people share their feeling and intention with others. This study is motivated to build "intersubjective relationship" between human and robot. In this paper, we propose the concept of a side-by-side walking robot "Mako-no-te".
{"title":"Mako-no-te: Investigating Intersubjectivity with Side-by-Side Walking Robot","authors":"Komei Hasegawa, M. Okada","doi":"10.1145/3349537.3352770","DOIUrl":"https://doi.org/10.1145/3349537.3352770","url":null,"abstract":"How do we interact with mechanical systems such as PC, smartphone and so on? Users command something to the system, and the system always accepts and reacts it. That kind of relationship can be named \"leader-follower\" relationship. On the other hand, thinking about a scene that you have a walk in a park with your partner, there are neither a definite leader nor a follower. You and your partner co-adjust the walking direction and pace by considering each other's intention and feeling from implicit cues. Such relationship has \"intersubjectivity\" that people share their feeling and intention with others. This study is motivated to build \"intersubjective relationship\" between human and robot. In this paper, we propose the concept of a side-by-side walking robot \"Mako-no-te\".","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115448697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jacqueline Urakami, B. A. Moore, Sujitra Sutthithatip, Sung Park
The goal of this study was to examine usertextquoteright s perception of expressions of empathy by an autonomous system. In a survey eight different components of empathy identified in literature studies and prior tests (Expressing own feelings, Expressing to know what the other feels, Helping, Showing interest, Taking the others perspective, Displaying regard, Situational understanding, and Agreement) were compared to neutral expressions. Differences in participants evaluations were found across the components of empathy as well as individual differences were revealed. Expressions of cognitive empathy (Showing interest, situational understanding) and expressions of empathy of assistance (helping) were perceived positively by participants. However, expressions of affective empathy (expressing own feelings, expressing to know what the other feels) received mainly negative ratings. Cluster analysis revealed individual differences especially for items relating to affective empathy. Whereas one group of participants identified in the cluster analysis rated expressions of affective empathy negatively, a second group of participants rated these expressions positively. Furthermore, large differences across participants also existed for taking the other's perspective, a component of cognitive empathy. Integrating expressions of empathy in human-machine interaction is a sensitive issue and designers must carefully choose what components of empathy are adequate depending on the situational circumstances and the targeted user group.
{"title":"Users' Perception of Empathic Expressions by an Advanced Intelligent System","authors":"Jacqueline Urakami, B. A. Moore, Sujitra Sutthithatip, Sung Park","doi":"10.1145/3349537.3351895","DOIUrl":"https://doi.org/10.1145/3349537.3351895","url":null,"abstract":"The goal of this study was to examine usertextquoteright s perception of expressions of empathy by an autonomous system. In a survey eight different components of empathy identified in literature studies and prior tests (Expressing own feelings, Expressing to know what the other feels, Helping, Showing interest, Taking the others perspective, Displaying regard, Situational understanding, and Agreement) were compared to neutral expressions. Differences in participants evaluations were found across the components of empathy as well as individual differences were revealed. Expressions of cognitive empathy (Showing interest, situational understanding) and expressions of empathy of assistance (helping) were perceived positively by participants. However, expressions of affective empathy (expressing own feelings, expressing to know what the other feels) received mainly negative ratings. Cluster analysis revealed individual differences especially for items relating to affective empathy. Whereas one group of participants identified in the cluster analysis rated expressions of affective empathy negatively, a second group of participants rated these expressions positively. Furthermore, large differences across participants also existed for taking the other's perspective, a component of cognitive empathy. Integrating expressions of empathy in human-machine interaction is a sensitive issue and designers must carefully choose what components of empathy are adequate depending on the situational circumstances and the targeted user group.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128192963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Personality of Artificial Intelligence (A.I) is a vast and complex domain. Traits like trustworthiness and humanness have long been evaluated, but less so for traits like fun. In this study we evaluate fun in four conversational agents with a mix of menial tasks, games, and free play in the US and India on voice and text-based platforms. Our research explores user sentiment of fun in an A.I. personality, implications of fun personality on voice-based and text-based agents, and the perception of a fun A.I. personality in two culturally distinct markets. We used a mixed method approach to evaluate these objectives with 44 participants. Our results end with design principles for creating fun in artificial intelligence: 1) balance fun through conversational humor and goal-oriented actions, 2) create fun experiences through playful interactions, 3) convey fun through platform specific expressions like tone of voice or visual gestures and emojis, and 4) be inclusively fun by being culturally relevant so your conversational agent translates across borders.
{"title":"Are We Having Fun Yet?: Designing for Fun in Artificial Intelligence That Is Multicultural and Multiplatform","authors":"Jennifer Zamora","doi":"10.1145/3349537.3352767","DOIUrl":"https://doi.org/10.1145/3349537.3352767","url":null,"abstract":"Personality of Artificial Intelligence (A.I) is a vast and complex domain. Traits like trustworthiness and humanness have long been evaluated, but less so for traits like fun. In this study we evaluate fun in four conversational agents with a mix of menial tasks, games, and free play in the US and India on voice and text-based platforms. Our research explores user sentiment of fun in an A.I. personality, implications of fun personality on voice-based and text-based agents, and the perception of a fun A.I. personality in two culturally distinct markets. We used a mixed method approach to evaluate these objectives with 44 participants. Our results end with design principles for creating fun in artificial intelligence: 1) balance fun through conversational humor and goal-oriented actions, 2) create fun experiences through playful interactions, 3) convey fun through platform specific expressions like tone of voice or visual gestures and emojis, and 4) be inclusively fun by being culturally relevant so your conversational agent translates across borders.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114325394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we verify whether an agent's internal state of desire can be expressed by combining the agent's visible behavior and tactile heartbeat as an involuntary physiological phenomenon. The results of the experiment confirmed that the agent's desires related to food are expressed by both heartbeat and behavior, furthermore, their combination expresses a strong desire. On the other hand, "being interested," the initial state of desire, and "being patient," internal suppression, both appear in the heartbeat but not in visual behaviors.
{"title":"Agent's Desire State Expression by Combining Tactile Heartbeat and Visible Behaviors","authors":"Naoto Yoshida, Kaede Ueno, Tomoko Yonezawa","doi":"10.1145/3349537.3352773","DOIUrl":"https://doi.org/10.1145/3349537.3352773","url":null,"abstract":"In this paper, we verify whether an agent's internal state of desire can be expressed by combining the agent's visible behavior and tactile heartbeat as an involuntary physiological phenomenon. The results of the experiment confirmed that the agent's desires related to food are expressed by both heartbeat and behavior, furthermore, their combination expresses a strong desire. On the other hand, \"being interested,\" the initial state of desire, and \"being patient,\" internal suppression, both appear in the heartbeat but not in visual behaviors.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134121916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Himangshu Saikia, Fangkai Yang, Christopher E. Peters
Goal directed agent navigation in crowd simulations involves a complex decision making process. An agent must avoid all collisions with static or dynamic obstacles (such as other agents) and keep a trajectory faithful to its target at the same time. This seemingly global optimization problem can be broken down into smaller local optimization problems by looking at a concept of criticality. Our method resolves critical agents - agents that are likely to come within collision range of each other - in order of priority using a Particle Swarm Optimization scheme. The resolution involves altering the velocities of agents to avoid criticality. Results from our method show that the navigation problem can be solved in several important test cases with minimal number of collisions and minimal deviation to the target direction. We prove the efficiency and correctness of our method by comparing it to four other well-known algorithms, and performing evaluations on them based on various quality measures.
{"title":"Criticality-based Collision Avoidance Prioritization for Crowd Navigation","authors":"Himangshu Saikia, Fangkai Yang, Christopher E. Peters","doi":"10.1145/3349537.3351887","DOIUrl":"https://doi.org/10.1145/3349537.3351887","url":null,"abstract":"Goal directed agent navigation in crowd simulations involves a complex decision making process. An agent must avoid all collisions with static or dynamic obstacles (such as other agents) and keep a trajectory faithful to its target at the same time. This seemingly global optimization problem can be broken down into smaller local optimization problems by looking at a concept of criticality. Our method resolves critical agents - agents that are likely to come within collision range of each other - in order of priority using a Particle Swarm Optimization scheme. The resolution involves altering the velocities of agents to avoid criticality. Results from our method show that the navigation problem can be solved in several important test cases with minimal number of collisions and minimal deviation to the target direction. We prove the efficiency and correctness of our method by comparing it to four other well-known algorithms, and performing evaluations on them based on various quality measures.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131247991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kai-Yuan Ding, Hung-Hsuan Huang, Nicolas Berberich, Mineya Kaseda, K. Kuwabara, T. Nishida
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.
{"title":"Designing a Data Corpus of Collaborative Group Tasks with the Members from Unbalanced Cultural Backgrounds","authors":"Kai-Yuan Ding, Hung-Hsuan Huang, Nicolas Berberich, Mineya Kaseda, K. Kuwabara, T. Nishida","doi":"10.1145/3349537.3352807","DOIUrl":"https://doi.org/10.1145/3349537.3352807","url":null,"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.","PeriodicalId":188834,"journal":{"name":"Proceedings of the 7th International Conference on Human-Agent Interaction","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133584778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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