TY - GEN
T1 - Generating Natural Language Responses in Robot-Mediated Referential Communication Tasks to Simulate Theory of Mind
AU - Liu, Ziming
AU - Qin, Yigang
AU - Zou, Huiqi
AU - Paek, Eun Jin
AU - Casenhiser, Devin
AU - Zhou, Wenjun
AU - Zhao, Xiaopeng
N1 - Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).
PY - 2022/12
Y1 - 2022/12
N2 - With advances in neural network-based computation, socially assistive robots have been endowed with the ability to provide natural conversation to users. However, the lack of transparency in the computation models results in unexpected robot behaviors and feedback, which may cause users to lose their trust in the robot. Theory of mind (ToM) in cooperative tasks has been considered as a key factor in understanding the relationship between user acceptance and the explainability of robot behaviors. Therefore, we develop a dialog system using previously collected data from a robot-mediated cooperative communication task data to simulate natural language smart feedback. The system is designed based on the mechanism of ToM and validated with a simulation test. Based on the result, we believe the designed dialog system bears the feasibility of simulating ToM and can be used as a research tool for further studying the importance of simulating ToM in human-robot communication. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
AB - With advances in neural network-based computation, socially assistive robots have been endowed with the ability to provide natural conversation to users. However, the lack of transparency in the computation models results in unexpected robot behaviors and feedback, which may cause users to lose their trust in the robot. Theory of mind (ToM) in cooperative tasks has been considered as a key factor in understanding the relationship between user acceptance and the explainability of robot behaviors. Therefore, we develop a dialog system using previously collected data from a robot-mediated cooperative communication task data to simulate natural language smart feedback. The system is designed based on the mechanism of ToM and validated with a simulation test. Based on the result, we believe the designed dialog system bears the feasibility of simulating ToM and can be used as a research tool for further studying the importance of simulating ToM in human-robot communication. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
KW - Human robot interaction
KW - Natural language processing
KW - Theory of mind
UR - http://www.scopus.com/inward/record.url?scp=85149828652&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85149828652&origin=recordpage
U2 - 10.1007/978-3-031-24667-8_9
DO - 10.1007/978-3-031-24667-8_9
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-3-031-24666-1
T3 - Lecture Notes in Artificial Intelligence (including subseries Lecture Notes in Computer Science)
SP - 100
EP - 109
BT - Social Robotics
A2 - Cavallo, Filippo
A2 - Cabibihan, John-John
A2 - Fiorini, Laura
A2 - Sorrentino, Alessandra
A2 - He, Hongsheng
A2 - Liu, Xiaorui
A2 - Matsumoto, Yoshio
A2 - Ge, Shuzhi Sam
PB - Springer
CY - Cham
T2 - 14th International Conference on Social Robotics (ICSR 2022)
Y2 - 13 December 2022 through 16 December 2022
ER -