TY - GEN
T1 - What Should Autonomous Robots Verbalize and What Should They Not?
AU - Yoshihara, Daichi
AU - Yuguchi, Akishige
AU - Kawano, Seiya
AU - Iio, Takamasa
AU - Yoshino, Koichiro
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - Empowered by the development of multimodal information processing and large language model-related technologies, robots that can operate autonomously in human living spaces are being realized. When such robots communicate with human users, they need a framework to appropriately select what to say to the user among the recognition results, memories, and decisions obtained from various multimodal environments. In this study, we constructed a framework that enables robots to appropriately select events to be verbalized by calculating the mutual information between the robot’s verbalization texts and its own memory or common sense knowledge. User evaluation results using crowdsourcing suggested that the proposed framework improves the necessity and sufficiency of the robot’s speech. This ability will contribute to improving the usability of the robot.
AB - Empowered by the development of multimodal information processing and large language model-related technologies, robots that can operate autonomously in human living spaces are being realized. When such robots communicate with human users, they need a framework to appropriately select what to say to the user among the recognition results, memories, and decisions obtained from various multimodal environments. In this study, we constructed a framework that enables robots to appropriately select events to be verbalized by calculating the mutual information between the robot’s verbalization texts and its own memory or common sense knowledge. User evaluation results using crowdsourcing suggested that the proposed framework improves the necessity and sufficiency of the robot’s speech. This ability will contribute to improving the usability of the robot.
KW - Autonomous robot
KW - human-robot interaction
KW - multimodal information processing
KW - verbalization
UR - http://www.scopus.com/inward/record.url?scp=85215985308&partnerID=8YFLogxK
U2 - 10.1007/978-981-96-2074-6_2
DO - 10.1007/978-981-96-2074-6_2
M3 - Conference contribution
AN - SCOPUS:85215985308
SN - 9789819620739
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 18
EP - 29
BT - MultiMedia Modeling - 31st International Conference on Multimedia Modeling, MMM 2025, Proceedings
A2 - Ide, Ichiro
A2 - Kompatsiaris, Ioannis
A2 - Xu, Changsheng
A2 - Yanai, Keiji
A2 - Chu, Wei-Ta
A2 - Nitta, Naoko
A2 - Riegler, Michael
A2 - Yamasaki, Toshihiko
PB - Springer Science and Business Media Deutschland GmbH
T2 - 31st International Conference on Multimedia Modeling, MMM 2025
Y2 - 8 January 2025 through 10 January 2025
ER -