Introduction: We have conducted research on building a robot dialogue system to support the independent living of older adults. In order to provide appropriate support for them, it is necessary to obtain as much information, particularly related to their health condition, as possible. As the first step, we have examined a method to allow dialogue to continue for longer periods. Methods: A scenario-based dialogue system utilizing pause detection for turn-taking was built. The practicality of adjusting the system based on the dialogue rhythm of each individual was studied. The system was evaluated through user studies with a total of 20 users, 10 of whom were older adults. Results: The system detected pauses in the user's speech using the sound level of their voice, and predicted the duration and number of pauses based on past dialogue data. Thus, the system initiated the robot's voice-call after the user's predicted speech. Conclusions: Multiple turns of dialogue between robot and older adults are found possible under the system, despite several overlaps of robot's and users' speech observed. The users responded to the robot, including the questions related to health conditions. The feasibility of a scenario-based dialogue system was suggested; however, improvements are required.
Introduction: We have conducted research on building a robot dialogue system to support the independent living of older adults. In order to provide appropriate support for them, it is necessary to obtain as much information, particularly related to their health condition, as possible. As the first step, we have examined a method to allow dialogue to continue for longer periods. Methods: A scenario-based dialogue system utilizing pause detection for turn-taking was built. The practicality of adjusting the system based on the dialogue rhythm of each individual was studied. The system was evaluated through user studies with a total of 20 users, 10 of whom were older adults. Results: The system detected pauses in the user's speech using the sound level of their voice, and predicted the duration and number of pauses based on past dialogue data. Thus, the system initiated the robot's voice-call after the user's predicted speech. Conclusions: Multiple turns of dialogue between robot and older adults are found possible under the system, despite several overlaps of robot's and users' speech observed. The users responded to the robot, including the questions related to health conditions. The feasibility of a scenario-based dialogue system was suggested; however, improvements are required.
Authors: James C Mundt; Peter J Snyder; Michael S Cannizzaro; Kara Chappie; Dayna S Geralts Journal: J Neurolinguistics Date: 2007-01 Impact factor: 1.710
Authors: Norina Gasteiger; Ho Seok Ahn; Christine Fok; JongYoon Lim; Christopher Lee; Bruce A MacDonald; Geon Ha Kim; Elizabeth Broadbent Journal: Assist Technol Date: 2021-05-03