Scenario-based dialogue system based on pause detection toward daily health monitoring.

IF 2 Q3 ENGINEERING, BIOMEDICAL Journal of Rehabilitation and Assistive Technologies Engineering Pub Date : 2022-10-13 eCollection Date: 2022-01-01 DOI:10.1177/20556683221133367
Kazumi Kumagai, Seiki Tokunaga, Norihisa P Miyake, Kazuhiro Tamura, Ikuo Mizuuchi, Mihoko Otake-Matsuura
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引用次数: 1

Abstract

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.

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基于暂停检测的面向日常健康监测的场景对话系统。
引言:我们研究了构建一个机器人对话系统来支持老年人的独立生活。为了向他们提供适当的支助,必须尽可能多地获取信息,特别是与他们的健康状况有关的信息。作为第一步,我们研究了一种允许对话持续更长时间的方法。方法:构建基于场景的对话系统,利用暂停检测进行轮询。研究了基于个体对话节奏对系统进行调整的可行性。该系统通过用户研究进行评估,共有20名用户,其中10名是老年人。结果:系统通过用户语音的声级来检测用户语音中的停顿,并根据过去的对话数据预测停顿的持续时间和次数。因此,系统在用户预测的语音之后启动机器人的语音呼叫。结论:在该系统下,机器人和老年人之间的对话可以有多个回合,尽管观察到机器人和用户的语音有几个重叠。用户对机器人做出回应,包括与健康状况有关的问题。提出了基于场景的对话系统的可行性;然而,需要改进。
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