Evidence map›Paper›PMID 36267900›Full record

ArticleJournal of rehabilitation and assistive technologies engineering

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

Kazumi Kumagai, Seiki Tokunaga, Norihisa P Miyake, Kazuhiro Tamura, Ikuo Mizuuchi, Mihoko Otake-Matsuura

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Article in Journal of rehabilitation and assistive technologies engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Kazumi KumagaiCenter for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.ORCID https://orcid.org/0000-0003-3191-3219
Seiki TokunagaCenter for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
Norihisa P MiyakeCenter for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
Kazuhiro TamuraCenter for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.
Ikuo MizuuchiTokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo 184-8588, Japan.
Mihoko Otake-MatsuuraCenter for Advanced Intelligence Project, RIKEN, Nihonbashi 1-chome Mitsui Building, 15th floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

human robot interactionrobotics for ambient assisted livingscenario-based dialogueturn-taking

Identifiers

PMID36267900
PMCPMC9578174

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.