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dc.contributor.authorGonzález, Adriana Lorena
dc.contributor.authorGeiskkovitch, Denise Y.
dc.contributor.authorYoung, James E.
dc.date.accessioned2023-03-31T05:48:07Z
dc.date.available2023-03-31T05:48:07Z
dc.date.issued2023
dc.identifier.issn2196-6826
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/41077
dc.description.abstractWe present a conversational social robot behaviour design that draws from psychotherapy research to support individual self-reflection and wellbeing, without requiring the robot to parse or otherwise understand what the user is saying. This simplicity focused approached enabled us to intersect the well-being aims with privacy and simplicity, while achieving high robustness. We implemented a fully autonomous and standalone (not network enabled) prototype and conducted a proof-of-concept study as an initial step to test the feasibility of our behaviour design: whether people would successfully engage with our simple behaviour and could interact meaningfully with it. We deployed our robot unsupervised for 48 h into the homes of 14 participants. All participants engaged with self-reflection with the robot without reporting any interaction challenges or technical issues. This supports the feasibility of our specific behaviour design, as well as the general viability of our non-parsing simplicity approach to conversation, which we believe to be an exciting avenue for further exploration. Our results thus pave the way for further exploring how conversational behaviour designs like ours may support people living with loneliness.en
dc.language.isoen
dc.publisherDe Gruyter
dc.relation.ispartofi-com: Vol. 22, No. 1
dc.subjectcompanion robots
dc.subjectconversational robot
dc.subjectdomestic robots
dc.subjectrobots in the wild
dc.subjectself-reflection therapy
dc.subjectsocial robotics
dc.titleSay what you want, I’m not listening! A conversational self-reflection robot that does not parse user speechen
dc.typeText/Journal Article
dc.pubPlaceBerlin
mci.conference.sessiontitleResearch Article
dc.identifier.doi10.1515/icom-2022-0047


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