Avdic, M;
Marquardt, N;
Rogers, Y;
Vermeulen, J;
(2021)
Machine Body Language: Expressing a Smart Speaker’s Activity with Intelligible Physical Motion.
In:
Proceedings DIS '21: Designing Interactive Systems Conference 2021.
(pp. pp. 1403-1418).
ACM
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Abstract
People’s physical movement and body language implicitly convey what they think and feel, are doing or are about to do. In contrast, current smart speakers miss out on this richness of body language, primarily relying on voice commands only. We present QUBI, a dynamic smart speaker that leverages expressive physical motion – stretching, nodding, turning, shrugging, wiggling, pointing and leaning forwards/backwards – to convey cues about its underlying behaviour and activities. We conducted a qualitative Wizard of Oz lab study, in which 12 participants interacted with QUBI in four scripted scenarios. From our study, we distilled six themes: (1) mirroring and mimicking motions; (2) body language to supplement voice instructions; (3) anthropomorphism and personality; (4) audio can trump motion; (5) reaffirming uncertain interpretations to support mutual understanding; and (6) emotional reactions to QUBI’s behaviour. From this, we discuss design implications for future smart speakers.
Type: | Proceedings paper |
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Title: | Machine Body Language: Expressing a Smart Speaker’s Activity with Intelligible Physical Motion |
Event: | DIS '21: Designing Interactive Systems Conference 2021 |
ISBN-13: | 9781450384766 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1145/3461778.3462031 |
Publisher version: | https://doi.org/10.1145/3461778.3462031 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10130537 |
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