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Mixing implicit and explicit probes: Finding a ground truth for engagement in social human-robot interactions
Vise andre og tillknytning
2014 (engelsk)Inngår i: HRI '14 Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction, IEEE Computer Society, 2014, s. 140-141Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

In our work we explore the development of a computational model capable of automatically detecting engagement in social human-robot interactions from real-time sensory and contextual input. However, to train the model we need to establish ground truths of engagement from a large corpus of data collected from a study involving task and social-task engagement. Here, we intend to advance the current state-of-the-art by reducing the need for unreliable post-experiment questionnaires and costly time-consuming annotation with the novel introduction of implicit probes. A non-intrusive, pervasive and embedded method of collecting informative data at different stages of an interaction.

sted, utgiver, år, opplag, sider
IEEE Computer Society, 2014. s. 140-141
Serie
ACM/IEEE International Conference on Human-Robot Interaction, ISSN 2167-2148
Emneord [en]
Engagement, Ground truth, Human-robot interaction, Machine learning, Social tasks
HSV kategori
Identifikatorer
URN: urn:nbn:se:kth:diva-145468DOI: 10.1145/2559636.2559815Scopus ID: 2-s2.0-84897008442ISBN: 978-145032658-2 (tryckt)OAI: oai:DiVA.org:kth-145468DiVA, id: diva2:718699
Konferanse
9th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2014; Bielefeld; Germany; 3 March 2014 through 6 March 2014
Merknad

QC 20140522

Tilgjengelig fra: 2014-05-22 Laget: 2014-05-21 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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Peters, Christopher

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RefereraExporteraLink to record
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Referensformat
  • apa
  • harvard1
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  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
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Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf