%0 Book Section %1 JokinenWilcock14MA3HMI %A Jokinen, Kristiina %A Wilcock, Graham %B Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction %C Cham %D 2015 %E Böck, Ronald %E Bonin, Francesca %E Campbell, Nick %E Poppe, Ronald %I Springer %K v1500 springer paper ai speech user interface robot agent multimodal interaction requirements test zzz.hci zzz.mmi %N 8757 %P 45-56 %R 10.1007/978-3-319-15557-9_5 %T Modelling User Experience in Human-Robot Interactions %X In human-human interaction, the participants' multimodal behaviour has impact on the interaction as a whole, and similarly in spoken human-robot interactions, the interlocutors' multimodal signals seem to correlate with the user's experience and impressions of the interaction. We explored in more detail how some aspects of multimodal behaviour (gazing, facial expressions, body posture) can predict the user's evaluation of the robot's behaviour (Responsiveness, Expressiveness, Interface, Usability, Overall impression). The results indicate that the user's assessment concerning the evaluation categories Interface and Usability, and to some extent the categories Expressiveness and Overall correlate with their behaviour in a statistically significant manner. The work contributes to our understanding of how the interlocutors' engagement and active participation relate to their assessment of the success of communication, and points towards automating evaluation of human-robot interactions.

@incollection{JokinenWilcock14MA3HMI, abstract = {In human-human interaction, the participants' multimodal behaviour has impact on the interaction as a whole, and similarly in spoken human-robot interactions, the interlocutors' multimodal signals seem to correlate with the user's experience and impressions of the interaction. We explored in more detail how some aspects of multimodal behaviour (gazing, facial expressions, body posture) can predict the user's evaluation of the robot's behaviour (Responsiveness, Expressiveness, Interface, Usability, Overall impression). The results indicate that the user's assessment concerning the evaluation categories Interface and Usability, and to some extent the categories Expressiveness and Overall correlate with their behaviour in a statistically significant manner. The work contributes to our understanding of how the interlocutors' engagement and active participation relate to their assessment of the success of communication, and points towards automating evaluation of human-robot interactions.}, added-at = {2015-03-09T10:31:20.000+0100}, address = {Cham}, author = {Jokinen, Kristiina and Wilcock, Graham}, biburl = {https://www.bibsonomy.org/bibtex/205c4822247649774c8dd8b5e583aa021/flint63}, booktitle = {Multimodal Analyses enabling Artificial Agents in Human-Machine Interaction}, crossref = {MA3HMI2014}, doi = {10.1007/978-3-319-15557-9_5}, editor = {B\"{o}ck, Ronald and Bonin, Francesca and Campbell, Nick and Poppe, Ronald}, file = {SpringerLink:2014/JokinenWilcock14MA3HMI.pdf:PDF}, groups = {public}, interhash = {67cac8e80fa55cdb943960ccdb4a6078}, intrahash = {05c4822247649774c8dd8b5e583aa021}, keywords = {v1500 springer paper ai speech user interface robot agent multimodal interaction requirements test zzz.hci zzz.mmi}, number = 8757, pages = {45-56}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, timestamp = {2018-04-16T12:10:45.000+0200}, title = {Modelling User Experience in Human-Robot Interactions}, username = {flint63}, year = 2015 }