Name
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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-15557-9_5 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
Multimodal human-robot interaction,Evaluation,User experience | User experience design,Computer science,Usability,Speech recognition,Human–computer interaction,Body posture,Facial expression,Robot,Human–robot interaction,Expressivity | Conference |
Volume | ISSN | Citations |
8757 | 0302-9743 | 1 |
PageRank | References | Authors |
0.35 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kristiina Jokinen | 1 | 277 | 40.85 |
| Graham Wilcock | 2 | 38 | 15.03 |