By Ina Wechsung
This publication offers (1) an exhaustive and empirically demonstrated taxonomy of caliber points of multimodal interplay in addition to respective dimension equipment, (2) a established questionnaire particularly adapted to the review of multimodal structures and masking many of the taxonomy‘s caliber points, (3) insights on how the standard perceptions of multimodal platforms relate to the standard perceptions of its person elements, (4) a suite of empirically validated elements which effect modality selection, and (5) types concerning the dating of the perceived caliber of a modality and the particular utilization of a modality.
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Additional info for An Evaluation Framework for Multimodal Interaction: Determining Quality Aspects and Modality Choice
Thus, their information processing might lack logical consistency. For evaluative judgments this means, that evaluation is probably more context-driven than contentdriven (Bless et al, 1996). More specifically in terms of usability studies, people in a positive mood might give less exact evaluation ratings, as positive mood is associated with less attention given to details and less information being considered. g. the setting and scenario. 28 3 What to Evaluate? – A Taxonomy of Quality Aspects Additionally, memory recall is mood congruent: good moods make recall of positive experiences more likely than bad moods and vice versa (Kahneman, 1999).
G. lip-movements or facial expressions). Interaction Performance Aspects on the User Side All processing steps described above, can be mapped to the interaction performance aspects proposed by Möller et al. (2009) and Wechsung et al. (2012a). These aspects are perceptual effort, cognitive workload and response effort. Perceptual effort. g. listening-effort or reading effort. 2 Interaction Performance 31 ties described above. The Borg scale can be used to assess perceptual effort (Borg, 1982).
Kühnel (2012) and Möller (2009) define concept efficiency based on Glass et al. ” Dialogue management performance. The main function of the dialog manager is maintaining the dialogue coherence to lead the dialogue to the intended goal (Gibbon, Moore, & Winski, 1998). This meta-functionality can be assessed via task-success parameters (cf. Möller, 2005). g. the selection of the dialogue strategy and error recovery (for a comprehensive list see Gibbon, Moore, & Winski, 1998). ” (Kühnel, 2012) and the number of system correction turns or the system corrections rate, which are defined as the “overall number (SCT) or percentage (SCR) of all system turns in a dialogue which are primarily concerned with rectifying ‘a trouble’ (caused by […] recognition or understanding errors, or by illogical, contradictory, or undefined user input), thus not contributing new propositional content and interrupting the dialogue flow.
An Evaluation Framework for Multimodal Interaction: Determining Quality Aspects and Modality Choice by Ina Wechsung