By Ina Wechsung
This booklet provides (1) an exhaustive and empirically proven taxonomy of caliber features of multimodal interplay in addition to respective dimension equipment, (2) a tested questionnaire particularly adapted to the assessment of multimodal structures and masking lots of the taxonomy‘s caliber elements, (3) insights on how the standard perceptions of multimodal structures relate to the standard perceptions of its person parts, (4) a collection of empirically confirmed components 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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Extra resources for An Evaluation Framework for Multimodal Interaction: Determining Quality Aspects and Modality Choice
A prominent method is Thinking Aloud. Here participants are asked to verbalize and loudly utter their thoughts (Holzinger, 2005). This might be done during the interaction or after the interaction as retrospective Thinking Aloud. For the latter, the user is confronted with video recordings of the test session and is asked to comment on them. Although retrospective Thinking Aloud is less intrusive than online Thinking Aloud, it might probably be affected by memory biases. Another version is the plural Thinking Aloud involving multiple participants using the system together.
According to Jokinen and Raike (2003), especially multimodal interfaces offer a possibility to realize this metaphor, as they enable the user to employ various types of input and output modalities and are thus more conversational in nature. g. the number of available functions and their complexity, structure and usage frequency (cf. Möller, 2006). , 2009). The characteristics are then listed qualitatively in specification documents. Agent factors are defined by the system developer together with design experts.
Fusion gain is, according to Kühnel (2012), the sum of recognition errors for each modality compared to the recognition errors of the fused input. Output modality appropriateness. Output modality appropriateness corresponds to the input modality appropriateness and can be quantified in the same way, by using the properties offered by Bernsen (2008). The possible values are the same as for input modality appropriateness. Contextual appropriateness. Contextual appropriateness is the proportion of system utterances being judged as appropriate in the dialogue context.
An Evaluation Framework for Multimodal Interaction: Determining Quality Aspects and Modality Choice by Ina Wechsung