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Individual differences in multimodal integration patterns: what are they and why do they exist?
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
Portland, Oregon, USA
SESSION: Eye gaze and multimodal integration patterns table of contents
Pages: 241 - 249  
Year of Publication: 2005
ISBN:1-58113-998-5
Authors
Sharon Oviatt  Oregon Health & Science University, Beaverton, OR
Rebecca Lunsford  Oregon Health & Science University, Beaverton, OR
Rachel Coulston  Oregon Health & Science University, Beaverton, OR
Sponsors
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Techniques for information fusion are at the heart of multimodal system design. To develop new user-adaptive approaches for multimodal fusion, the present research investigated the stability and underlying cause of major individual differences that have been documented between users in their multimodal integration pattern. Longitudinal data were collected from 25 adults as they interacted with a map system over six weeks. Analyses of 1,100 multimodal constructions revealed that everyone had a dominant integration pattern, either simultaneous or sequential, which was 95-96% consistent and remained stable over time. In addition, coherent behavioral and linguistic differences were identified between these two groups. Whereas performance speed was comparable, sequential integrators made only half as many errors and excelled during new or complex tasks. Sequential integrators also had more precise articulation (e.g., fewer disfluencies), although their speech rate was no slower. Finally, sequential integrators more often adopted terse and direct command-style language, with a smaller and less varied vocabulary, which appeared focused on achieving error-free communication. These distinct interaction patterns are interpreted as deriving from fundamental differences in reflective-impulsive cognitive style. Implications of these findings are discussed for the design of adaptive multimodal systems with substantially improved performance characteristics.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Sharon Oviatt: colleagues
Rebecca Lunsford: colleagues
Rachel Coulston: colleagues