Model-based Measurement of Interaction in Mobile Multimodal Environments

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Model-based Measurement of Interaction in Mobile Multimodal Environments Pedro Mateo – Stefan Hillmann aMMI - October 2012 Pedro Mateo – Stefan Hillmann Model-based Interaction Measurement aMMI - October 2012 1 / 17

description

by Pedro Mateo ([email protected]) and Stefan Hillmann

Transcript of Model-based Measurement of Interaction in Mobile Multimodal Environments

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Model-based Measurement of Interaction in MobileMultimodal Environments

Pedro Mateo – Stefan Hillmann

aMMI - October 2012

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Agenda

Model-based Measurement of Interaction in Mobile MultimodalEnvironments:

1 Research Questions

motivation, questions and proposed solutions

2 Research and Development

MMI metrics, MMI model and Android implementation

3 Conclusion

advantages, disadvantages and research directions

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IResearch Questions

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Motivation

We analyze interaction in differentsystems...

...but independently for each system

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Motivation

And now, for each system...

different quantification/evaluation metrics

different representation formats

different interaction analysis tools

multimodal communication is not analyzed as a whole

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Research questions and proposed solutions

Question 1:

MMI assessed on a common level for different modalities?⇒ Use common and generic metrics for all modalities

Question 2:

Compare interactions observed in different MMI contexts?⇒ Structure metrics in a common representation (model)

Question 3:

Analyze MMI dinamically, step-by-step, and using real-time data?⇒ Use a run-time model

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IIResearch and Development

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Defining multimodal metrics

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Modeling multimodal interaction in EMF

Turn DialogModality

Task

User Turn System Turn

User Metacommunication System Metacommunication

Metacommunication

Speech Input

GUI Input

Gesture Input

Speech Output

GUI Output

Gesture Output

Cooperativity

Synchrony Modality Change

Appropriateness

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Modeling multimodal interaction in EMF

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Android implementation

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Android implementation

how does it work?

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IIIConclusion

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Good stuff...

common metrics + uniform representation⇒ unified criteria to quantify MMI in different scenarios

comparison is allowed, model transformation is possible

different modalities are on a level ⇒ single thread

dynamic representation of MMI ⇒ run-time applications

reuse of metrics and tools is improved

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Not so good stuff...

some data can’t be automatically collected

criteria to record parameters in different modalities?

lack of plasticity⇒ user and context information to enrich the analysis process

the HOW of interaction is not described

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And now what?

Integrate this solution in real projects

Use the framework for real analysis

Make the model context-aware, more “mobile”

Explore new possibilities of the model

E.g. behavioral biometric authentication

Project info: http://www.catedrasaes.org/wiki/MIM

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Acknowledgements

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