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TU Berlin

Inhalt des Dokuments

Superior User Experience Modeling

Lupe

Semi-automatic assessment of User Experience based on a battery of machine learning and artificial intelligence methods using information from various sources (e.g. interaction data, web-services, usability heuristics)


Motivation & Project Description

  • UX has become the key success metric for all commercial services and products
  • UX is on the DTAG roadmap of most urgent topics
  • Fusion of several engineering approaches for a quick and cheap objective assessment of a design's UX
  • The proposed methods are tested with several design prototypes


Outcome:

  • Model of the user’s belief about the dialog state; can be used to predict quality judgments and detect problematic dialog situations
  • Activation-based user model – first step towards a model of users’ affect during the interaction
  • Analysis of importance of quality aspects on overall quality judgments of dialog systems
  • Interaction quantification framework and logging capabilities for android apps
  • Model of older adults’ errors when using smartphones due to their mental model of the device
  • Models to predict modality selection in multimodal interaction
  • Models to predict perceived quality in multimodal interaction
  • Study on user characteristics and user judgments for android apps (still running)
  • Study on app characteristics and user judgments for android apps (still running)
  • Several papers and a framework for research on dialog simulation
  • Improvements in the MeMo workbench


Time Frame: 
01/2011 - 12/2012

T-labs Team Members:
F. Gödde, K.-P. Engelbrecht, S. Möller, S.Schmidt, M. Schulz, B. Weiss
Students:
M. Siebke, R. Tönges, G. Neitzel
Partners:
Funding by:
Deutsche Telekom Laboratories
Publications:
see project publications

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