The media equation: how people treat computers, television, and new media like real people and places
The limits of speech recognition
Communications of the ACM
Spoken dialogue technology: enabling the conversational user interface
ACM Computing Surveys (CSUR)
A model for habitable and efficient dialogue management for natural language interaction
Natural Language Engineering
Towards efficient human machine speech communication: The speech graffiti project
ACM Transactions on Speech and Language Processing (TSLP)
Wired for Speech: How Voice Activates and Advances the Human-Computer Relationship
Wired for Speech: How Voice Activates and Advances the Human-Computer Relationship
Being accurate is not enough: how accuracy metrics have hurt recommender systems
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Making recommendations better: an analytic model for human-recommender interaction
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Design space for driver-based automotive user interfaces
Proceedings of the 1st International Conference on Automotive User Interfaces and Interactive Vehicular Applications
Automotive user interfaces: human computer interaction in the car
CHI '10 Extended Abstracts on Human Factors in Computing Systems
Benefits and costs of adaptive user interfaces
International Journal of Human-Computer Studies
Explaining the user experience of recommender systems
User Modeling and User-Adapted Interaction
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We present an initial set of design principles for designing efficient, effective, coherent, and desirable adaptive spoken interaction for traffic information and navigation. The principles are based on a qualitative analysis of driver interactions with an adaptive speech prototype along with driver interviews. The derived set of principles range from high-level fundamental design values, conceptual and behavioral principles, to low-level interface-level principles that can guide the design of adaptive spoken dialogue interaction in the car from a user experience perspective.