We present a system for exploring and personalizing internet information in the car using natural language queries. Speech dialog applications are generated automatically from well-structured internet content, such as tables, and transferred to the car. In order to cope with the large variety of speech applications, we propose a hybrid content-based personalization approach. Speech applications are clustered into various topic areas by mapping them to a domain ontology. Applications are ranked according to explicit preferences of the driver, global profile data and an implicit user profile. This profile adapts itself while the user is interacting with the system and takes into account the selected application and the speech queries. The resulting list of ranked applications is displayed to the user. Global ratings are based on the preferred topics of 20 subjects that were also questioned about the prototype's usability and accuracy in a first user evaluation.
Bibliographic reference. Fischer, Philipp / Österle, Andreas / Berton, André / Regel-Brietzmann, Peter (2007): "How to personalize speech applications for web-based information in a car", In INTERSPEECH-2007, 2557-2560.