Managing adaptive spoken dialogue for Intelligent Environments

Speech interfaces within Intelligent Environments (IEs) must be rendered adaptive to external and internal factors, among those the complexity of the dialogue. Hence, we present HIS-OwlSpeak, a model-driven dialogue manager for Intelligent Environments. It meets the challenges arising from engineering IEs by providing a unified platform comprising adaptivity to a variety of internal and external factors. This work addresses internal adaptivity realized by different modes of dialogue control, i.e., rule-based and probabilistic. For this, the Hidden Information State (HIS) approach - featuring inherent handling of uncertainty in dialogue systems - is applied to a model-driven, solely rule-based dialogue manager. It uses ontologies to specify the dialogue thus separating the specification from the dialogue control. Consequently, all necessary aspects for merging the world of model-driven dialogue management with the HIS approach are presented in detail. Furthermore, the system has been evaluated using two concurrent dialogues of different complexity successfully validating the implementation.