This paper describes a dialogue act tagging scheme developed for the purpose of providing finer-grained quantitative dialogue metrics for comparing and evaluating DARPA COMMUNICATOR spoken dialogue systems. We show that these dialogue act metrics can be used to quantify the amount of effort spent in a dialogue maintaining the channel of communication or, establishing the frame for communication...

We present open dialogue management and its application to relational databases. An open dialogue manager generates dialogue states, actions, and default strategies from the semantics of its application domain. We define three open dialogue management tasks. First, vocabulary selection finds the intelligible attributes in each database table. Second, focus discovery selects candidate dialogue f...

We define a new dialogue management strategy Limited Enquiry Negotiation Dialogues designed for enabling simple man-machine dialogues in which the parameters (for which the user will supply values) of a query to a database are negotiated. The choice of which query to make next is also not pre-ordained. The strategy is simple and intuitive but permits interestingly complex dialogue behaviour. We...

For tutorial dialogue systems, selecting an appropriate dialogue move to support learners can significantly influence cognitive and affective outcomes. The strategies implemented in tutorial dialogue systems have historically been based on handcrafted rules derived from observing human tutors, but a data-driven model of strategy selection may increase the effectiveness of tutorial dialogue syst...

We investigate the use of different machine learning methods in combination with feature selection techniques to explore human multimodal dialogue strategies and the use of those strategies for automated dialogue systems. We learn policies from data collected in a Wizardof-Oz study where different human ‘wizards’ decide whether to ask a clarification request in a multimodal manner or else to us...

We investigate the use of different machine learning methods in combination with feature selection techniques to explore human multimodal dialogue strategies and the use of those strategies for automated dialogue systems. We learn policies from data collected in a Wizardof-Oz study where different human ‘wizards’ decide whether to ask a clarification request in a multimodal manner or else to us...

In many settings, agents (whether human or artificial) engage in problem solving activities, which require them to share resources, act on each others’ behalf, communicate and coordinate individual acts, and so on. If autonomous agents are to effectively interact (or support interaction among humans) in situations such as deciding whom and how to approach the provision of a resource or the perf...

This paper describes a strategy for mixed-initiative spoken dialogue management. The strategy is outlined, and two experiments are carried out to investigate the methodology. The experiments are carried out within the Esprit OVID1project. The OVID project is concerned with the development of trial applications within automated banking services [1]. Among other things, the OVID user specificatio...