We introduce an architecture and toolkit for building dialogue managers currently being developed in the TRINDI project, based on the notions of information state and dialogue move engine. The aim is to provide a framework for experimenting with implementations of different theories of information state, information state update and dialogue control. A number of dialogue managers are currently being built using the toolkit, and we present overviews of two of them. We believe that this framework will make implementation of dialogue processing theories easier, also facilitating comparison of different types of dialogue systems, thus helping to achieve a prerequisite for arriving at a best practice for the development of the dialogue management component of a spoken dialogue system.

In this paper we show how established object modelling techniques can be used in the creation of spoken dialogue management systems. One of the motivations behind the particular approach adopted here is the observation that, in spoken human-to-human dialogues, certain skillsets and patterns of dialogue evolution are common to many different contexts; other dialogue skills and accompanying real-world knowledge are required only for more specialised transactions within particular business domains. As a starting point for modelling an automated spoken dialogue management system we recommend a use case analysis of the required functionality. The use case analysis encourages the developer to identify generic-specific relationships and interactions between different dialogue management skills. We consider some of the broad philosophies underlying current dialogue management systems and outline practical high-level dialogue behaviour based on mixed-initiative, frame-based processing, combined with a rigorously applied confirmation strategy. On the basis of the use case requirements analysis, we explore a possible design for an object-oriented dialogue management system, indicating the roles and relationships of the various classes that embody the required dialogue functionality, and showing how implemented objects within the system will interact. The manner of this interaction is such as to allow one overall system to process transactions in several business domains. We also indicate some of the advantages of a rule-based implementation: the proposed design is tailored towards such an implementation in Prolog++. An object-oriented development process places high-level, generic dialogue management functionality at the disposal of more specialised ‘expert’ components. Maintainability and extensibility are therefore enhanced: if the developer chooses to refine generic behaviour, it is immediately available to the more specialised components; if new domain-specific expertise is required, it can be added with minimal impact on generic behaviour.

The design of methods for performance evaluation is a major open research issue in the area of spoken language dialogue systems. This paper presents the PARADISE methodology for developing predictive models of spoken dialogue performance, and shows how to evaluate the predictive power and generalizability of such models. To illustrate the methodology, we develop a number of models for predicting system usability (as measured by user satisfaction), based on the application of PARADISE to experimental data from three different spoken dialogue systems. We then measure the extent to which the models generalize across different systems, different experimental conditions, and different user populations, by testing models trained on a subset of the corpus against a test set of dialogues. The results show that the models generalize well across the three systems, and are thus a first approximation towards a general performance model of system usability.