Multi-domain spoken dialogue systems with high degree of intelligence and domain extensibility have long been desired but difficult to achieve. When the user freely surfs among different topics during the dialogue, it will be very difficult for the system to control the switching of the topics and domains while keeping the dialogue consistent, and decide when and how to take the initiative. This paper presents a distributed agent architecture for multi-domain spoken dialogue systems with high domain extensibility and intelligence. Under this architecture, different spoken dialogue agents (SDA's) handling different domains can be developed independently, and then smoothly cooperate with one another to achieve the user's multiple goals, while a user interface agent (UIA) can access the correct spoken dialogue agent through a domain switching protocol, and carry over the dialogue state and history so as to keep the knowledge processed coherently across different domains.

In this paper, we propose a dialogue model that reflects two important aspects of spoken dialogue system: to be robust' and to be cooperative'. For this purpose, our model has two main inference spaces: Conversational Space (CS) and Problem Solving Space (PSS). CS is a kind of dynamic Bayesian network that represents a meaning of utterance and general dialogue rule. Robust' aspect is treated in CS. PSS is a network so called Event Hierarchy that represents the structure of task domain problems. Cooperative' aspect is mainly treated in PSS. In constructing CS and making inference on PSS, system's process, from meaning understanding through response generation, is modeled by dividing into five steps. These steps are (1) meaning understanding, (2) intention understanding, (3) communicative effect, (4) reaction generation, and (5) response generation. Meaning understanding step constructs CS and response generation step composes a surface expression of system's response from the part of CS. Intention understanding step makes correspondence utterance type in CS with action in PSS. Reaction generation step selects a cooperative reaction in PSS and expands a reaction to utterance type of CS. The status of problem solving and declared user's preference are recorded in mental state by communicative effect step. Then from our point of view, cooperative problem solving dialogue is regarded as a process of constructing CS and achieving goal in PSS through these five steps.

This paper discusses new trends and directions in human interface (HI) technologies, and the effects of HI technologies on human life or on social activities. This paper postulates that the HI subsumes man-machine interface, human-computer interaction, human-human interaction, human-organizational interface, human-environmental interface, human-social interface, etc. A new communication model, called Human Interface Communication Model (HICOM), and a new human dialogue model, called Human Interface Dialogue model (HIDIM), are derived by reexamining trends and directions on HI technologies from the viewpoint of functional meanings of interfaces, and from the viewpoint of a socially distributed cognition mechanism.