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Building a working spoken natural language dialog system is a complex challenge. It requires the integration of solutions to many of the important subproblems of natural language processing. This chapter discusses the foundations for a theory of integrated dialog processing, highlighting previous research efforts. The traditional approach in AI for problem solving has been the planning of a complete solution. We claim that the interactive environment, especially one with variable initiative, renders such a strategy inadequate. A user with the initiative may not perform the task steps in the same order as those planned by the computer. They may even perform a different set of steps. Furthermore, there is always the possibility of miscommunication. Regardless of the source of complexity, the previously developed solution plan may be rendered unusable and must be redeveloped. This is noted by Korf [Kor87]: . . . Ideally, the term planning applies to problem solving in a real-world environment where the agent may not have complete information about the world or cannot completely predict the effects of its actions. In that case, the agent goes through several iterations of planning a solution, executing the plan, and then replanning based on the perceived result of the solution. Most of the literature on planning, however, deals with problem solving with perfect information and prediction. . . . Wilkins [Wil84] also acknowledges this problem: . . . In real-world domains, things do not always proceed as planned. Therefore, it is desirable to develop better execution-monitoring techniques and better capabilities to replan when things do not go as expected. This may involve planning for tests to verify that things are indeed going as expected.... The problem of replanning is also critical. In complex domains it becomes increasingly important to use as much as possible of the old plan, rather than to start all over when things go wrong. . . . Consequently, Wilkins adopts the strategy of producing a complete plan and revising it rather than reasoning in an incremental fashion.

The most sophisticated and efficient means of communication between humans is spoken natural language (NL). It is a rare circumstance when two people choose to communicate via another means when spoken natural language is possible. Ochsman and Chapanis [OC74] conducted a study involving two person teams solving various problems using restricted means of communication such as typewriting and video, typewriting only, handwriting and video, voice and video, voice only, etc. Their conclusion included the following statement. . . . The single most important decision in the design of a telecommunications link should center around the inclusion of a voice channel. In the solution of factual real-world problems, little else seems to make a demonstrable difference . . . Thus, it would seem desirable to develop computer systems that can also communicate with humans via spoken natural language dialog. Furthermore, recent reports from the research community in speech recognition [Adv93] indicate that accuracy levels in speaker-independent continuous speech recognition have reached a threshold where practical applications of spoken natural language are viable. This book addresses the dialog issues that must be resolved in building effective spoken natural language dialog systems—systems where both the human and computer interact via spoken natural language. We present an architecture for dialog processing for which an implementation in the equipment repair domain has been constructed that exhibits a number of behaviors required for efficient human-machine dialog. These behaviors include the following. • Problem solving to achieve a target goal. • The ability to carry out subdialogs to achieve appropriate subgoals and to pass control arbitrarily from one subdialog to another. • The use of a user model to enable useful verbal exchanges and to inhibit unnecessary ones. • The ability to use context dependent expectations to correct speech recognition and track user movement to new subdialogs. • The ability to vary the task/dialog initiative from strongly computer controlled to strongly user controlled or somewhere in between.