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Spoken Natural Language Dialog SystemsA Practical Approach$
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Ronnie W. Smith and D. Richard Hipp

Print publication date: 1995

Print ISBN-13: 9780195091878

Published to Oxford Scholarship Online: November 2020

DOI: 10.1093/oso/9780195091878.001.0001

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Computational Model

Computational Model

(p.75) Chapter 4 Computational Model
Spoken Natural Language Dialog Systems

Ronnie W. Smith

D. Richard Hipp

Oxford University Press

This chapter describes the computational model that has evolved from the theory of integrated dialog processing presented in the previous chapter. The organization of this chapter follows. 1. A high-level description of the basic dialog processing algorithm. 2. A detailed discussion of the major steps of the algorithm. 3. A concluding critique that evaluates the model’s effectiveness at handling several fundamental problems in dialog processing. The system software that implements this model is available via anonymous FTP. Details on obtaining the software are given in appendix C. Figure 4.1 describes the basic steps of the overall dialog processing algorithm that is executed by the dialog controller. By necessity, this description is at a very high level, but specifics will be given in subsequent sections. The motivation for these steps is presented below. Since the computer is providing task assistance, an important part of the algorithm must be the selection of a task step to accomplish (steps 1 and 2). Because the characterization of task steps is a function of the domain processor, the dialog controller must receive recommendations from the domain processor during the selection process (step 1). However, since a dialog may have arbitrary suspensions and resumptions of subdialogs, the dialog controller cannot blindly select the domain processor’s recommendation. The relationship of the recommended task step to the dialog as well as the dialog status must be considered before the selection can be made (step 2). Once a task step is selected, the dialog controller must use the general reasoning facility (i.e. the interruptible theorem prover, IPSIM) in step 3 to determine when the task step is accomplished. Whenever the theorem prover cannot continue due to a missing axiom, the dialog controller uses available knowledge about linguistic realizations of utterances in order to communicate a contextually appropriate utterance as well as to compute expectations for the response. After the response is received and its relationship to the missing axiom determined, the dialog controller must decide how to continue the task step completion process.

Keywords:   Axiom Value, Domain knowledge, Ellipsis, FTP, General reasoning module, Input, Knowledge module, Linguistic interface module, Matching strings

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