Proceedings

A Comprehension Model for Human Dialogue

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Proceedings of the Fifth International Joint Conference on Artificial Intelligence. Natural Language. Pages 77-86.

Abstract

he comprehension of dialogue is an important concern for those interested in natural language processing for several reasons: dialogue gives particularly good access to human communication phenomena, it is less contrived than authored text, and human dialogue provides useful analogies for improving man-machine communication. In naturally occurring dialogues, the goals of the participants play a key role in structuring their language interactions. People know how dialogue is used to achieve goals, and they use this knowledge to comprehend what they hear. We have represented this knowledge in structures called Dialogue-games, which differ from other multisentential knowledge structures by represent i ng knowledge about how language is used to pursue goals rather than the structure of the content being conveyed. These Dialogue-games, whi ch govern such activities as helping, information seeking, giving i nstruct ions, announcing, and testing someone's knowledge, are part of a strongly goal-oriented model of language comprehension . This model is composed of autonomous processes which operate on shared memories. Each of the four memories (a long-term memory and a short-term memory for each of two participants) is a collection of predicate expressions representing the individual's fixed knowledge and current awareness. An important part of this research has focused on the problem of model evaluation. Benchmarks for use in evaluating model performance have been developed, creating opportunities for empirical validation of the effectiveness of natural language process models. The modeling effort described here has led to progress on several problems of natural language comprehension - it provides an explanation for topic changes, serves as a basis for limiting inferences, accounts for the comprehension of a number of different kinds of implicit communication, and suggests ways that formal man-machine communication could be improved. It thus illustrates the utility of an overall goal-oriented view of language.

William C. Mann, James A. Moore, and James A. Levin. 1977. A Comprehension Model for Human Dialogue. In Proceedings of the Fifth International Joint Conference on Artificial Intelligence, IJCAI-77. IJCAI, 77–86. https://ijcai.org/proceedings/1977/13
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