Shaping user input: a strategy for natural language dialogue design

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Abstract
Traditional approaches to natural language dialogue interface design have adopted ordinary human-human conversation as the model for online human-computer interaction. The attempt to deal with all the subtleties of natural dialogues, such as topic focus, coherence, ellipsis, pronominal reference, etc. has resulted in prototype systems that are enormously complex and computationally expensive. The experimentation reported here was supported by the IBM Corporation under the Shared University Research programme, Poughkeepsie contract #755 to Vassar College. The views expressed herein are those of the authors and do not necessarily represent those of Vassar College or the IBM Corporation. we explored ways of minimizing the processing burden of a dialogue system by channeling user input towards a more tractable, though still natural, form of Englishlanguage questions. Through linking a pair of terminals, we presented subjects with two different dialogue styles as a framework for online help in the domain of word-processing. The first dialogue style involved ordinary conversational format. The second style involved a simulation of an automated dialogue system, including apparent processing restrictions and ‘system process messages’ to inform the subject of the steps taken by the system during query analysis. In both cases human tutors played the role of the help system. After each dialogue session, subjects were interviewed to determine their assessments of the naturalness and usability of the dialogue interface. We found that user input became more tractable to parsing and query analysis as the dialogue style became more formalized, yet the subjective assessment of naturalness and usability remained fairly constant. This suggests that techniques for channeling user input in a dialogue system may be effectively employed to reduce processing demands without compromising the benefits of a natural language interface. Theoretically, this data lends support to the hypothesis that unrestricted human-human conversation is not the most appropriate model for the design of human-computer dialogue interfaces.

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