Abstract
Modeling language as people really use it is an elusive goal. Today, thanks to advances in speech recognition, dialog systems capable of understanding the meaning of user input and replying with appropriate information exist, but there are as yet no systems which interact naturally with humans. Two problems are:
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1.
Priority is given to understanding and responding accurately; but for human dialog, being responsive and interactive is also important.
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The granularity of interaction is the sentence; but for human dialog, interaction happens more frequently, in real time, often with overlapping utterances;
Given that such responsiveness is important to human language use, the question arises: how do we build systems with these abilities? The obvious approach is to add these abilities to a meaning based speech system. An alternative approach is to take these abilities as a basic foundation, and to layer meaning-based processing on top of this, subsumption-style (Ward, 1997).
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Ward, N., Tsukahara, W. (1999). A Responsive Dialog System. In: Wilks, Y. (eds) Machine Conversations. The Springer International Series in Engineering and Computer Science, vol 511. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5687-6_14
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DOI: https://doi.org/10.1007/978-1-4757-5687-6_14
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