Spoken natural language dialog systems: a practical approach
Spoken natural language dialog systems: a practical approach
The informational complexity of learning from examples
The informational complexity of learning from examples
Survey of the state of the art in human language technology
Survey of the state of the art in human language technology
Computational Complexity and Natural Language
Computational Complexity and Natural Language
Lessons learned in modeling schizophrenic and depressed responsive virtual humans for training
Proceedings of the 8th international conference on Intelligent user interfaces
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This paper will describe a way to organize the salient objects, their attributes, and relationships between the objects in a given domain. This organization allows us to assign an information value to each collection, and to the domain as a whole, which corresponds to the number of things to "talk about" in the domain. This number gives a measure of semantic complexity; that is, it will correspond to the number of objects, attributes, and relationships in the domain, but not to the level of syntactic diversity allowed when conveying these meanings.Defining a measure of semantic complexity for a dialog system domain will give an insight towards making a complexity measurement standard. With such a standard, natural language programmers can measure the feasibility of making a natural language interface, compare different language processors' ability to handle more and more complex domains, and quantify the abilities of the current state of the art in natural language processors.