Natural Language Generation in Interactive Systems

392021 Natural Language Generation for Interactive Systems (S) (SoSe 2015)
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Intuition and the Limits of Natural Language Generation - InfoDesk

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Edited by Amanda Stent, AT&T Research, Florham Park, New Jersey, Srinivas Bangalore, AT&T Research, Florham Park, New Jersey. Subjects: Computer Science, Communications and Signal Processing, Artificial Intelligence and Natural Language Processing, Engineering. 7 - Reinforcement. An informative and comprehensive overview of the state-of-the-art in natural language generation (NLG) for interactive systems, this guide serves to introduce .

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Natural Language Processing Publications

For example, conversational interaction and interfaces are nowadays a trend, showing the central role of language generation in a variety of intelligent interactive systems. This limits a system's expressivity in unexpected situations. Adeyanju, I. Gadgets Essays. With a major influx of data that needs to be assessed along with the need to reduce costs significantly, enterprises need to identify ways to streamline.

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Computing Science. Abstract Introduction A key task of almost any natural language generation NLG system is to refer to entities.

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In the words of the philosopher John Searle, Any expression which serves to identify any thing, process, event, action, or any other kind of individual or particular I shall call a referring expression. Computing Science.

Natural language generation for augmentative and assistive technologies

Bangalore Eds. Cambridge: Cambridge University Press.

Natural Language Generation at Google Research (AI Adventures)

Natural Language Generation in Interactive Systems.