Affecting People with Natural Language

Lead Research Organisation: University of Aberdeen
Department Name: Computing Science

Abstract

Documents written in natural languages like English are increasingly being written by computers as well as people, and computer-written documents are used routinely in many specialised applications, such as weather forecasting.Unfortunately computer models of natural language generation have a relatively poor idea about how individual readers differ and which ways of saying things will be most appropriate for which readers. As a result, they are ill-suited to more challenging tasks, such as persuading a patient to give up smoking of using humour to change someone's beliefs about the significance of globall warming. These are tasks where the goal of the text is to affect the reader in a much deeper way than just to give them some important facts.The proposed research aims to improve NLG technology in terms both of sensitivity to the reader and also of the range of effects that can be achieved. For this, it is necessary for experts in the technology of NLG to learn from researchers in other fields, for instance psychology and user modelling, and for NLG researchers in turn to increase the robustness and generality of the technology to meet the new challenges.

Publications

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WILLIAMS S (2008) Generating basic skills reports for low-skilled readers in Natural Language Engineering

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VARGES S (2010) Instance-based natural language generation in Natural Language Engineering

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Van Deemter K (2008) Fully generated scripted dialogue for embodied agents in Artificial Intelligence

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Van Deemter K (2012) Toward a computational psycholinguistics of reference production. in Topics in cognitive science

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Van Deemter K (2009) Utility and Language Generation: The Case of Vagueness in Journal of Philosophical Logic

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Reiter E (2007) The Shrinking Horizons of Computational Linguistics in Computational Linguistics