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

10 25 50
publication icon
Black R (2012) Supporting Personal Narrative for Children with Complex Communication Needs in ACM Transactions on Computer-Human Interaction

publication icon
Deemter Kees Van (2010) Not Exactly: In Praise of Vagueness

publication icon
Edwards P (2009) e-Social Science and Evidence-Based Policy Assessment Challenges and Solutions in Social Science Computer Review

publication icon
Hunter J (2011) BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data. in Journal of the American Medical Informatics Association : JAMIA

publication icon
Karamanis N (2009) Evaluating Centering for Information Ordering Using Corpora in Computational Linguistics

publication icon
Krahmer E (2012) Computational Generation of Referring Expressions: A Survey in Computational Linguistics

publication icon
Manurung R (2008) Adding phonetic similarity data to a lexical database in Language Resources and Evaluation