Affecting People with Natural Language

用自然语言影响人们

• 批准号: EP/E011764/1
• 负责人: Christopher Mellish
• 金额: $ 82.05万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2007
• 资助国家: 英国
• 起止时间: 2007 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FE011764%2F1
• 关键词: Affecting; People; Natural; Language

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.

用自然语言（如英语）编写的文档越来越多地由计算机和人编写，计算机编写的文档经常用于许多专业应用，如天气预报。不幸的是，自然语言生成的计算机模型对个体读者的差异以及哪种表达方式最适合哪种读者的理解相对较差。因此，他们不适合更有挑战性的任务，比如说服病人戒烟，或者用幽默来改变某人对全球变暖意义的看法。这些任务的文本的目标是影响读者在一个更深的方式比只是给他们一些重要的事实。拟议的研究旨在提高NLG技术的敏感性，读者和范围的影响，可以实现。为此，NLG技术专家有必要向其他领域的研究人员学习，例如心理学和用户建模，而NLG研究人员则需要提高技术的鲁棒性和通用性，以应对新的挑战。

项目成果

Managing ambiguity in reference generation: the role of surface structure.

管理参考生成中的歧义：表面结构的作用。

• DOI: 10.1111/j.1756-8765.2011.01167.x
• 发表时间: 2012
• 期刊: Topics in cognitive science
• 影响因子: 3
• 作者: Khan IH

Evaluating Centering for Information Ordering Using Corpora

使用语料库评估信息排序的中心化

• DOI: 10.1162/coli.07-036-r2-06-22
• 发表时间: 2009
• 期刊: Computational Linguistics
• 影响因子: 9.3
• 作者: Karamanis N

Computational Generation of Referring Expressions: A Survey

• DOI: 10.1162/coli_a_00088
• 发表时间: 2012-03-01
• 期刊: COMPUTATIONAL LINGUISTICS
• 影响因子: 9.3
• 作者: Krahmer, Emiel;van Deemter, Kees
• 通讯作者: van Deemter, Kees

Supporting Personal Narrative for Children with Complex Communication Needs

• DOI: 10.1145/2240156.2240163
• 发表时间: 2012-07-01
• 期刊: ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION
• 影响因子: 3.7
• 作者: Black, Rolf;Waller, Annalu;Reiter, Ehud
• 通讯作者: Reiter, Ehud

BT-Nurse: computer generation of natural language shift summaries from complex heterogeneous medical data.

BT-Nurse：计算机根据复杂的异构医疗数据生成自然语言转换摘要。

• DOI: 10.1136/amiajnl-2011-000193
• 发表时间: 2011
• 期刊: JAMIA
• 作者: Hunter J