Text generation: using discourse strategies and focus constraints to generate natural language text
Text generation: using discourse strategies and focus constraints to generate natural language text
Attention, intentions, and the structure of discourse
Computational Linguistics
Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
Generating Natural Language under Pragmatic Constraints
Generating Natural Language under Pragmatic Constraints
User modelling, dialog structure, and dialog strategy in HAM-ANS
EACL '85 Proceedings of the second conference on European chapter of the Association for Computational Linguistics
Stylistic variation in multilingual instructions
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Towards the application of text generation in an integrated publication system
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Content selection and organization as a process involving compromises
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Toward a multidimensional framework to guide the automated generation of text types
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Interactional disparities in english and arabic native speakers with a bi-lingual robot receptionist
Proceedings of the 6th international conference on Human-robot interaction
Expressing conditions in tailored brochures for public administration
Proceedings of the 11th ACM symposium on Document engineering
A policy-based approach to context dependent natural language generation
ENLG '11 Proceedings of the 13th European Workshop on Natural Language Generation
A domain-independent framework for modeling emotion
Cognitive Systems Research
The pragmatic web: addressing complex communication in public administration using tailored delivery
Proceedings of the 31st ACM international conference on Design of communication
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When humans use language, they show an essential, inbuilt responsiveness to their hearers/readers. When language is generated by machine, it is similarly necessary to ensure that that language is appropriate for its intended audience. Much of previous research on text generation and user modelling has focused on building a user model and selecting appropriate information from the knowledge base to present to the user. It is important, however, that the phrasing of a text be also tailored to the hearer - otherwise it may be just as ineffective as texts which wrongly direct attention or which rely on knowledge that the hearer does not have. This research proposes a new mechanism which allows the text planning process to specifically tailor syntactic phrasing to the hearer type. This is done in the context of an expert system explanation facility that needs to produce explanations of the expert system's behavior for a variety of different users - users who differ in goals, expectations, and expertise concerning both the expert system and its domain.