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
Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
Generating Natural Language under Pragmatic Constraints
Generating Natural Language under Pragmatic Constraints
From RAGS to RICHES: exploiting the potential of a flexible generation architecture
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Natural Language Engineering
Modelling control in generation
ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation
Towards personality-based user adaptation: psychologically informed stylistic language generation
User Modeling and User-Adapted Interaction
Instance-based natural language generation
Natural Language Engineering
An extractive supervised two-stage method for sentence compression
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Phrase-based statistical language generation using graphical models and active learning
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Towards a programmable instrumented generator
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Finding common ground: towards a surface realisation shared task
INLG '10 Proceedings of the 6th International Natural Language Generation Conference
Controlling user perceptions of linguistic style: Trainable generation of personality traits
Computational Linguistics
SemScribe: automatic generation of medical reports
USAB'11 Proceedings of the 7th conference on Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society: information Quality in e-Health
Information Processing and Management: an International Journal
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In this paper we present a new approach to controlling the behaviour of a natural language generation system by correlating internal decisions taken during free generation of a wide range of texts with the surface stylistic characteristics of the resulting outputs, and using the correlation to control the generator. This contrasts with the generate-and-test architecture adopted by most previous empirically-based generation approaches, offering a more efficient, generic and holistic method of generator control. We illustrate the approach by describing a system in which stylistic variation (in the sense of Biber (1988)) can be effectively controlled during the generation of short medical information texts.