Getting the message across in RST-based text generation
Current research in natural language generation
Informational redundancy and resource bounds in dialogue
Informational redundancy and resource bounds in dialogue
Improvising linguistic style: social and affective bases for agent personality
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Building natural language generation systems
Building natural language generation systems
The automated design of believable dialogues for animated presentation teams
Embodied conversational agents
Generating Natural Language under Pragmatic Constraints
Generating Natural Language under Pragmatic Constraints
User Modeling and User-Adapted Interaction
Stylistic Decision-Making in Natural Language Generation
EWNLG '93 Selected papers from the Fourth European Workshop on Trends in Natural Language Generation, An Artificial Intelligence Perspective
Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents
User Modeling and User-Adapted Interaction
Intentional influences on object redescriptions in dialogue: evidence from an empirical study
Intentional influences on object redescriptions in dialogue: evidence from an empirical study
A fast and portable realizer for text generation systems
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Learning optimal dialogue strategies: a case study of a spoken dialogue agent for email
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Generation that exploits corpus-based statistical knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Exploiting a probabilistic hierarchical model for generation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
A flexible pragmatics-driven language generator for animated agents
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Evaluating a trainable sentence planner for a spoken dialogue system
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Bootstrapping lexical choice via multiple-sequence alignment
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Trainable sentence planning for complex information presentation in spoken dialog systems
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Predicting student emotions in computer-human tutoring dialogues
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Empirically-based control of natural language generation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Learning to say it well: reranking realizations by predicted synthesis quality
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
ACM Transactions on Speech and Language Processing (TSLP)
Modeling self-efficacy in intelligent tutoring systems: An inductive approach
User Modeling and User-Adapted Interaction
Natural Language Engineering
The Politeness Effect: Pedagogical Agents and Learning Gains
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Optimizing dialogue management with reinforcement learning: experiments with the NJFun system
Journal of Artificial Intelligence Research
Individual and domain adaptation in sentence planning for dialogue
Journal of Artificial Intelligence Research
Using linguistic cues for the automatic recognition of personality in conversation and text
Journal of Artificial Intelligence Research
Database-text alignment via structured multilabel classification
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Stylistic variation in multilingual instructions
INLG '94 Proceedings of the Seventh International Workshop on Natural Language Generation
Individuality and alignment in generated dialogues
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Towards personality-based user adaptation: psychologically informed stylistic language generation
User Modeling and User-Adapted Interaction
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
Don't scratch! self-adaptors reflect emotional stability
IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
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
Perceived or not perceived: film character models for expressive NLG
ICIDS'11 Proceedings of the 4th international conference on Interactive Digital Storytelling
Proceedings of the 8th ACM/IEEE international conference on Human-robot interaction
Information Processing and Management: an International Journal
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Recent work in natural language generation has begun to take linguistic variation into account, developing algorithms that are capable of modifying the system's linguistic style based either on the user's linguistic style or other factors, such as personality or politeness. While stylistic control has traditionally relied on handcrafted rules, statistical methods are likely to be needed for generation systems to scale to the production of the large range of variation observed in human dialogues. Previous work on statistical natural language generation (SNLG) has shown that the grammaticality and naturalness of generated utterances can be optimized from data; however these data-driven methods have not been shown to produce stylistic variation that is perceived by humans in the way that the system intended. This paper describes Personage, a highly parameterizable language generator whose parameters are based on psychological findings about the linguistic reflexes of personality. We present a novel SNLG method which uses parameter estimation models trained on personality-annotated data to predict the generation decisions required to convey any combination of scalar values along the five main dimensions of personality. A human evaluation shows that parameter estimation models produce recognizable stylistic variation along multiple dimensions, on a continuous scale, and without the computational cost incurred by overgeneration techniques.