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        <namePart type="given">Zhichao</namePart>
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            <title>Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue</title>
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        <name type="personal">
            <namePart type="given">Kazunori</namePart>
            <namePart type="family">Komatani</namePart>
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            <namePart type="given">Diane</namePart>
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    <abstract>Previous work has shown that conversants adapt to many aspects of their partners’ language. Other work has shown that while every person is unique, they often share general patterns of behavior. Theories of personality aim to explain these shared patterns, and studies have shown that many linguistic cues are correlated with personality traits. We propose an adaptation measure for adaptive natural language generation for dialogs that integrates the predictions of both personality theories and adaptation theories, that can be applied as a dialog unfolds, on a turn by turn basis. We show that our measure meets criteria for validity, and that adaptation varies according to corpora and task, speaker, and the set of features used to model it. We also produce fine-grained models according to the dialog segmentation or the speaker, and demonstrate the decaying trend of adaptation.</abstract>
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%0 Conference Proceedings
%T Modeling Linguistic and Personality Adaptation for Natural Language Generation
%A Hu, Zhichao
%A Fox Tree, Jean
%A Walker, Marilyn
%Y Komatani, Kazunori
%Y Litman, Diane
%Y Yu, Kai
%Y Papangelis, Alex
%Y Cavedon, Lawrence
%Y Nakano, Mikio
%S Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F hu-etal-2018-modeling
%X Previous work has shown that conversants adapt to many aspects of their partners’ language. Other work has shown that while every person is unique, they often share general patterns of behavior. Theories of personality aim to explain these shared patterns, and studies have shown that many linguistic cues are correlated with personality traits. We propose an adaptation measure for adaptive natural language generation for dialogs that integrates the predictions of both personality theories and adaptation theories, that can be applied as a dialog unfolds, on a turn by turn basis. We show that our measure meets criteria for validity, and that adaptation varies according to corpora and task, speaker, and the set of features used to model it. We also produce fine-grained models according to the dialog segmentation or the speaker, and demonstrate the decaying trend of adaptation.
%R 10.18653/v1/W18-5003
%U https://aclanthology.org/W18-5003
%U https://doi.org/10.18653/v1/W18-5003
%P 20-31

Markdown (Informal)

[Modeling Linguistic and Personality Adaptation for Natural Language Generation](https://aclanthology.org/W18-5003) (Hu et al., SIGDIAL 2018)

• Modeling Linguistic and Personality Adaptation for Natural Language Generation (Hu et al., SIGDIAL 2018)

ACL

• Zhichao Hu, Jean Fox Tree, and Marilyn Walker. 2018. Modeling Linguistic and Personality Adaptation for Natural Language Generation. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 20–31, Melbourne, Australia. Association for Computational Linguistics.