@inproceedings{bunescu-uduehi-2022-distribution,
title = "Distribution-Based Measures of Surprise for Creative Language: Experiments with Humor and Metaphor",
author = "Bunescu, Razvan C. and
Uduehi, Oseremen O.",
editor = "Ghosh, Debanjan and
Beigman Klebanov, Beata and
Muresan, Smaranda and
Feldman, Anna and
Poria, Soujanya and
Chakrabarty, Tuhin",
booktitle = "Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.flp-1.10",
doi = "10.18653/v1/2022.flp-1.10",
pages = "68--78",
abstract = "Novelty or surprise is a fundamental attribute of creative output. As such, we postulate that a writer{'}s creative use of language leads to word choices and, more importantly, corresponding semantic structures that are unexpected for the reader. In this paper we investigate measures of surprise that rely solely on word distributions computed by language models and show empirically that creative language such as humor and metaphor is strongly correlated with surprise. Surprisingly at first, information content is observed to be at least as good a predictor of creative language as any of the surprise measures investigated. However, the best prediction performance is obtained when information and surprise measures are combined, showing that surprise measures capture an aspect of creative language that goes beyond information content.",
}
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<abstract>Novelty or surprise is a fundamental attribute of creative output. As such, we postulate that a writer’s creative use of language leads to word choices and, more importantly, corresponding semantic structures that are unexpected for the reader. In this paper we investigate measures of surprise that rely solely on word distributions computed by language models and show empirically that creative language such as humor and metaphor is strongly correlated with surprise. Surprisingly at first, information content is observed to be at least as good a predictor of creative language as any of the surprise measures investigated. However, the best prediction performance is obtained when information and surprise measures are combined, showing that surprise measures capture an aspect of creative language that goes beyond information content.</abstract>
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%0 Conference Proceedings
%T Distribution-Based Measures of Surprise for Creative Language: Experiments with Humor and Metaphor
%A Bunescu, Razvan C.
%A Uduehi, Oseremen O.
%Y Ghosh, Debanjan
%Y Beigman Klebanov, Beata
%Y Muresan, Smaranda
%Y Feldman, Anna
%Y Poria, Soujanya
%Y Chakrabarty, Tuhin
%S Proceedings of the 3rd Workshop on Figurative Language Processing (FLP)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F bunescu-uduehi-2022-distribution
%X Novelty or surprise is a fundamental attribute of creative output. As such, we postulate that a writer’s creative use of language leads to word choices and, more importantly, corresponding semantic structures that are unexpected for the reader. In this paper we investigate measures of surprise that rely solely on word distributions computed by language models and show empirically that creative language such as humor and metaphor is strongly correlated with surprise. Surprisingly at first, information content is observed to be at least as good a predictor of creative language as any of the surprise measures investigated. However, the best prediction performance is obtained when information and surprise measures are combined, showing that surprise measures capture an aspect of creative language that goes beyond information content.
%R 10.18653/v1/2022.flp-1.10
%U https://aclanthology.org/2022.flp-1.10
%U https://doi.org/10.18653/v1/2022.flp-1.10
%P 68-78
Markdown (Informal)
[Distribution-Based Measures of Surprise for Creative Language: Experiments with Humor and Metaphor](https://aclanthology.org/2022.flp-1.10) (Bunescu & Uduehi, Fig-Lang 2022)
ACL