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Abstract
In this paper we investigate whether subject doubling in French is affected by the Uniform Information Density (UID) principle, which states that speakers prefer language encoding that minimizes fluctuations in information density. We show that, other factors being controlled, speakers are more likely to double the NP subject when it has a high surprisal, thus providing further empirical evidence to the UID principle which predicts a surprisal-redundancy trade-off as a property of natural languages. We argue for the importance of employing GPT-2 to investigate complex linguistic phenomena such as subject doubling, as it enables the estimation of subject surprisal by considering a rather large conversational context, a task made possible by powerful language models that incorporate linguistic knowledge through pre-training on extensive datasets.
Keywords
Uniform Information Density, subject doubling, spoken French, syntactic redundancy, surprisal

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MLA
Liang, Yiming, et al. “Uniform Information Density Explains Subject Doubling in French.” Proceedings of the 46th Annual Conference of the Cognitive Science Society, vol. 46, 2024, pp. 780–88.
APA
Liang, Y., Amsili, P., Burnett, H., & Demberg, V. (2024). Uniform information density explains subject doubling in French. Proceedings of the 46th Annual Conference of the Cognitive Science Society, 46, 780–788.
Chicago author-date
Liang, Yiming, Pascal Amsili, Heather Burnett, and Vera Demberg. 2024. “Uniform Information Density Explains Subject Doubling in French.” In Proceedings of the 46th Annual Conference of the Cognitive Science Society, 46:780–88.
Chicago author-date (all authors)
Liang, Yiming, Pascal Amsili, Heather Burnett, and Vera Demberg. 2024. “Uniform Information Density Explains Subject Doubling in French.” In Proceedings of the 46th Annual Conference of the Cognitive Science Society, 46:780–788.
Vancouver
1.
Liang Y, Amsili P, Burnett H, Demberg V. Uniform information density explains subject doubling in French. In: Proceedings of the 46th Annual Conference of the Cognitive Science Society. 2024. p. 780–8.
IEEE
[1]
Y. Liang, P. Amsili, H. Burnett, and V. Demberg, “Uniform information density explains subject doubling in French,” in Proceedings of the 46th Annual Conference of the Cognitive Science Society, Rotterdam, The Netherlands, 2024, vol. 46, pp. 780–788.
@inproceedings{01J3ZH4C14VQ9VDYS2ZCBSN53S,
  abstract     = {{In this paper we investigate whether subject doubling in French is affected by the Uniform Information Density (UID) principle, which states that speakers prefer language encoding that minimizes fluctuations in information density. We show that, other factors being controlled, speakers are more likely to double the NP subject when it has a high surprisal, thus providing further empirical evidence to the UID principle which predicts a surprisal-redundancy trade-off as a property of natural languages. We argue for the importance of employing GPT-2 to investigate complex linguistic phenomena such as subject doubling, as it enables the estimation of subject surprisal by considering a rather large conversational context, a task made possible by powerful language models that incorporate linguistic knowledge through pre-training on extensive datasets.}},
  author       = {{Liang, Yiming and Amsili, Pascal and Burnett, Heather and Demberg, Vera}},
  booktitle    = {{Proceedings of the 46th Annual Conference of the Cognitive Science Society}},
  issn         = {{1069-7977}},
  keywords     = {{Uniform Information Density,subject doubling,spoken French,syntactic redundancy,surprisal}},
  language     = {{eng}},
  location     = {{Rotterdam, The Netherlands}},
  pages        = {{780--788}},
  title        = {{Uniform information density explains subject doubling in French}},
  url          = {{https://escholarship.org/uc/item/645673fs}},
  volume       = {{46}},
  year         = {{2024}},
}