@inproceedings{eder-etal-2023-question,
title = "A Question of Style: A Dataset for Analyzing Formality on Different Levels",
author = "Eder, Elisabeth and
Krieg-Holz, Ulrike and
Wiegand, Michael",
editor = "Vlachos, Andreas and
Augenstein, Isabelle",
booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-eacl.42",
doi = "10.18653/v1/2023.findings-eacl.42",
pages = "580--593",
abstract = "Accounting for different degrees of formality is crucial for producing contextually appropriate language. To assist NLP applications concerned with this problem and formality analysis in general, we present the first dataset of sentences from a wide range of genres assessed on a continuous informal-formal scale via comparative judgments. It is the first corpus with a comprehensive perspective on German sentence-level formality overall. We compare machine learning models for formality scoring, a task we treat as a regression problem, on our dataset. Finally, we investigate the relation between sentence- and document-level formality and evaluate leveraging sentence-based annotations for assessing formality on documents.",
}
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%0 Conference Proceedings
%T A Question of Style: A Dataset for Analyzing Formality on Different Levels
%A Eder, Elisabeth
%A Krieg-Holz, Ulrike
%A Wiegand, Michael
%Y Vlachos, Andreas
%Y Augenstein, Isabelle
%S Findings of the Association for Computational Linguistics: EACL 2023
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F eder-etal-2023-question
%X Accounting for different degrees of formality is crucial for producing contextually appropriate language. To assist NLP applications concerned with this problem and formality analysis in general, we present the first dataset of sentences from a wide range of genres assessed on a continuous informal-formal scale via comparative judgments. It is the first corpus with a comprehensive perspective on German sentence-level formality overall. We compare machine learning models for formality scoring, a task we treat as a regression problem, on our dataset. Finally, we investigate the relation between sentence- and document-level formality and evaluate leveraging sentence-based annotations for assessing formality on documents.
%R 10.18653/v1/2023.findings-eacl.42
%U https://aclanthology.org/2023.findings-eacl.42
%U https://doi.org/10.18653/v1/2023.findings-eacl.42
%P 580-593
Markdown (Informal)
[A Question of Style: A Dataset for Analyzing Formality on Different Levels](https://aclanthology.org/2023.findings-eacl.42) (Eder et al., Findings 2023)
ACL