@inproceedings{seiffe-etal-2022-subjective,
title = "Subjective Text Complexity Assessment for {G}erman",
author = {Seiffe, Laura and
Kallel, Fares and
M{\"o}ller, Sebastian and
Naderi, Babak and
Roller, Roland},
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.74/",
pages = "707--714",
abstract = "For different reasons, text can be difficult to read and understand for many people, especially if the text`s language is too complex. In order to provide suitable text for the target audience, it is necessary to measure its complexity. In this paper we describe subjective experiments to assess the readability of German text. We compile a new corpus of sentences provided by a German IT service provider. The sentences are annotated with the subjective complexity ratings by two groups of participants, namely experts and non-experts for that text domain. We then extract an extensive set of linguistically motivated features that are supposedly interacting with complexity perception. We show that a linear regression model with a subset of these features can be a very good predictor of text complexity."
}
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%0 Conference Proceedings
%T Subjective Text Complexity Assessment for German
%A Seiffe, Laura
%A Kallel, Fares
%A Möller, Sebastian
%A Naderi, Babak
%A Roller, Roland
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Thirteenth Language Resources and Evaluation Conference
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F seiffe-etal-2022-subjective
%X For different reasons, text can be difficult to read and understand for many people, especially if the text‘s language is too complex. In order to provide suitable text for the target audience, it is necessary to measure its complexity. In this paper we describe subjective experiments to assess the readability of German text. We compile a new corpus of sentences provided by a German IT service provider. The sentences are annotated with the subjective complexity ratings by two groups of participants, namely experts and non-experts for that text domain. We then extract an extensive set of linguistically motivated features that are supposedly interacting with complexity perception. We show that a linear regression model with a subset of these features can be a very good predictor of text complexity.
%U https://aclanthology.org/2022.lrec-1.74/
%P 707-714
Markdown (Informal)
[Subjective Text Complexity Assessment for German](https://aclanthology.org/2022.lrec-1.74/) (Seiffe et al., LREC 2022)
ACL
- Laura Seiffe, Fares Kallel, Sebastian Möller, Babak Naderi, and Roland Roller. 2022. Subjective Text Complexity Assessment for German. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 707–714, Marseille, France. European Language Resources Association.