@inproceedings{asghari-hewett-2022-hiig,
title = "{HIIG} at {G}erm{E}val 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment",
author = "Asghari, Hadi and
Hewett, Freya",
editor = {M{\"o}ller, Sebastian and
Mohtaj, Salar and
Naderi, Babak},
booktitle = "Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text",
month = sep,
year = "2022",
address = "Potsdam, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.germeval-1.3",
pages = "15--20",
abstract = "In this paper we explain HIIG{'}s contribution to the shared task Text Complexity DE Challenge 2022. Our best-performing model for the task of automatically determining the complexity level of a German-language sentence is a combination of a transformer model and a classic feature-based model, which achieves a mapped root square mean error of 0.446 on the test data.",
}
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%0 Conference Proceedings
%T HIIG at GermEval 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment
%A Asghari, Hadi
%A Hewett, Freya
%Y Möller, Sebastian
%Y Mohtaj, Salar
%Y Naderi, Babak
%S Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text
%D 2022
%8 September
%I Association for Computational Linguistics
%C Potsdam, Germany
%F asghari-hewett-2022-hiig
%X In this paper we explain HIIG’s contribution to the shared task Text Complexity DE Challenge 2022. Our best-performing model for the task of automatically determining the complexity level of a German-language sentence is a combination of a transformer model and a classic feature-based model, which achieves a mapped root square mean error of 0.446 on the test data.
%U https://aclanthology.org/2022.germeval-1.3
%P 15-20
Markdown (Informal)
[HIIG at GermEval 2022: Best of Both Worlds Ensemble for Automatic Text Complexity Assessment](https://aclanthology.org/2022.germeval-1.3) (Asghari & Hewett, GermEval 2022)
ACL