arXiv Open Access 2023

Exploring Automatic Text Simplification of German Narrative Documents

Thorben Schomacker Tillmann Dönicke Marina Tropmann-Frick

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Abstrak

In this paper, we apply transformer-based Natural Language Generation (NLG) techniques to the problem of text simplification. Currently, there are only a few German datasets available for text simplification, even fewer with larger and aligned documents, and not a single one with narrative texts. In this paper, we explore to which degree modern NLG techniques can be applied to German narrative text simplifications. We use Longformer attention and a pre-trained mBART model. Our findings indicate that the existing approaches for German are not able to solve the task properly. We conclude on a few directions for future research to address this problem.

Topik & Kata Kunci

cs.CL cs.AI

Penulis (3)

Thorben Schomacker

Tillmann Dönicke

Marina Tropmann-Frick

Format Sitasi

APA MLA BibTeX

Schomacker, T., Dönicke, T., Tropmann-Frick, M. (2023). Exploring Automatic Text Simplification of German Narrative Documents. https://arxiv.org/abs/2312.09907

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓