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arXiv · 2312.09966

Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communication

Thorben Schomacker·Michael Gille·Jörg von der Hülls·Marina Tropmann-Frick
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Abstract

This paper examines the current state-of-the-art of German text simplification, focusing on parallel and monolingual German corpora. It reviews neural language models for simplifying German texts and assesses their suitability for legal texts and accessibility requirements. Our findings highlight the need for additional training data and more appropriate approaches that consider the specific linguistic characteristics of German, as well as the importance of the needs and preferences of target groups with cognitive or language impairments. The authors launched the interdisciplinary OPEN-LS project in April 2023 to address these research gaps. The project aims to develop a framework for text formats tailored to individuals with low literacy levels, integrate legal texts, and enhance comprehensibility for those with linguistic or cognitive impairments. It will also explore cost-effective ways to enhance the data with audience-specific illustrations using image-generating AI. For more and up-to-date information, please visit our project homepage https://open-ls.entavis.com

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Thorben Schomacker, Michael Gille, Jörg von der Hülls, Marina Tropmann-Frick. 2023-12-15. Data and Approaches for German Text simplification -- towards an Accessibility-enhanced Communication. https://arxiv.org/abs/2312.09966

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