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arXiv · 2605.09476

Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification

Kenji Hilasaca·Nouran Khallaf·Serge Sharoff
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Abstract

Text simplification plays a crucial role in improving the accessibility and comprehensibility of written information for diverse audiences, including language learners and readers with limited literacy. Despite its importance, large-scale, high-quality datasets for training and evaluating text simplification models remain scarce for languages other than English. This paper reports an experimental study on the collection and processing of crowd-sourced simplification data from comparable corpora to construct a corpus suitable for both training and testing text simplification systems across multiple languages (Catalan, English, French, Italian and Spanish). We report mechanisms for sentence-level alignment from document-level data. The resulting dataset of the aligned sentence pairs is publicly available.

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Kenji Hilasaca, Nouran Khallaf, Serge Sharoff. 2026-05-10. Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification. https://arxiv.org/abs/2605.09476

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