Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866914549331918848 |
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| author | Hilasaca, Kenji Khallaf, Nouran Sharoff, Serge |
| author_facet | Hilasaca, Kenji Khallaf, Nouran Sharoff, Serge |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2605_09476 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification Hilasaca, Kenji Khallaf, Nouran Sharoff, Serge Computation and Language Artificial Intelligence I.2.7; I.2.6 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. |
| title | Align and Shine: Building High-Quality Sentence-Aligned Corpora for Multilingual Text Simplification |
| topic | Computation and Language Artificial Intelligence I.2.7; I.2.6 |
| url | https://arxiv.org/abs/2605.09476 |