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    <abstract>We present experiments on biomedical text simplification in French. We use two kinds of corpora – parallel sentences extracted from existing health comparable corpora in French and WikiLarge corpus translated from English to French – and a lexicon that associates medical terms with paraphrases. Then, we train neural models on these parallel corpora using different ratios of general and specialized sentences. We evaluate the results with BLEU, SARI and Kandel scores. The results point out that little specialized data helps significantly the simplification.</abstract>
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%0 Conference Proceedings
%T French Biomedical Text Simplification: When Small and Precise Helps
%A Cardon, Rémi
%A Grabar, Natalia
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F cardon-grabar-2020-french
%X We present experiments on biomedical text simplification in French. We use two kinds of corpora – parallel sentences extracted from existing health comparable corpora in French and WikiLarge corpus translated from English to French – and a lexicon that associates medical terms with paraphrases. Then, we train neural models on these parallel corpora using different ratios of general and specialized sentences. We evaluate the results with BLEU, SARI and Kandel scores. The results point out that little specialized data helps significantly the simplification.
%R 10.18653/v1/2020.coling-main.62
%U https://aclanthology.org/2020.coling-main.62
%U https://doi.org/10.18653/v1/2020.coling-main.62
%P 710-716

Markdown (Informal)

[French Biomedical Text Simplification: When Small and Precise Helps](https://aclanthology.org/2020.coling-main.62) (Cardon & Grabar, COLING 2020)

• French Biomedical Text Simplification: When Small and Precise Helps (Cardon & Grabar, COLING 2020)

ACL

• Rémi Cardon and Natalia Grabar. 2020. French Biomedical Text Simplification: When Small and Precise Helps. In Proceedings of the 28th International Conference on Computational Linguistics, pages 710–716, Barcelona, Spain (Online). International Committee on Computational Linguistics.