Grammatical error correction for Spanish health records

Salvador Lima-López, Naiara Perez, Montse Cuadros


This paper describes the first approach to Grammatical Error Correction for Spanish health records. We present a series of experiments using neural networks and data augmentation, achieving 70.89 F0.5 score. Resources designed for this task are introduced, namely the IMEC corpus of corrected health records and the TMAE corpus of clinical texts augmented with errors.

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