Automatic Grammar Correction of Commas in Czech Written Texts : Comparative Study



Year of publication 2022
Type Article in Proceedings
Conference Text, Speech, and Dialogue : 25th International Conference, TSD 2022, Brno, Czech Republic, September 6–9, 2022, Proceedings
MU Faculty or unit

Faculty of Arts

Web Conference paper
Keywords Grammatical error correction; Linguistic rules; Transfer learning
Description The task of grammatical error correction is a widely studied field of natural language processing where the traditional rule-based approaches compete with the machine learning methods. The rule-based approach benefits mainly from a wide knowledge base available for a given language. On the contrary, the transfer learning methods and especially the use of pre-trained Transformers have the ability to be trained from a huge number of texts in a given language. In this paper, we focus on the task of automatic correction of missing commas in Czech written texts and we compare the rule-based approach with the Transformer-based model trained for this task.
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