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Czech Grammar Error Correction with a Large and Diverse Corpus

Jakub Náplava, Milan Straka, Jana Straková, Alexandr Rosen

2022Transactions of the Association for Computational Linguistics11 citationsDOIOpen Access PDF

Abstract

Abstract We introduce a large and diverse Czech corpus annotated for grammatical error correction (GEC) with the aim to contribute to the still scarce data resources in this domain for languages other than English. The Grammar Error Correction Corpus for Czech (GECCC) offers a variety of four domains, covering error distributions ranging from high error density essays written by non-native speakers, to website texts, where errors are expected to be much less common. We compare several Czech GEC systems, including several Transformer-based ones, setting a strong baseline to future research. Finally, we meta-evaluate common GEC metrics against human judgments on our data. We make the new Czech GEC corpus publicly available under the CC BY-SA 4.0 license at http://hdl.handle.net/11234/1-4639.

Topics & Concepts

CzechComputer scienceNatural language processingGrammarArtificial intelligenceBaseline (sea)Variety (cybernetics)Error detection and correctionDomain (mathematical analysis)LicenseLinguisticsAnnotationSpeech recognitionError analysisLanguage modelText corpusTraining setNatural Language Processing TechniquesText Readability and SimplificationAuthorship Attribution and Profiling
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