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Conference ProceedingsArtificial Intelligence & Machine Learning

Grammatical Error Correction in Low-Resource Scenarios

Jakub Náplava·Milan Straka
Workshop on Noisy User-generated Text (W-NUT)2019

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Abstract & Overview

Grammatical error correction in English is a long studied problem with many existing systems and datasets.However, there has been only a limited research on error correction of other languages.In this paper, we present a new dataset AKCES-GEC on grammatical error correction for Czech.We then make experiments on Czech, German and Russian and show that when utilizing synthetic parallel corpus, Transformer neural machine translation model can reach new state-of-the-art results on these datasets.

Cite this record

Jakub Náplava, Milan Straka (2019). Grammatical Error Correction in Low-Resource Scenarios. Workshop on Noisy User-generated Text (W-NUT). https://doi.org/10.18653/v1/d19-5545

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Náplava, J., & Straka, M. (2019). Grammatical Error Correction in Low-Resource Scenarios. Workshop on Noisy User-generated Text (W-NUT). https://doi.org/10.18653/v1/d19-5545
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