Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task

north american chapter of the association for computational linguistics, pp. 595-606, 2018.

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Abstract:

Previously, neural methods in grammatical error correction (GEC) did not reach state-of-the-art results compared to phrase-based statistical machine translation (SMT) baselines. We demonstrate parallels between neural GEC and low-resource neural MT and successfully adapt several methods from low-resource MT to neural GEC. We further estab...More

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