(Almost) Unsupervised Grammatical Error Correction using Synthetic Comparable Corpus

WS 2019  ·  Satoru Katsumata, Mamoru Komachi ·

We introduce unsupervised techniques based on phrase-based statistical machine translation for grammatical error correction (GEC) trained on a pseudo learner corpus created by Google Translation. We verified our GEC system through experiments on a low resource track of the shared task at BEA2019... As a result, we achieved an F0.5 score of 28.31 points with the test data. read more

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