Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction

EMNLP, pp. 1546-1556, 2016.

Cited by: 67|Views23
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Abstract:

In this work, we study parameter tuning towards the M^2 metric, the standard metric for automatic grammar error correction (GEC) tasks. After implementing M^2 as a scorer in the Moses tuning framework, we investigate interactions of dense and sparse features, different optimizers, and tuning strategies for the CoNLL-2014 shared task. We n...More

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