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We applied two standard, open source tools for detecting spelling and grammar errors to the AESW 2016 shared task: After the Deadline and LanguageTool. The tools’ output was combined with a Maximum Entropy machine learning model to classify each input sentence as requiring or not requiring any edits. This approach yielded the second-highest precision of 64.41% in the binary estimation task at AESW 2016, but also the lowest recall of 36.85%, resulting in an F-Measure of 46.34%.

Combining Off-the-shelf Grammar and Spelling Tools for the Automatic Evaluation of Scientific Writing (AESW) Shared Task 2016