The lack of large-scale datasets has been a major hindrance to the
development of NLP tasks such as spelling correction and grammatical error
correction (GEC). As a complementary new resource for these tasks, we present
the GitHub Typo Corpus, a large-scale, multilingual dataset of misspellings and
grammatical errors along with their corrections harvested from GitHub, a large
and popular platform for hosting and sharing git repositories. The dataset,
which we have made publicly available, contains more than 350k edits and 65M
characters in more than 15 languages, making it the largest dataset of
misspellings to date. We also describe our process for filtering true typo
edits based on learned classifiers on a small annotated subset, and demonstrate
that typo edits can be identified with F1 ~ 0.9 using a very simple classifier
with only three features. The detailed analyses of the dataset show that
existing spelling correctors merely achieve an F-measure of approx. 0.5,
suggesting that the dataset serves as a new, rich source of spelling errors
that complement existing datasets.

该研究介绍了一种新的语料库，即 GitHub Typo Corpus，旨在提供全球最大的单词拼写错误和语法错误数据集，以帮助 NLP 任务。基于该数据集的初步研究结果表明，该数据集可以作为一个新的拼写错误数据源，补充现有的数据集。