We used the Levenshtein distance metric BIBREF8 implemented in Apache Lucene library BIBREF9 . Another simple approach is the aforementioned diacritical swapping, which is a term that we introduce here for referring to a solution inspired by the work of BIBREF4 . A promising method, adapted from work on correcting texts by English language learners BIBREF11 , expands on the concept of selecting a correction nearest to the spelling error according to some notion of distance. Here, the Levenshtein distance is used in a weighted sum to cosine distance between word vectors. Our ELMo-augmented LSTM is bidirectional. 
 Question: What methods are tested in PIEWi?
Levenshtein distance metric BIBREF8 diacritical swapping Levenshtein distance is used in a weighted sum to cosine distance between word vectors ELMo-augmented LSTM