%0 Conference Proceedings %T Misspelling Oblivious Word Embeddings %A Piktus, Aleksandra %A Edizel, Necati Bora %A Bojanowski, Piotr %A Grave, Edouard %A Ferreira, Rui %A Silvestri, Fabrizio %Y Burstein, Jill %Y Doran, Christy %Y Solorio, Thamar %S Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) %D 2019 %8 June %I Association for Computational Linguistics %C Minneapolis, Minnesota %F piktus-etal-2019-misspelling %X In this paper we present a method to learn word embeddings that are resilient to misspellings. Existing word embeddings have limited applicability to malformed texts, which contain a non-negligible amount of out-of-vocabulary words. We propose a method combining FastText with subwords and a supervised task of learning misspelling patterns. In our method, misspellings of each word are embedded close to their correct variants. We train these embeddings on a new dataset we are releasing publicly. Finally, we experimentally show the advantages of this approach on both intrinsic and extrinsic NLP tasks using public test sets. %R 10.18653/v1/N19-1326 %U https://aclanthology.org/N19-1326 %U https://doi.org/10.18653/v1/N19-1326 %P 3226-3234