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	title        = {Swedish MuClaGED: A new dataset for Grammatical Error Detection in Swedish},
	abstract     = {This paper introduces the Swedish MuClaGED dataset, a new dataset specifically built for the task of Multi-Class Grammatical Error Detection (GED). The dataset has been produced as a part of the multilingual Computational  SLA shared  task  initiative. In  this paper we elaborate on the generation process and the design choices made to obtain Swedish MuClaGED. We also show initial baseline results for the performance on the  dataset in a task of Grammatical Error Detection and Classification on the sentence level, which have been obtained through (Bi)LSTM ((Bidirectional) Long-Short Term Memory) methods.},
	booktitle    = {Proceedings of the 11th Workshop on Natural Language Processing for Computer-Assisted Language Learning (NLP4CALL 2022) },
	author       = {Casademont Moner , Judit and Volodina, Elena},
	year         = {2022},
	publisher    = {Linköping Electronic Conference Proceedings 190 / NEALT Proceedings Series 47},
	address      = {Linköping, Sweden},
	ISBN         = {978-91-7929-460-1},