@article{Heyman_Vuli´c_Laevaert_Moens_2018, title={Automatic detection and correction of context-dependent dt-mistakes using neural networks}, volume={8}, url={https://clinjournal.org/clinj/article/view/79}, abstractNote={<p>We introduce a novel approach to correcting context-dependent dt-mistakes, one of the most frequent spelling errors in the Dutch language. We show that by using a neural network to estimate the probability distribution of a verb’s suffix conditioned jointly on its stem and context, we obtain large improvements over state-of-the-art spell checkers on three different benchmarking datasets, achieving a perfect score on a verb spelling test from de Standaard, a Flemish newspaper. The method is unsupervised and only relies on basic preprocessing tools to tokenize the text and identify verbs, which enables training on millions of sentences. Furthermore, we propose a method to determine which words in a sentence cause the system to make corrections, which is valuable for providing feedback to the user.</p>}, journal={Computational Linguistics in the Netherlands Journal}, author={Heyman, Geert and Vuli´c, Ivan and Laevaert, Yannick and Moens, Marie-Francine}, year={2018}, month={Dec.}, pages={49–65} }