PoliSpell: An Adaptive Spellchecker and Predictor for People with Dyslexia. Quattrini Li, A., Sbattella, L., & Tedesco, R. In 21st Conference on User Modeling, Adaptation and Personalization (UMAP), pages 302-309, 2013.
PoliSpell: An Adaptive Spellchecker and Predictor for People with Dyslexia [link]Paper  abstract   bibtex   
People with dyslexia often face huge writing difficulties. Spellcheckers/predictors can help, but the current systems are not appropriate for them, because of the assumptions behind the models and because of heavy-to-use interfaces. This paper presents a system for spellchecking/predicting words, which can adapt both its model and its interface according to the individual behavior. The model takes into account typical errors made by people with dyslexia, such as boundary errors, and the context for correcting real-word errors. The interface aims at reducing interaction with the user. The model and the interface are easily adaptable to general use.
@inproceedings{quattrinili2013umap,
  author = {Alberto {Quattrini Li} and Licia Sbattella and Roberto Tedesco},
  booktitle = {21st Conference on User Modeling, Adaptation and Personalization (UMAP)},
  title = {{PoliSpell}: An Adaptive Spellchecker and Predictor for People with Dyslexia},
  year = {2013},
  pages = {302-309},
  url = {https://doi.org/10.1007/978-3-642-38844-6_27},
  abstract = {People with dyslexia often face huge writing difficulties. Spellcheckers/predictors can help, but the current systems are not appropriate for them, because of the assumptions behind the models and because of heavy-to-use interfaces. This paper presents a system for spellchecking/predicting words, which can adapt both its model and its interface according to the individual behavior. The model takes into account typical errors made by people with dyslexia, such as boundary errors, and the context for correcting real-word errors. The interface aims at reducing interaction with the user. The model and the interface are easily adaptable to general use.},
  keywords = {spellchecker, predictor, dyslexia, adaptive system}
}

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