User Modelling for Error Recovery: A Spelling Checker for Dyslexic Users

Abstract

In the pursuit of a remedy for the poor spelling of dyslexic writers, a software system has been developed which features centrally a user model of the writer’s spelling error patterns. Dyslexic writers are poorly catered for by most spelling programs because of their diverse errors. In this system, Babel, a user model directs the search towards likely corrections considering the writer’s common errors. Babel includes the novel idea of more complex rules which describe permutations of errors typically made by dyslexic writers. It also measures and improves the accuracy of its user model using as feedback the choices made from its list of suggestions. Samples of writing from dyslexic users have been used to show successful detection and correction of typical errors, consistent between samples by the same writer and distinct from other writers. The user model allows, for some users, more diverse errors to be corrected more effectively than in systems without individual user models.