Predictive Composition of Pictogram Messages for Users with Autism

Communication is a basic need for every person. However, there are many people who present disabilities that prevent communication through natural language. Augmentative and Alternative Communication (AAC) systems, including those based on pictograms, attempt to facilitate the communication for people with this kind of difficulties. In this paper we present PictoEditor, an Augmentative and Alternative Communication application for the composition of pictogram messages for users with autism that incorporates prediction functionalities. Although such functionalities have been widely studied in text-based Augmentative and Alternative Communication tools, they have not been applied to pictogram based ones. The results show that prediction based on frequency of use of specific pictograms improves the immediate availability of the desired pictograms, but the improvement with prediction based on sequencing of pseudo-syntactic types of pictogram is not as clear.