Recommending Missing Symbols of Augmentative and Alternative Communication by Means of Explicit Semantic Analysis

For people constrained to picture based communication, the expression of interest in a question answering (QA) or information retrieval (IR)scenario is highly limited. Traditionally, alternative and augmentative communication (AAC) methods (such as gestures and communication boards) are utilised. But only few systems allow users to produce whole utterances or sentences that consist of multiple words; work to generate them automatically is a promising direction in the big data context.In this paper, we provide a dedicated access method for the open-domain QA and IR context. We propose a method for the user to search for additional symbols to be added to the communication board in real-time while using access to big data sources and context based filtering when the desired symbol is missing. The user can select a symbol that is associated with the desired concept and the system searches for images on the Internet - here, in Wikipedia - with the purpose of retrieving an appropriate symbol or picture. Querying for candidates is performed by estimating semantic relatedness between text fragments using explicit semantic analysis (ESA).