Abstract

The authoring of meaningful sentences is an essential requirement for AAC systems aimed at the education of children with complex communication needs. Some studies propose the use of linguistic knowledge databases to meet that requirement. In this paper, we propose and present a Semantic Grammar (SG) for AAC systems based on visual and semantic clues. The proposed SG was acquired using an automatic process based on Natural Language Processing (NLP) techniques for the extraction of semantic relations from text samples. We assessed the SG precision on suggesting the correct words on reconstructing telegraphic sentences and obtained a precision average of 90%.

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