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Compositional Language Modeling for Icon-Based Augmentative and Alternative Communication

Overview
Journal Proc Conf Assoc Comput Linguist Meet
Date 2021 May 3
PMID 33935351
Citations 2
Authors
Shiran Dudy
Steven Bedrick
Affiliations
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Abstract

Icon-based communication systems are widely used in the field of Augmentative and Alternative Communication. Typically, icon-based systems have lagged behind word- and character-based systems in terms of predictive typing functionality, due to the challenges inherent to training icon-based language models. We propose a method for synthesizing training data for use in icon-based language models, and explore two different modeling strategies.

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