Abstract

Nonspeaking individuals with motor disabilities frequently rely on augmentative and alternative communication (AAC) systems that allow users to communicate through a text entry interface coupled with a speech synthesizer. Such systems are notoriously difficult to evaluate with end-users. However, recent research has proposed envelope analysis as a method to estimate text entry rates and keystroke savings by simulating the interaction of an expert surrogate user entering sentences on a conceptual word-predictive text entry system. While only a part of the evaluation process of an AAC system, this method enables AAC designers to benefit from quantitative insights early on in the design process. This paper extends prior work by (1) demonstrating how to incorporate natural language generation, such as sentence generation, in such analyses; (2) presenting a model of an imperfect surrogate user that incorporates bounded rationality, human error, and interruptions to provide a more realistic simulation of text entry behavior; and (3) demonstrating how to estimate model parameters by observing users' actual typing behavior. We validate the model with data collected from eight participants using an AAC system on a touchscreen.

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