Word Prediction and Communication Rate in AAC

K. Trnka, J. McCaw, D. Yarrington, K.F. McCoy, and C. Pennington (USA)


Natural Language Processing, Word Prediction, AAC, Communication Rate


Word prediction systems can reduce the number of keystrokes required to form a message in a letter-based AAC system. It has been questioned, however, whether such savings translate into an enhanced communication rate due to the additional overhead (e.g., shifting of focus and repeated scanning of a prediction list) required in using such a system. Our hypothesis is that word prediction has high potential for enhancing AAC communication rate, but the amount is dependent in a complex way on the accuracy of the predictions. Due to significant user interface varia tions in AAC systems and the potential bias of prior word prediction experience on existing devices, this hypothesis is difficult to verify. We present a study of two different word prediction methods compared against letter-by-letter entry at simulated AAC communication rates. We find that word prediction systems can in fact speed communication rate (an advanced system gave a 58.6% improvement), and that a more accurate word prediction system can raise commu nication rate higher than is explained by the additional ac curacy of the system alone due to better utilization (93.6% utilization for advanced vs. 78.2% for basic).

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