Class-based n-gram models of natural language
Computational Linguistics
The rôle of natural language processing in alternative and augmentative communication
Natural Language Engineering
Semantic knowledge in word completion
Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility
Topic modeling in fringe word prediction for AAC
Proceedings of the 11th international conference on Intelligent user interfaces
Text prediction systems: a survey
Universal Access in the Information Society
The effects of word prediction on communication rate for AAC
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
User Interaction with Word Prediction: The Effects of Prediction Quality
ACM Transactions on Accessible Computing (TACCESS)
Critically analyzing workplace discourse to inform AAC device design
ACM SIGACCESS Accessibility and Computing
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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 variations 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 communication rate higher than is explained by the additional accuracy of the system alone due to better utilization (93.6% utilization for advanced vs. 78.2% for basic).