User Interaction with Word Prediction: The Effects of Prediction Quality

  • Authors:

  • Keith Trnka;John McCaw;Debra Yarrington;Kathleen F. McCoy;Christopher Pennington

  • Affiliations:

  • University of Delaware;University of Delaware;University of Delaware;University of Delaware;AgoraNet, Inc.

  • Venue:
  • ACM Transactions on Accessible Computing (TACCESS)
  • Year:
  • 2009

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Abstract

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 the communication rate higher than is explained by the additional accuracy of the system alone due to better utilization (93.6% utilization for advanced versus 78.2% for basic).