Techniques for augmenting scanning communication

TLDR

Scanning communication systems offer opportunities for augmentative communication technologies, including row‑column matrix optimization, dynamic rearrangement, and the addition of character or word lists. The authors conducted systematic experiments on 14 scanning configurations, using a common software platform and regimented testing to analyze parameters and optimize row‑column matrices for prediction lists. The best character prediction method achieved 40.5% switch savings, while the best word prediction method achieved 38.8%, both using seven‑element prediction lists and optimized row‑column matrices.

Abstract

Scanning communication systems provide a unique set of opportunities for the application of augmentative communication technologies. Possibilities include optimization of the row-column matrix, dynamic rearrangement of the matrix, addition of character or word lists, and combinations of these techniques. A series of descriptive experiments were performed to establish the switch savings performance of 14 different scanning configurations. A common software platform and a strictly regimented testing procedure were employed to ensure the reliability and consistency of the data, facilitating comparisons between the different paradigms. Within each configuration, a systematic analysis of the relevant parameters was performed. The best character prediction method provided an average switch savings of 40.5% over a baseline row-column configuration, while the best word prediction technique provided an average savings of only 38.8%. Both of these configurations used seven-element prediction lists, which did not present any predictions until after selection of the first letter of each word. Additionally, the rowcolumn matrices of these designs were optimized for use with the prediction list such that the more frequently selected matrix entries tended to be in more rapidly accessible matrix locations.