Motor input assistance
Peter Parente
just two weeks ago. They might be of interest when brainstorming about
innovation in OSK.
Indirect text entry using one or two keys
ABSTRACT
This paper introduces a new descriptive model for indirect text
composition facilities that is based on the notion of a containment
hierarchy. This paper also demonstrates a novel, computer-aided
technique for the design of indirect text selection interfaces -- one
in which Huffman coding is used for the derivation of the containment
hierarchy. This approach guarantees the derivation of optimal
containment hierarchies, insofar as mean encoding length. This paper
describes an empirical study of two two-key indirect text entry
variants and compares them to one another and to the predictive model.
The intended application of these techniques is the design of improved
indirect text entry facilities for the users of AAC systems.
http://doi.acm.org/10.1145/1168987.1168992
>From letters to words: efficient stroke-based word completion for
trackball text entry
ABSTRACT
We present a major extension to our previous work on Trackball
EdgeWrite--a unistroke text entry method for trackballs--by taking it
from a character-level technique to a word-level one. Our design is
called stroke-based word completion, and it enables efficient word
selection as part of the stroke-making process. Unlike most word
completion designs, which require users to select words from a list,
our technique allows users to select words by performing a fluid
crossing gesture. Our theoretical model shows this word-level design to
be 45.0% faster than our prior model for character-only strokes. A
study with a subject with spinal cord injury comparing Trackball
EdgeWrite to the onscreen keyboard WiViK, both using word prediction
and completion, shows that Trackball EdgeWrite is competitive with
WiViK in speed (12.09 vs. 11.82 WPM) and accuracy (3.95% vs. 2.21%
total errors), but less visually tedious and ultimately preferred. The
results also show that word-level Trackball EdgeWrite is 46.5% faster
and 36.7% more accurate than our subject's prior peak performance with
character-level Trackball EdgeWrite, and 75.2% faster and 40.2% more
accurate than his prior peak performance with his preferred on-screen
keyboard. An additional evaluation of the same subject over a two-month
field deployment shows a 43.9% reduction in unistrokes due to
strokebased word completion in Trackball EdgeWrite.