@inproceedings{Weir2014,
	abstract = {Modern mobile devices typically rely on touchscreen keyboards for input. Unfortunately, users often struggle to enter text accurately on virtual keyboards. To address this, we present a novel decoder for touchscreen text entry that combines probabilistic touch models with a long-span language model. We investigate two touch models – one based on Gaussian Processes that implicitly models the inherent uncertainty of the touching process and a second that allows users to explicitly control the uncertainity via touch pressure. Using the first model we show that character error rate can be reduced by up to 7% over a baseline, and by up to 1.3% over a leading commercial keyboard. With the second model, we demonstrate that providing users with control over input certainty results in improved text entry rates for phrases containing out of vocabulary words.},
	title = {Uncertain Text Entry on Mobile Devices},
	author = {Weir, Daryl and Pohl, Henning and Rogers, Simon and Vertanen, Keith and Kristensson, Per Ola},
	booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
	doi = {10.1145/2556288.2557412},
	year = {2014},
	papertype = {fullpaper}
}