AI

Optimizing Touchscreen Keyboards for Gesture Typing

Abstract

Despite its growing popularity, gesture typing suffers from a major problem not present in touch typing: gesture ambiguity on the Qwerty keyboard. By applying rigorous mathematical optimization methods, this paper systematically investigates the optimization space related to the accuracy, speed, and Qwerty similarity of a gesture typing keyboard. Our investigation shows that optimizing the layout for gesture clarity (a metric measuring how unique word gestures are on a keyboard) drastically improves the accuracy of gesture typing. Moreover, if we also accommodate gesture speed, or both gesture speed and Qwerty similarity, we can still reduce error rates by 52% and 37% over Qwerty, respectively. In addition to investigating the optimization space, this work contributes a set of optimized layouts such as GK-D and GK-T that can immediately benefit mobile device users.