TY - GEN
T1 - Optimal-T9
T2 - 13th ACM International Conference on Interactive Surfaces and Spaces, ISS 2018
AU - Qin, Ryan
AU - Zhu, Suwen
AU - Lin, Yu Hao
AU - Ko, Yu Jung
AU - Bi, Xiaojun
N1 - Publisher Copyright:
© 2018 ACM.
PY - 2018/11/19
Y1 - 2018/11/19
N2 - T9-like keyboards (i.e., 3×3 layouts) have been commonly used on small touchscreen devices to mitigate the problem of tapping tiny keys with imprecise finger touch (e.g., T9 is the default keyboard on Samsung Gear 2). In this paper, we proposed a computational approach to design optimal T9-like layouts by considering three key factors: clarity, speed, and learnability. In particular, we devised a clarity metric to model the word collisions (i.e., words with identical tapping sequences), used the Fitts-Digraph model to predict speed, and introduced a Qwerty-bounded constraint to ensure high learnability. Founded upon rigorous mathematical optimization, our investigation led to Optimal-T9, an optimized T9-like layout which outperformed the original T9 and other T9-like layouts. A user study showed that its average input speed was 17% faster than T9 and 26% faster than a T9-like layout from literature. Optimal-T9 also drastically reduced the error rate by 72% over a regular Qwerty keyboard. Subjective ratings were in favor of Optimal-T9: it had the lowest physical, mental demands, and the best perceived-performance among all the tested keyboards. Overall, our investigation has led to a more efficient, and more accurate T9-like layout than the original T9. Such a layout would immediately benefit both T9-like keyboard users and small touchscreen device users.
AB - T9-like keyboards (i.e., 3×3 layouts) have been commonly used on small touchscreen devices to mitigate the problem of tapping tiny keys with imprecise finger touch (e.g., T9 is the default keyboard on Samsung Gear 2). In this paper, we proposed a computational approach to design optimal T9-like layouts by considering three key factors: clarity, speed, and learnability. In particular, we devised a clarity metric to model the word collisions (i.e., words with identical tapping sequences), used the Fitts-Digraph model to predict speed, and introduced a Qwerty-bounded constraint to ensure high learnability. Founded upon rigorous mathematical optimization, our investigation led to Optimal-T9, an optimized T9-like layout which outperformed the original T9 and other T9-like layouts. A user study showed that its average input speed was 17% faster than T9 and 26% faster than a T9-like layout from literature. Optimal-T9 also drastically reduced the error rate by 72% over a regular Qwerty keyboard. Subjective ratings were in favor of Optimal-T9: it had the lowest physical, mental demands, and the best perceived-performance among all the tested keyboards. Overall, our investigation has led to a more efficient, and more accurate T9-like layout than the original T9. Such a layout would immediately benefit both T9-like keyboard users and small touchscreen device users.
KW - Pareto optimization
KW - Smartwatches
KW - Text entry
KW - Touchscreen
UR - https://www.scopus.com/pages/publications/85061061173
U2 - 10.1145/3279778.3279786
DO - 10.1145/3279778.3279786
M3 - Conference contribution
AN - SCOPUS:85061061173
T3 - ISS 2018 - Proceedings of the 2018 ACM International Conference on Interactive Surfaces and Spaces
SP - 137
EP - 146
BT - ISS 2018 - Proceedings of the 2018 ACM International Conference on Interactive Surfaces and Spaces
PB - Association for Computing Machinery, Inc
Y2 - 25 November 2018 through 28 November 2018
ER -