TY - GEN
T1 - JustCorrect
T2 - 33rd Annual ACM Symposium on User Interface Software and Technology, UIST 2020
AU - Cui, Wenzhe
AU - Zhu, Suwen
AU - Zhang, Mingrui Ray
AU - Schwartz, Andrew
AU - Wobbrock, Jacob O.
AU - Bi, Xiaojun
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/10/20
Y1 - 2020/10/20
N2 - Correcting errors in entered text is a common task but usually difficult to perform on mobile devices due to tedious cursor navigation steps. In this paper, we present JustCorrect, an intelligent post hoc text correction technique for smartphones. To make a correction, the user simply types the correct text at the end of their current input, and JustCorrect will automatically detect the error and apply the correction in the form of an insertion or a substitution. In this way, manual navigation steps are bypassed, and the correction can be committed with a single tap. We solved two critical problems to support JustCorrect: (1) Correction Algorithm: we propose an algorithm that infers the user's correction intention from the last typed word. (2) Input Modalities: our study revealed that both tap and gesture were suitable input modalities for performing JustCorrect. Based on our findings, we integrated JustCorrect into a soft keyboard. Our user studies show that using JustCorrect reduces the text correction time by 12.8% over the stock Android keyboard and by 9.7% over the "Type, then Correct"text correction technique by Zhang et al. (2019). Overall, JustCorrect complements existing post hoc text correction techniques, making error correction more automatic and intelligent.
AB - Correcting errors in entered text is a common task but usually difficult to perform on mobile devices due to tedious cursor navigation steps. In this paper, we present JustCorrect, an intelligent post hoc text correction technique for smartphones. To make a correction, the user simply types the correct text at the end of their current input, and JustCorrect will automatically detect the error and apply the correction in the form of an insertion or a substitution. In this way, manual navigation steps are bypassed, and the correction can be committed with a single tap. We solved two critical problems to support JustCorrect: (1) Correction Algorithm: we propose an algorithm that infers the user's correction intention from the last typed word. (2) Input Modalities: our study revealed that both tap and gesture were suitable input modalities for performing JustCorrect. Based on our findings, we integrated JustCorrect into a soft keyboard. Our user studies show that using JustCorrect reduces the text correction time by 12.8% over the stock Android keyboard and by 9.7% over the "Type, then Correct"text correction technique by Zhang et al. (2019). Overall, JustCorrect complements existing post hoc text correction techniques, making error correction more automatic and intelligent.
KW - Error correction
KW - Smartphones
KW - Text entry
UR - https://www.scopus.com/pages/publications/85096983565
U2 - 10.1145/3379337.3415857
DO - 10.1145/3379337.3415857
M3 - Conference contribution
AN - SCOPUS:85096983565
T3 - UIST 2020 - Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology
SP - 487
EP - 499
BT - UIST 2020 - Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology
PB - Association for Computing Machinery, Inc
Y2 - 20 October 2020 through 23 October 2020
ER -