TY - GEN
T1 - Vipboard
T2 - 2019 CHI Conference on Human Factors in Computing Systems, CHI 2019
AU - Shi, Weinan
AU - Yu, Chun
AU - Fan, Shuyi
AU - Wang, Feng
AU - Wang, Tong
AU - Yi, Xin
AU - Bi, Xiaojun
AU - Shi, Yuanchun
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/5/2
Y1 - 2019/5/2
N2 - Modern touchscreen keyboards are all powered by the word-level auto-correction ability to handle input errors. Unfortunately, visually impaired users are deprived of such beneft because a screen-reader keyboard ofers only character-level input and provides no correction ability. In this paper, we present VIPBoard, a smart keyboard for visually impaired people, which aims at improving the underlying keyboard algorithm without altering the current input interaction. Upon each tap, VIPBoard predicts the probability of each key considering both touch location and language model, and reads the most likely key, which saves the calibration time when the touchdown point misses the target key. Meanwhile, the keyboard layout automatically scales according to users’ touch point location, which enables them to select other keys easily. A user study shows that compared with the current keyboard technique, VIPBoard can reduce touch error rate by 63.0% and increase text entry speed by 12.6%.
AB - Modern touchscreen keyboards are all powered by the word-level auto-correction ability to handle input errors. Unfortunately, visually impaired users are deprived of such beneft because a screen-reader keyboard ofers only character-level input and provides no correction ability. In this paper, we present VIPBoard, a smart keyboard for visually impaired people, which aims at improving the underlying keyboard algorithm without altering the current input interaction. Upon each tap, VIPBoard predicts the probability of each key considering both touch location and language model, and reads the most likely key, which saves the calibration time when the touchdown point misses the target key. Meanwhile, the keyboard layout automatically scales according to users’ touch point location, which enables them to select other keys easily. A user study shows that compared with the current keyboard technique, VIPBoard can reduce touch error rate by 63.0% and increase text entry speed by 12.6%.
KW - Auto-correction
KW - Smartphone
KW - Text entry
KW - Visually impaired
UR - https://www.scopus.com/pages/publications/85067618605
U2 - 10.1145/3290605.3300747
DO - 10.1145/3290605.3300747
M3 - Conference contribution
AN - SCOPUS:85067618605
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 4 May 2019 through 9 May 2019
ER -