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21. AI-Driven Intelligent Text Correction Techniques for Mobile Text Entry

Author

Jacob O. Wobbrock, H. Andrew Schwartz, Wenzhe Cui, Mingrui Ray Zhang, He Wen, Xiaojun Bi, and Suwen Zhu

Subjects
De facto, Computer science, Human–computer interaction, Text entry, Cursor (databases), Mobile device
Abstract

Current text correction processes on mobile touch devices are laborious: users either extensively use backspace, or navigate the cursor to the error position, make a correction, and navigate back, usually by employing multiple taps or drags over small targets. In this chapter, we present two techniques, Type, Then Correct and JustCorrect, that utilize the power of artificial intelligence to improve the text correction experience on mobile devices. All of the techniques skip error-deletion and cursor-positioning procedures, and instead allow the user to type the correction first, and then apply that correction to a previously committed error. We evaluated these techniques in and the results show that correction with the new techniques was faster than de facto cursor and backspace-based correction.

Published
2021
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