ResType: Invisible and Adaptive Tablet Keyboard Leveraging Resting Fingers

Zhuojun Li, Chun Yu, Yizheng Gu, Yuanchun Shi

Abstract: Text entry on tablet touchscreens is a basic need nowadays. Tablet keyboards require visual attention for users to locate keys, thus not supporting efficient touch typing. They also take up a large proportion of screen space, which affects the access to information. To solve these problems, we propose ResType, an adaptive and invisible keyboard on three-state touch surfaces (e.g. tablets with unintentional touch prevention). ResType allows users to rest their hands on it and automatically adapts the keyboard to the resting fingers. Thus, users do not need visual attention to locate keys, which supports touch typing. We quantitatively explored users’ resting finger patterns on ResType, based on which we proposed an augmented Bayesian decoding algorithm for ResType, with 96.3% top-1 and 99.0% top-3 accuracies. After a 5-day evaluation, ResType achieved 41.26 WPM, outperforming normal tablet keyboards by 13.5% and reaching 86.7% of physical keyboards. It solves the occlusion problem while maintaining comparable typing speed with current methods on visible tablet keyboards.