Typing on a smartwatch is challenging because of the fat-finger problem. Rising to the challenge, we present a soft keyboard for ultrasmall touch screen devices with efficient visual feedback integrated with autocorrection and prediction techniques. After exploring the design space to support efficient typing on smartwatches, we designed a novel and space-saving text entry interface based on an in situ decoder and prediction function that can run in real-time on a smartwatch such as LG Watch Style. We outlined the details implemented through performance optimization techniques and released interface code, APIs, and libraries as open source. We examined the design decisions with the simulations and studied the visual feedback methods in terms of performance and user preferences. The experiment showed that users could type more accurately and quickly on the target device with our best-performing visual feedback design and implementation. The simulation result showed that the single word suggestion could yield a sufficiently high hit ratio using the optimized word suggestion algorithm.

中文翻译：

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基于Schnorr-Lyubashevsky框架的代码签名方案的密码分析


由于胖手指问题，在智能手表上打字非常具有挑战性。迎接挑战，我们推出了一款适用于超小型触摸屏设备的软键盘，具有高效的视觉反馈以及自动校正和预测技术。在探索了支持智能手表上高效打字的设计空间后，我们设计了一种新颖且节省空间的文本输入界面，该界面基于原位解码器和预测功能，可以在 LG Watch Style 等智能手表上实时运行。我们概述了通过性能优化技术实现的细节，并将接口代码、API 和库作为开源发布。我们通过模拟检查了设计决策，并研究了性能和用户偏好方面的视觉反馈方法。实验表明，通过我们性能最佳的视觉反馈设计和实现，用户可以在目标设备上更准确、更快速地打字。仿真结果表明，使用优化的单词建议算法，单单词建议可以产生足够高的命中率。