An Adaptive Keyboard with Personalized Language-Based Features

Our research is about an adaptive keyboard, which autonomously adjusts its predictive features and key displays to current user input. We used personalized word prediction to improve the performance of such a system. Prediction using common English dictionary (represented by the British National Corpus) is compared with prediction using personal data, such as personal documents, chat logs, and personal emails. A user study was also conducted to gather requirements for a new keyboard design. Based on these studies, we developed a personalized and adaptive on-screen keyboard for both single-handed and zero-handed users. It combines tapping-based and motion-based text input with language-based acceleration techniques, including personalized and adaptive task-based dictionary, frequent character prompting, word completion, and grammar checker with suffix completion.