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Eye typing interfaces enable a person to enter text into an interface usingonly their own eyes. But despite the inherent advantages of touchless operationand intuitive design, such eye-typing interfaces often suffer from slow typingspeeds, resulting in slow words per minute (WPM) counts. In this study, we addword and letter prediction to the eye-typing interface and investigate users'typing performance as well as their subjective experience while using theinterface. In experiment 1, we compared three typing interfaces with letterprediction (LP), letter+word prediction (L+WP), and no prediction (NoP),respectively. We found that the interface with L+WP achieved the highestaverage text entry speed (5.48 WPM), followed by the interface with LP (3.42WPM), and the interface with NoP (3.39 WPM). Participants were able to quicklyunderstand the procedural design for word prediction and perceived thisfunction as very helpful. Compared to LP and NoP, participants needed more timeto familiarize themselves with L+WP in order to reach a plateau regarding textentry speed. Experiment 2 explored training effects in L+WP interfaces. Twomoving speeds were implemented: slow (6.4{\deg}/s same speed as in experiment1) and fast (10{\deg}/s). The study employed a mixed experimental design,incorporating moving speeds as a between-subjects factor, to evaluate itsinfluence on typing performance throughout 10 consecutive training sessions.The results showed that the typing speed reached 6.17 WPM for the slow groupand 7.35 WPM for the fast group after practice. Overall, the two experimentsshow that adding letter and word prediction to eye-typing interfaces increasestyping speeds. We also find that more extended training is required to achievethese high typing speeds.

Enhancing Hybrid Eye Typing Interfaces with Word and Letter Prediction: A Comprehensive Evaluation