engleski

Predicting upper-bound text entry speeds for discrete-tilt-based input on smartphones

Motion sensors integrated into contemporary smartphones allow the introduction of new mobile interaction paradigms, here including tilt-based input control in the mobile context. Namely, as opposed to existing implementations that typically apply continuous feedback on tilting, we define Pitch and Roll movement sequences that change the orientation of the mobile device as discrete-tilt input primitives. The respective commands are then used to manage text entry within three discrete-tilt-based methods thus introduced: keyboard bisection, single cursor, and quad cursor. Each method is based on the use of a particular QWERTY-based keyboard layout with related strategy for character input. We model upper-bound text entry speeds for the input methods, taking into account both movement aspects and language context. The movement model corresponds to both the tilt-based shortest path between two consequent characters, which is theoretically defined, and the time of discrete-tilt execution, which is obtained from user testing experiment we conducted. The linguistic model, comprising digraph statistics, is constructed basing on available English corpora. This modeling approach provides discrete-tilt-based text entry speed predictions representing efficiency rates for expert behavior, i.e. for optimal performance. The results obtained enable the evaluation of the proposed designs without need to test with real users, and can furthermore serve as a baseline for efficiency of text entry implementations that rely on discrete tilt.

text entry; tilt interaction; mobile devices; predictive models

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