The Expressive Keyboards project demonstrates and tests an approach to text input that celebrates input variation—rather than discarding it as noise—and maps it to continuous properties of the output.
Jessalyn Alvina, Joseph Malloch, and Wendy E. Mackay. 2016. Expressive Keyboards: Enriching Gesture-Typing on Mobile Devices. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST ’16). ACM, New York, NY, USA, 583-593. DOI: https://doi.org/10.1145/2984511.2984560
Gesture-typing is an efficient, easy-to-learn, and error tolerant technique for entering text on software keyboards. Our goal is to “recycle” users’ otherwise-unused gesture variation to create rich output under the users’ control, without sacrificing accuracy. Experiment 1 reveals a high level of existing gesture variation, even for accurate text, and shows that users can consciously vary their gestures under different conditions. We designed an Expressive Keyboard for a smart phone which maps input gesture features identified in Experiment 1 to a continuous output parameter space, i.e. RGB color. Experiment 2 shows that users can consciously modify their gestures, while retaining accuracy, to generate specific colors as they gesture-type. Users are more successful when they focus on output characteristics (such as red) rather than input characteristics (such as curviness). We designed an app with a dynamic font engine that continuously interpolates between several typefaces, as well as controlling weight and random variation. Experiment 3 shows that, in the context of a more ecologically-valid conversation task, users enjoy generating multiple forms of rich output. We conclude with suggestions for how the Expressive Keyboard approach can enhance a wide variety of gesture recognition applications.