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Conference Papers Year : 2016

Expressive Keyboards: Enriching Gesture-Typing on Mobile Devices

Abstract

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.
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Dates and versions

hal-01437054 , version 1 (17-01-2017)

Identifiers

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Jessalyn Alvina, Joseph Malloch, Wendy Mackay. Expressive Keyboards: Enriching Gesture-Typing on Mobile Devices. Proceedings of the 29th ACM Symposium on User Interface Software and Technology (UIST 2016), ACM, Oct 2016, Tokyo, Japan. pp.583 - 593, ⟨10.1145/2984511.2984560⟩. ⟨hal-01437054⟩
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