Asela Gunawardana, Tim Paek, and Christopher Meek
Soft keyboards offer touch-capable mobile and tabletop devices many advantages such as multiple language support and room for larger displays. On the other hand, because soft keyboards lack haptic feedback, users often produce more typing errors. In order to make soft keyboards more robust to noisy input, researchers have developed key-target resizing algorithms, where underlying target areas for keys are dynamically resized based on their probabilities. In this paper, we describe how overly aggressive key-target resizing can sometimes prevent users from typing their desired text, violating basic user expectations about keyboard functionality. We propose the anchored dynamic key-target method which incorporates usability principles so that soft keyboards can remain robust to errors while respecting usability principles. In an empirical evaluation, we found that anchored dynamic key-targets significantly reduce keystroke errors, improving over the state of the art.
In International Conference on Intelligent User Interfaces
Publisher Association for Computing Machinery, Inc.
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Joshua Goodman, Gina Venolia, Keith Steury, and Chauncey Parker. Language modeling for soft keyboards, ACM, 2002.
Gina D. Venolia, Joshua Goodman, Keith Steury, and Chauncey Parker. Language Modeling for Soft Keyboards, November 2001.
Joshua Goodman, Gina Venolia, Keith Steury, and Chauncey Parker. Language modeling for soft keyboards, American Association for Artificial Intelligence, 2002.