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Text entry is a common and important part of many intelligent user interfaces. However, inferring a user’s intended text from their input can be challenging: motor actions can be imprecise, input sensors can be noisy, and situations or disabilities can hamper a user’s perception of interface feedback. Numerous prior studies have explored input on touchscreen phones, smartwatches, in midair, and on desktop keyboards. Based on these prior studies, we are releasing a large and diverse data set of noisy typing input consisting of thousands of sentences written by hundreds of users on QWERTY-layout keyboards. This paper describes the various subsets contained in this new research dataset as well as the data format.
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Motor Accessibility of Smartwatch Touch and Bezel Input
Smartwatches present inherent input difficulties due to the small touchscreen. In a controlled experiment with 14 participants with upper body motor impairments, we compared smartwatch touchscreen input to input on the bezel of the watch, the latter of which should at least theoretically stabilize user input due to its hard edge. Results demonstrate a speed-accuracy tradeoff whereby the touchscreen is faster but the bezel is more accurate.
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- Award ID(s):
- 1818594
- PAR ID:
- 10134435
- Date Published:
- Journal Name:
- ASSETS '19: The 21st International ACM SIGACCESS Conference on Computers and Accessibility
- Page Range / eLocation ID:
- 563 to 565
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3308561.3354638
