Text Text Revolution: A Game That Improves Text Entry on Mobile Touchscreen Keyboards

Rudchenko, Dmitry; Paek, Tim; Badger, Eric

doi:10.1007/978-3-642-21726-5_13

Cited by 26 publications

(23 citation statements)

References 11 publications

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“…Gunawardana et al [10] presented an approach with dynamic key-target resizing which defined a minimum target size, preventing key targets from shrinking too much. Rudchenko et al [29], with their Text Text Revolution game, showed that per-user touch models and personalized key-target resizing can further improve typing accuracy. Kristensson and Zhai [19] presented the gesture keyboard Shark 2 , which combined a shorthand writing system with a language model.…”

Section: Related Work Text Entry Correction Approachesmentioning

confidence: 99%

Uncertain text entry on mobile devices

Weir

Pohl²,

Rogers

et al. 2014

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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Users often struggle to enter text accurately on touchscreen keyboards. To address this, we present a flexible decoder for touchscreen text entry that combines probabilistic touch models with a language model. We investigate two different touch models. The first touch model is based on a Gaussian Process regression approach and implicitly models the inherent uncertainty of the touching process. The second touch model allows users to explicitly control the uncertainty via touch pressure. Using the first model we show that the character error rate can be reduced by up to 7% over a baseline method, and by up to 1.3% over a leading commercial keyboard. Using the second model we demonstrate that providing users with control over input certainty reduces the amount of text users have to correct manually and increases the text entry rate.

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Section: Related Work Text Entry Correction Approachesmentioning

confidence: 99%

Uncertain text entry on mobile devices

Weir

Pohl²,

Rogers

et al. 2014

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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“…Sears (1991) pointed out that even though using speech for text entry with a touch panel is not as fast as using the traditional panel, it still offers alternatives. Recent studies had also investigated the text entry performance on touch screens (Rudchenko, Paek, and Badge 2011;Malik and Findlater 2013). All of the above literatures were based on English text entry tasks.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Chinese text entry performance for mobile display interfaces

Lin

2014

Ergonomics

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This study examined the effects of panel type, frequency of use and arrangement of phonetic symbols on operation time, usability, visual fatigue and workload in text entry performance. Three types of panel (solid, touch and mixed), three types of frequency of use (low, medium and high) and two types of the arrangement of phonetic symbols (vertical and horizontal) were investigated through 30 college students in the experiment. The results indicated that panel type, frequency of use, arrangement of phonetic symbols and the interaction between panel type and frequency of use were significant factors on operation time. Panel type was also a significant factor on usability, and a touch panel and a solid panel showed better usability than a mixed panel. Furthermore, a touch panel showed good usability and the lowest workload and therefore it is recommended to use a touch panel with vertical phonetic arrangement in sending Chinese text messages. Practitioner Summary: This study found, from ergonomics considerations, that a touch panel showed good usability and it is recommended to use a touch panel with vertical phonetic arrangement in sending Chinese text messages. Mobile display manufacturers can use the results of this study as a reference for future keyboard design.

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“…When users mistype a character, they are typically notified through auditory and visual feedback, such as beeps and squiggly underlines. [19]. This is effective for highly motivated users with a certain degree of knowledge and skill.…”

Section: Text Entry For Older Adultsmentioning

confidence: 99%

Assistive Typing Application for Older Adults Based on Input Stumble Detection

Hagiya

Horiuchi

Yazaki

et al. 2017

Journal of Information Processing

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Smartphones offer new opportunities to improve the lives of older adults. Although many older adults are interested in smartphones, most of them face difficulties in self-instruction and need support. Text entry, which is essential for various applications, is one of the most difficult operations to master. Therefore, we propose an assistive typing application that detects input stumbles and provides instructions for typing presented sentences, instead of having human tutors help older adults resolve the input stumbles by themselves. First, we investigated the ways that novice older adults have problems with text entry on smartphones. Next, we confirmed the acceptability of being provided with instructions for text entry by Wizard-of-Oz (WoZ). Then, we constructed an assistive typing application based on the collected data from two user studies. An evaluation with novice older adults (60+) showed that the assistive typing application increased typing speed by 17.2% and reduced input stumble incidence by 59.1% compared with the users' initial performance. Improvement rates were almost the same as those achieved with human tutors.

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Text Text Revolution: A Game That Improves Text Entry on Mobile Touchscreen Keyboards

Cited by 26 publications

References 11 publications

Uncertain text entry on mobile devices

Uncertain text entry on mobile devices

Investigation of Chinese text entry performance for mobile display interfaces

Assistive Typing Application for Older Adults Based on Input Stumble Detection

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