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Research at St Andrews

VelociTap: investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Keith Vertanen, Haythem Memmi, Justin Emge, Shyam Mehraaj Reyal, Per Ola Kristensson

School/Research organisations

Abstract

We present VelociTap: a state-of-the-art touchscreen keyboard decoder that supports a sentence-based text entry approach. VelociTap enables users to seamlessly choose from three word-delimiter actions: pushing a space key, swiping to the right, or simply omitting the space key and letting the decoder infer spaces automatically. We demonstrate that VelociTap has a significantly lower error rate than Google's keyboard while retaining the same entry rate. We show that intermediate visual feedback does not significantly affect entry or error rates and we find that using the space key results in the most accurate results. We also demonstrate that enabling flexible word-delimiter options does not incur an error rate penalty. Finally, we investigate how small we can make the keyboard when using VelociTap. We show that novice users can reach a mean entry rate of 41 wpm on a 40 mm wide smartwatch-sized keyboard at a 3% character error rate.
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Details

Original languageEnglish
Title of host publicationCHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
Place of PublicationNew York
PublisherACM
Pages659-668
Number of pages9
ISBN (Electronic)9781450331456
DOIs
StatePublished - 18 Apr 2015
EventThe 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI) - COEX Convention & Exhibition Center, Seoul, Korea, Republic of
Duration: 18 Apr 201523 Apr 2015
http://chi2015.acm.org/

Conference

ConferenceThe 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI)
Abbreviated titleCHI2015
CountryKorea, Republic of
CitySeoul
Period18/04/1523/04/15
Internet address

    Research areas

  • Mobile text entry, Touchscreen keyboard, Sentence decoding

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