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

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

doi:10.1145/2702123.2702135

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

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

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
Place of Publication	New York
Publisher	ACM
Pages	659-668
Number of pages	9
ISBN (Electronic)	9781450331456
DOIs	https://doi.org/10.1145/2702123.2702135
Publication status	Published - 18 Apr 2015
Event	The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI) - COEX Convention & Exhibition Center, Seoul, Korea, Republic of Duration: 18 Apr 2015 → 23 Apr 2015 http://chi2015.acm.org/

Conference

Conference	The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI)
Abbreviated title	CHI2015
Country/Territory	Korea, Republic of
City	Seoul
Period	18/04/15 → 23/04/15
Internet address	http://chi2015.acm.org/

Keywords

Mobile text entry
Touchscreen keyboard
Sentence decoding

Access to Document

10.1145/2702123.2702135

velocitap
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Accepted author manuscript, 1 MB

Cite this

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

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.",

keywords = "Mobile text entry, Touchscreen keyboard, Sentence decoding",

author = "Keith Vertanen and Haythem Memmi and Justin Emge and Reyal, {Shyam Mehraaj} and Kristensson, {Per Ola}",

note = "Date of Acceptance: 15/12/2014; The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI), CHI2015 ; Conference date: 18-04-2015 Through 23-04-2015",

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month = apr,

day = "18",

doi = "10.1145/2702123.2702135",

language = "English",

pages = "659--668",

booktitle = "CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems",

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Vertanen, K, Memmi, H, Emge, J, Reyal, SM & Kristensson, PO 2015, VelociTap: investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input. in CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, New York, pp. 659-668, The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI), Seoul, Korea, Republic of, 18/04/15. https://doi.org/10.1145/2702123.2702135

VelociTap: investigating fast mobile text entry using sentence-based decoding of touchscreen keyboard input. / Vertanen, Keith; Memmi, Haythem; Emge, Justin et al.
CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York: ACM, 2015. p. 659-668.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - VelociTap

T2 - The 33rd Annual CHI Conference on Human Factors in Computing Systems (CHI)

AU - Vertanen, Keith

AU - Memmi, Haythem

AU - Emge, Justin

AU - Reyal, Shyam Mehraaj

AU - Kristensson, Per Ola

N1 - Date of Acceptance: 15/12/2014

PY - 2015/4/18

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N2 - 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.

AB - 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.

KW - Mobile text entry

KW - Touchscreen keyboard

KW - Sentence decoding

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DO - 10.1145/2702123.2702135

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PB - ACM

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ER -

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

Abstract

Conference

Keywords

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