research-article

TapType: Ten-finger text entry on everyday surfaces via Bayesian inference

Authors:

Andreas Rene Fender,

Christian HolzAuthors Info & Claims

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

Article No.: 497, Pages 1 - 16

https://doi.org/10.1145/3491102.3501878

Published: 29 April 2022 Publication History

Abstract

Despite the advent of touchscreens, typing on physical keyboards remains most efficient for entering text, because users can leverage all fingers across a full-size keyboard for convenient typing. As users increasingly type on the go, text input on mobile and wearable devices has had to compromise on full-size typing. In this paper, we present TapType, a mobile text entry system for full-size typing on passive surfaces—without an actual keyboard. From the inertial sensors inside a band on either wrist, TapType decodes and relates surface taps to a traditional QWERTY keyboard layout. The key novelty of our method is to predict the most likely character sequences by fusing the finger probabilities from our Bayesian neural network classifier with the characters’ prior probabilities from an n-gram language model. In our online evaluation, participants on average typed 19 words per minute with a character error rate of 0.6% after 30 minutes of training. Expert typists thereby consistently achieved more than 25 WPM at a similar error rate. We demonstrate applications of TapType in mobile use around smartphones and tablets, as a complement to interaction in situated Mixed Reality outside visual control, and as an eyes-free mobile text input method using an audio feedback-only interface.

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Cited By

Chiossi FEl Khaoudi YOu CSidenmark LZaky AFeuchtner TMayer S(2024)Evaluating Typing Performance in Different Mixed Reality Manifestations using Physiological FeaturesProceedings of the ACM on Human-Computer Interaction10.1145/36981428:ISS(377-406)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3698142
Darbar RHu XYan XWei YLiang HXu WSarcar S(2024)OnArmQWERTY: An Empirical Evaluation of On-Arm Tap Typing for AR HMDsProceedings of the 2024 ACM Symposium on Spatial User Interaction10.1145/3677386.3682084(1-12)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3677386.3682084
Kim DWhitmire EBoldu RKienzle WBenko HKostakos VKay JHoang T(2024)SoundScroll: Robust Finger Slide Detection Using Friction Sound and Wrist-Worn MicrophonesProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676614(63-70)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676614
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Index Terms

TapType: Ten-finger text entry on everyday surfaces via Bayesian inference

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cover image ACM Conferences

CHI '22: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems

April 2022

10459 pages

ISBN:9781450391573

DOI:10.1145/3491102

Editors:
Simone Barbosa
PUC-Rio, Brazil
,
Cliff Lampe
University of Michigan, USA
,
Caroline Appert
Université Paris-Saclay, France
,
David A. Shamma
Toyota Research Institute, USA
,
Steven Drucker
Microsoft Research, USA
,
Julie Williamson
University of Glasgow, UK
,
Koji Yatani
University of Tokyo, Japan

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Cited By

Chiossi FEl Khaoudi YOu CSidenmark LZaky AFeuchtner TMayer S(2024)Evaluating Typing Performance in Different Mixed Reality Manifestations using Physiological FeaturesProceedings of the ACM on Human-Computer Interaction10.1145/36981428:ISS(377-406)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3698142
Darbar RHu XYan XWei YLiang HXu WSarcar S(2024)OnArmQWERTY: An Empirical Evaluation of On-Arm Tap Typing for AR HMDsProceedings of the 2024 ACM Symposium on Spatial User Interaction10.1145/3677386.3682084(1-12)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3677386.3682084
Kim DWhitmire EBoldu RKienzle WBenko HKostakos VKay JHoang T(2024)SoundScroll: Robust Finger Slide Detection Using Friction Sound and Wrist-Worn MicrophonesProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676614(63-70)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676614
Richardson MBotros FShi YSnow BGuo PZhang LDong JVertanen KMa SWang R(2024)StegoType: Surface Typing from Egocentric CamerasAdjunct Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3672539.3686762(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3672539.3686762
Beier RWolling FHornecker EMichahelles F(2024)TipTopTyping: A Thumb-to-Finger Text Input Method and Character Layout Optimized for Mobile Spatial ComputingProceedings of Mensch und Computer 202410.1145/3670653.3670669(196-206)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1145/3670653.3670669
Zhang HLiang XLei YChen YHe ZZhang YChen LLin HHan TTian F(2024)Understanding the Effects of Restraining Finger Coactivation in Mid-Air Typing: from a Neuromechanical PerspectiveProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676441(1-18)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676441
Richardson MBotros FShi YGuo PSnow BZhang LDong JVertanen KMa SWang R(2024)StegoType: Surface Typing from Egocentric CamerasProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676343(1-14)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676343
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https://dl.acm.org/doi/10.1145/3617365
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https://doi.org/10.1109/AIxVR59861.2024.00060
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