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Swipeboard: a text entry technique for ultra-small interfaces that supports novice to expert transitions

Published: 05 October 2014 Publication History

Abstract

Ultra-small smart devices, such as smart watches, have become increasingly popular in recent years. Most of these devices rely on touch as the primary input modality, which makes tasks such as text entry increasingly difficult as the devices continue to shrink. In the sole pursuit of entry speed, the ultimate solution is a shorthand technique (e.g., Morse code) that sequences tokens of input (e.g., key, tap, swipe) into unique representations of each character. However, learning such techniques is hard, as it often resorts to rote memory. Our technique, Swipeboard, leverages our spatial memory of a QWERTY keyboard to learn, and eventually master a shorthand, eyes-free text entry method designed for ultra-small interfaces. Characters are entered with two swipes; the first swipe specifies the region where the character is located, and the second swipe specifies the character within that region. Our study showed that with less than two hours' training, Tested on a reduced word set, Swipeboard users achieved 19.58 words per minute (WPM), 15% faster than an existing baseline technique.

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      cover image ACM Conferences
      UIST '14: Proceedings of the 27th annual ACM symposium on User interface software and technology
      October 2014
      722 pages
      ISBN:9781450330695
      DOI:10.1145/2642918
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 05 October 2014

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      Author Tags

      1. input technique
      2. mobile device
      3. swipeboard
      4. text entry

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      UIST '14 Paper Acceptance Rate 74 of 333 submissions, 22%;
      Overall Acceptance Rate 561 of 2,567 submissions, 22%

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      Cited By

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      • (2024)Accessible Gesture Typing on Smartphones for People with Low VisionProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676447(1-11)Online publication date: 13-Oct-2024
      • (2024)RingGesture: A Ring-Based Mid-Air Gesture Typing System Powered by a Deep-Learning Word Prediction FrameworkIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345617930:11(7441-7451)Online publication date: Nov-2024
      • (2023)Statslator: Interactive Translation of NHST and Estimation Statistics Reporting Styles in Scientific DocumentsProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606762(1-14)Online publication date: 29-Oct-2023
      • (2023)DRG-KeyboardProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35694636:4(1-30)Online publication date: 11-Jan-2023
      • (2023)Investigating a Force-Based Selection Method for Smartwatches in a 1D Fitts’ Law Study and Two New Character-Level KeyboardsProceedings of the Seventeenth International Conference on Tangible, Embedded, and Embodied Interaction10.1145/3569009.3572741(1-10)Online publication date: 26-Feb-2023
      • (2023)Crownboard: A One-Finger Crown-Based Smartwatch Keyboard for Users with Limited DexterityProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580770(1-22)Online publication date: 19-Apr-2023
      • (2023)AirText: One-Handed Text Entry in the Air for COTS SmartwatchesIEEE Transactions on Mobile Computing10.1109/TMC.2021.313003622:5(2506-2519)Online publication date: 1-May-2023
      • (2023)Speech Synthesis Using Ambiguous Inputs From Wearable Keyboards2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)10.1109/APSIPAASC58517.2023.10317228(1172-1178)Online publication date: 31-Oct-2023
      • (2022)Understanding and Adapting Bezel-to-Bezel Interactions for Circular Smartwatches in Mobile and Encumbered ScenariosProceedings of the ACM on Human-Computer Interaction10.1145/35467366:MHCI(1-28)Online publication date: 20-Sep-2022
      • (2022)TypeAnywhere: A QWERTY-Based Text Entry Solution for Ubiquitous ComputingProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517686(1-16)Online publication date: 29-Apr-2022
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