Demonstrating 1D-Touch : NLP-Assisted Coarse Text Selection via a Semi-Direct Gesture

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

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Author(s)

  • Peiling Jiang
  • Li Feng
  • Fuling Sun
  • Haijun Xia
  • Can Liu

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationUIST '23
Subtitle of host publicationProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology
EditorsSean Follmer, Jeff Han, Jürgen Steimle, Nathalie Henry Riche
PublisherAssociation for Computing Machinery
ISBN (print)979-8-4007-0132-0
Publication statusPublished - Oct 2023

Conference

Title36th Annual ACM Symposium on User Interface Software and Technology, UIST 2023
PlaceUnited States
CitySan Francisco
Period29 October - 1 November 2023

Abstract

Existing text selection techniques on touchscreen focus on improving the control for moving the carets. Coarse-grained text selection on word- and phrase- levels have not received much support beyond word-snapping and entity recognition. We introduce 1D-Touch, a novel text selection method that complements the carets-based sub-word selection by facilitating the selection of words and larger semantic units. This method employs a simple vertical slide gesture to expand and contract a selection area from a word. The expansion can be by words or by semantic chunks ranging from sub-phrases to sentences, as implemented in two variants of our technique named WordTouch and ChunkTouch. This approach shifts the concept of text selection, away from defining a range by locating the first and last characters, towards a dynamic process of expanding and contracting a textual entity. While the full paper (expected to appear at the ACM ISS 2023) details the evaluation, this demonstration showcases 1D-Touch with a few applications of coarse-grained text selection, to engage the audience in discussions about its effectiveness and applications, as well as its integration with existing character-level selection techniques. © 2023 Owner/Author.

Research Area(s)

  • Natural Language Processing, Text selection, Touch interface

Citation Format(s)

Demonstrating 1D-Touch: NLP-Assisted Coarse Text Selection via a Semi-Direct Gesture. / Jiang, Peiling; Feng, Li; Sun, Fuling et al.
UIST '23: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology. ed. / Sean Follmer; Jeff Han; Jürgen Steimle; Nathalie Henry Riche. Association for Computing Machinery, 2023. 52.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review