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Jiangyue Yu

dblp:322/3910 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-5151-9596ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input
text entry
0.712023
T-Force: Exploring the Use of Typing Force for Three State Virtual Keyboards · CHI 2023
Interaction techniques and input › text entry
virtual keyboard
0.712023
T-Force: Exploring the Use of Typing Force for Three State Virtual Keyboards · CHI 2023
Interaction techniques and input › input device
keyboard design
0.212023
T-Force: Exploring the Use of Typing Force for Three State Virtual Keyboards · CHI 2023

Methods — techniques the papers use, named apart from their topics

user study · 0.7threshold function design · 0.7
YearPublicationVenuePosition
2023 T-Force: Exploring the Use of Typing Force for Three State Virtual Keyboards
abstract
Three state virtual keyboards which differentiate contact events between released, touched, and pressed states have the potential to improve overall typing experience and reduce the gap between virtual keyboards and physical keyboards. Incorporating force sensitivity, three-state virtual keyboards can utilize a force threshold to better classify a contact event. However, our limited knowledge of how force plays a role during typing on virtual keyboards limits further progress. Through a series of studies we observe that using a uniform threshold is not an optimal approach. Furthermore, the force being applied while typing varies significantly across the keys and among participants. As such, we propose three different approaches to further improve the uniform threshold. We show that a carefully selected non-uniform threshold function could be sufficient in delineating typing events on a three-state keyboard. Finally, we conclude our work with lessons learned, suggestion for future improvements, and comparisons with current methods available.
Shariff A. M. Faleel, Yishuo Liu, Roya Allison Cody, Bradley Rey, Linghao Du, Jiangyue Yu, Da-Yuan Huang, Pourang Irani, Wei Li 0002
CHI6