Abstract:

Text entry for extended reality (XR) is far from perfect, and a variety of text entry techniques (TETs) have been proposed to fit various contexts of use. However, comparing between TETs remains challenging due to the lack of a consolidated collection of techniques, and limited understanding of how interaction attributes of a technique (e.g., presence of visual feedback) impact user performance. To address these gaps, this paper examines the current landscape of XR TETs by creating a database of 176 different techniques. We analyze this database to highlight trends in the design of these techniques, the metrics used to evaluate them, and how various interaction attributes impact these metrics. We discuss implications for future techniques and present TEXT: Text Entry for XR Trove, an interactive online tool to navigate our database.

People:

Arpit Bhatia University of Copenhagen arbh@di.ku.dk	Moaaz Hudhud Mughrabi MPI for Intelligent Systems moaaz@is.mpg.de	Diar Abdlkarim University of Birmingham diarkarim@gmail.com	Massimiliano Di Luca University of Birmingham m.diluca@bham.ac.uk
Mar Gonzalez-Franco Google margon@google.com	Karan Ahuja Northwestern University kahuja@northwestern.edu	Hasti Seifi Arizona State University hasti.seifi@asu.edu