Researchers: Keith Vertanen, PI, Assistant Professor, Computer Science
Sponsor: Google Faculty Research Award
Amount of Support: $47,219
Abstract: While there have been significant improvements to text input on touchscreen mobile devices, entry rates still fall far short of allowing the free-flowing conversion of thought into text. Such free-flowing writing has been estimated to require input at around 67 words-per-minute (wpm) [1]. This is far faster than current mobile text entry methods that have entry rates of 20–40 wpm. The approach we investigate in this project is to accelerate entry by allowing users to enter an abbreviated version of their desired text. Users are allowed to drop letters or entire words, relying on a sentence-based decoder to infer the unabbreviated sentence. This project aims to answer four questions: 1) What sorts of abbreviations, a priori, do users think they should use? 2) How do users change the degree and nature of their abbreviations in response to recognition accuracy? 3) Can we train users to drop parts of their text intelligently in order to aid the decoder? 4) Can we leverage the abbreviation behaviors observed to improve decoder accuracy?
To answer these questions, we adopt a data-driven approach; collecting lots of data, from many users, over long-term use. To this end, we will extend our existing multi-player game Text Blaster [2], deploying the game on the Android app store. Text Blaster’s game play encourages players to type sentences both quickly and accurately. Players adopting successful abbreviation strategies will gain a competitive advantage. Text Blaster provides a platform to not only investigate abbreviated input but also a host of other open research questions in text entry. Data collected via Text Blaster will be released as a public research resource.
References
[1] Kristensson, P.O. and Vertanen, K. (2014). The Inviscid Text Entry Rate and its Application as a Grand Goal for Mobile Text Entry. In MobileHCI 2014, 335-338.