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SHARK2: A Large Vocabulary Shorthand Writing System for Pen-based Computers
Linköping University, Department of Computer and Information Science, MDALAB - Human Computer Interfaces. Linköping University, The Institute of Technology.
IBM Almaden Research Center, San Jose, USA.
2004 (English)In: UIST '04 Proceedings of the 17th annual ACM symposium on User interface software and technology, New York: ACM Press , 2004, 43-52 p.Conference paper, Published paper (Refereed)
Abstract [en]

Zhai and Kristensson (2003) presented a method of speed-writing for pen-based computing which utilizes gesturing on a stylus keyboard for familiar words and tapping for others. In SHARK2:, we eliminated the necessity to alternate between the two modes of writing, allowing any word in a large vocabulary (e.g. 10,000-20,000 words) to be entered as a shorthand gesture. This new paradigm supports a gradual and seamless transition from visually guided tracing to recall-based gesturing. Based on the use characteristics and human performance observations, we designed and implemented the architecture, algorithms and interfaces of a high-capacity multi-channel pen-gesture recognition system. The system's key components and performance are also reported.

Place, publisher, year, edition, pages
New York: ACM Press , 2004. 43-52 p.
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-24318DOI: 10.1145/1029632.1029640Local ID: 3941ISBN: 1-58113-957-8 (print)OAI: oai:DiVA.org:liu-24318DiVA: diva2:244636
Conference
UIST 2004, the Seventeenth Annual ACM Symposium on User Interface Software and Technology. Santa Fe, New Mexico. October 24–27, 2004.
Note

Also in ACM CHI Letters Volume 6 Issue 2

Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2013-11-26
In thesis
1. Large Vocabulary Shorthand Writing on Stylus Keyboard
Open this publication in new window or tab >>Large Vocabulary Shorthand Writing on Stylus Keyboard
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

We present a novel text entry method for pen-based computers. We view the trace obtained by connecting the letter keys comprising a word on a stylus keyboard as a pattern. This pattern can be matched against a user-s pen trace, invariant of scale and translation. Hence the patterns become an efficient form of shorthand gestures, allowing users to use eyes-free openloop motor actions to perform the gestures. This can result in higher text entry speed than optimized stylus keyboards, the fastest known text entry technique for pen-computers as of today. The approach supports a gradual and seamless skill transition from novices tracing the letter keys to experts articulating the shorthand gestures. Hence the ratio between the learning effort and efficiency in using the system can be said to be optimized at any given point in time in the user-s experience with the technique. This thesis describes the rationale, architecture and lgorithms behind a stylus keyboard augmented with a high-capacity gesture recognition engine. We also report results from an Expanding Rehearsal Interval (ERI) experiment which indicates that users can acquire about 15 shorthand gestures per 45 minute training session. Empirical expert speed estimates of the technique indicate text entry speeds much higher than any prior known pen-based text entry system for mobile computers.  

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2004. 14 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1127
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-24321 (URN)3944 (Local ID)91-85295-76-0 (ISBN)3944 (Archive number)3944 (OAI)
Presentation
2004-11-19, Alan Turing, Hus E, Linköpings universitet, Linköping, 10:15 (Swedish)
Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2013-11-26

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Publisher's full texthttp://www.pokristensson.com/pubs/KristenssonZhaiUIST2004.pdf

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Kristensson, Per-Ola

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CiteExportLink to record
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Citation style
  • apa
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  • ieee
  • modern-language-association-8th-edition
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Language
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Output format
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