Handwritten shorthand and its future potential for fast mobile text entry

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Title Handwritten shorthand and its future potential for fast mobile text entry
Author Leedham, Graham; Ma, Yang; Blumenstein, Michael Myer
Journal Name International Journal of Pattern Recognition and Artificial Intelligence
Editor X Jiang
Year Published 2009
Place of publication Singapore
Publisher World Scientific
Abstract Handwritten shorthand systems were devised to enable writers to record information on paper at fast speeds, ideally at the speed of speech. While they have been in existence for many years it is only since the 17th Century that widespread usage appeared. Several shorthand systems flourished in the first half of the 20th century until the introduction and widespread use of electronic recording and dictation machines in the 1970's. Since then, shorthand usage has been in rapid decline, but has not yet become a lost skill. Pitman shorthand has been shown to possess unique advantages as a means of fast text entry which is particularly applicable to hand-held devices in mobile environments. This paper presents progress and critical research issues for a Pitman/Renqun Shorthand Online Recognition System. Recognition and transcription experiments are reported which indicate that a correct recognition and transcription rate of around 90% is currently possible.
Peer Reviewed Yes
Published Yes
Publisher URI http://www.worldscinet.com/ijprai/ijprai.shtml
Alternative URI http://dx.doi.org/10.1142/S0218001409007405
Copyright Statement Electronic version of an article published as International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Volume: 23, Issue: 5(2009) pp. 1031-1051, http://dx.doi.org/10.1142/S0218001409007405. Copyright World Scientific Publishing Company http://www.worldscinet.com/ijprai/ijprai.shtml
Volume 23
Issue Number 5
Page from 1031
Page to 1051
ISSN 0218-0014
Date Accessioned 2010-03-05
Date Available 2010-05-13T06:40:25Z
Language en_AU
Research Centre Institute for Integrated and Intelligent Systems
Faculty Faculty of Science, Environment, Engineering and Technology
Subject Pattern Recognition and Data Mining
URI http://hdl.handle.net/10072/29652
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1

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