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Proceedings Paper

Online handwriting recognition in a form-filling task: evaluating the impact of context-awareness
Author(s): Giovanni Seni; Kimberly Rice; Eddy Mayoraz
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Paper Abstract

Guiding a recognition task using a language model is commonly accepted as having a positive effect on accuracy and is routinely used in automated speech processing. This paper presents a quantitative study of the impact of the use of word models in online handwriting recognition applied to form-filling tasks on handheld devices. Two types of word models are considered: a dictionary, typically from few thousands and up to hundred-thousand words; and a grammar or regular expression generating a language several orders of magnitude bigger than the dictionary. It is reported that the improvement in accuracy obtained by the use of a grammar compares with the gain provided by the use of a dictionary. Finally, the impact of the word models on user acceptance of online handwriting recognition in a specific form-filling application is presented.

Paper Details

Date Published: 15 December 2003
PDF: 7 pages
Proc. SPIE 5296, Document Recognition and Retrieval XI, (15 December 2003); doi: 10.1117/12.527115
Show Author Affiliations
Giovanni Seni, Motorola, Inc. (United States)
Kimberly Rice, Motorola, Inc. (United States)
Eddy Mayoraz, Motorola, Inc. (United States)


Published in SPIE Proceedings Vol. 5296:
Document Recognition and Retrieval XI
Elisa H. Barney Smith; Jianying Hu; James Allan, Editor(s)

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