15 December 2003 Online handwriting recognition in a form-filling task: evaluating the impact of context-awareness
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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.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Giovanni Seni, Giovanni Seni, Kimberly Rice, Kimberly Rice, Eddy Mayoraz, Eddy Mayoraz, } "Online handwriting recognition in a form-filling task: evaluating the impact of context-awareness", Proc. SPIE 5296, Document Recognition and Retrieval XI, (15 December 2003); doi: 10.1117/12.527115; https://doi.org/10.1117/12.527115
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