Analysis and evaluation of dictionary learning on a handy type pen-input interface for personal use.

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Bibliographic Details
Title:	Analysis and evaluation of dictionary learning on a handy type pen-input interface for personal use.
Authors:	Kimura, Yoshimasa¹, Odaka, Kazumi², Suzuki, Akira³, Sano, Mutsuo²
Source:	Systems & Computers in Japan. 4/1/2003, Vol. 34 Issue 4, p34-45. 12p.
Subjects:	Learning, Pen-based computers, User interfaces, Human-computer interaction, Systems design, Personal computers
Abstract:	We present the learning characteristics of personal dictionaries used for handy type pen-input interfaces. The personal dictionary grows by acquiring misrecognized input patterns whenever they are generated. Personal character pattern data is collected using a handy type tablet. The correct recognition rate of the data, which consists of 756 characters with 391 different characters, is improved from 79.9% to 96.2% for data used in learning, and from 78.0% to 95.4% for unlearnt data. On the contrary, the decrease of recognition rate by this learning is 0.1% –0.2%, which is negligible. The results show that the learning yields a handy type pen-input interface that is sufficient for practical use, moreover, this paper clarifies the learning characteristics against changesin writing condition, the number of objective categories, the number of registered patterns in the personal dictionary, and the formation process of the personal dictionary. Analysis and evaluation of the results gives useful instruction on the design of recognition systems. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(4): 34–45, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.1199 [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	We present the learning characteristics of personal dictionaries used for handy type pen-input interfaces. The personal dictionary grows by acquiring misrecognized input patterns whenever they are generated. Personal character pattern data is collected using a handy type tablet. The correct recognition rate of the data, which consists of 756 characters with 391 different characters, is improved from 79.9% to 96.2% for data used in learning, and from 78.0% to 95.4% for unlearnt data. On the contrary, the decrease of recognition rate by this learning is 0.1% –0.2%, which is negligible. The results show that the learning yields a handy type pen-input interface that is sufficient for practical use, moreover, this paper clarifies the learning characteristics against changesin writing condition, the number of objective categories, the number of registered patterns in the personal dictionary, and the formation process of the personal dictionary. Analysis and evaluation of the results gives useful instruction on the design of recognition systems. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(4): 34–45, 2003; Published online in Wiley InterScience (<URL>www.interscience.wiley.com</URL>). DOI 10.1002/scj.1199 [ABSTRACT FROM AUTHOR]
ISSN:	08821666
DOI:	10.1002/scj.1199