A language model using variable length tokens for open-vocabulary Hangul text recognition

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We propose a novel language model for Hangul text recognition. Without relying on prior linguistic knowledge in training, the proposed model learns variable length Hangul character sequences, which comprise the elementary tokens of Korean language, and their probabilities from statistics of a raw text corpus. Experiments in handwritten Hangul recognition shows that the proposed language model is effective in postprocessing of recognition results. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2004-07
Language
English
Article Type
Article
Keywords

UNITS

Citation

PATTERN RECOGNITION, v.37, no.7, pp.1549 - 1552

ISSN
0031-3203
DOI
10.1016/j.patcog.2003.12.004
URI
http://hdl.handle.net/10203/10241
Appears in Collection
CS-Journal Papers(저널논문)
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