A word language model based contextual language processing on Chinese character recognition

2010 ◽  
Author(s):  
Chen Huang ◽  
Xiaoqing Ding ◽  
Yan Chen
Keyword(s):  
Language Processing ◽  
Character Recognition ◽  
Chinese Character ◽  
Language Model ◽  
Chinese Character Recognition ◽  
Model Based

A HYBRID POST-PROCESSING SYSTEM FOR OFFLINE HANDWRITTEN CHINESE CHARACTER RECOGNITION BASED ON A STATISTICAL LANGUAGE MODEL

2005 ◽  
Vol 19 (03) ◽  
pp. 415-428 ◽  
Author(s):  
RUIFENG XU ◽  
DANIEL S. YEUNG ◽  
DAMING SHI
Keyword(s):  
Character Recognition ◽  
Chinese Character ◽  
Language Model ◽  
Recognition Rate ◽  
Processing System ◽  
Misclassification Rate ◽  
Post Processing ◽  
Chinese Character Recognition ◽  
Handwritten Chinese Character Recognition ◽  
Word Lattice

This paper presents a post-processing system for improving the recognition rate of a Handwritten Chinese Character Recognition (HCCR) device. This three-stage hybrid post-processing system reduces the misclassification and rejection rates common in the single character recognition phase. The proposed system is novel in two respects: first, it reduces the misclassification rate by applying a dictionary-look-up strategy that bind the candidate characters into a word-lattice and appends the linguistic-prone characters into the candidate set; second, it identifies promising sentences by employing a distant Chinese word BI-Gram model with a maximum distance of three to select plausible words from the word-lattice. These sentences are then output as the upgraded result. Compared with one of our previous works in single Chinese character recognition, the proposed system improves absolute recognition rates by 12%.

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