Integrating language model in handwritten Chinese text recognition

Qiu Feng Wang*, Fei Yin, Cheng Lin Liu

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

37 Citations (Scopus)

Abstract

This paper describes a system for handwritten Chinese text recognition integrating language model. On a text line image, the system generates character segmentation and word segmentation candidates, and the candidate paths are evaluated by character recognition scores and language model. The optimal path, giving segmentation and recognition result, is found using a pruned dynamic programming search method. We evaluate various language models, including the character-based n-gram, word-based n-gram, and hybrid n-gram models. Experimental results on the HIT-HW database show that the language models improve the recognition performance remarkably.

Original languageEnglish
Title of host publicationICDAR2009 - 10th International Conference on Document Analysis and Recognition
Pages1036-1040
Number of pages5
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventICDAR2009 - 10th International Conference on Document Analysis and Recognition - Barcelona, Spain
Duration: 26 Jul 200929 Jul 2009

Publication series

NameProceedings of the International Conference on Document Analysis and Recognition, ICDAR
ISSN (Print)1520-5363

Conference

ConferenceICDAR2009 - 10th International Conference on Document Analysis and Recognition
Country/TerritorySpain
CityBarcelona
Period26/07/0929/07/09

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