Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40544
DC FieldValue
dc.titleInfluence of language models and candidate set size on contextual post-processing for chinese script recognition
dc.contributor.authorLi, Y.-X.
dc.contributor.authorTan, C.L.
dc.date.accessioned2013-07-04T08:06:47Z
dc.date.available2013-07-04T08:06:47Z
dc.date.issued2004
dc.identifier.citationLi, Y.-X.,Tan, C.L. (2004). Influence of language models and candidate set size on contextual post-processing for chinese script recognition. Proceedings - International Conference on Pattern Recognition 2 : 537-540. ScholarBank@NUS Repository.
dc.identifier.issn10514651
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40544
dc.description.abstractIn the Chinese language, a word consisting of one or more characters is a basic syntax-meaningful unit, however, each character in the word also has a definite meaning in itself. In this paper, we compare the perplexities of four n-gram language models (character-based bigram, character-based trigram, word-based bigram and class-based bigram) and their influence on the performance of contextual post-processing of Chinese scripts in an offline handwritten Chinese character recognition system. We also demonstrate the influence of the candidate set size on the performance of contextual post-processing in detail, and indicate that the number of candidates should vary with each script.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings - International Conference on Pattern Recognition
dc.description.volume2
dc.description.page537-540
dc.description.codenPICRE
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

Page view(s)

51
checked on Jun 22, 2019

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.