Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64534
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Chinese and Bilingual Studies-
dc.creatorYao, Y-
dc.date.accessioned2017-02-23T04:38:08Z-
dc.date.available2017-02-23T04:38:08Z-
dc.identifier.urihttp://hdl.handle.net/10397/64534-
dc.language.isoenen_US
dc.rightsCopyright 2015 by Yao Yaoen_US
dc.titleA review of corpus-based statistical models of language variationen_US
dc.typeConference Paperen_US
dc.identifier.spage11en_US
dc.identifier.epage15en_US
dcterms.abstractThis paper is a brief review of the research on language variation using corpus data and statistical modeling methods. The variation phenomena covered in this review include phonetic variation (in spontaneous speech) and syntactic variation, with a focus on studies of English and Chinese. The goal of this paper is to demonstrate the use of corpus-driven statistical models in the study of language variation, and discuss the contribution and future directions of this line of research.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationThe 29th Pacific Asia Conference on Language, Information and Computation : Proceedings of PACLIC 2015 : Oral Papers, Shanghai, China, Oct 30 - Nov 1, 2015, p. 11-15-
dcterms.issued2015-
dc.relation.conferencePacific Asia Conference on Language, Information and Computation [PACLIC]-
dc.identifier.rosgroupid2015002665-
dc.description.ros2015-2016 > Academic research: refereed > Invited conference paper-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera0054-n03en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCopyright retained by authoren_US
Appears in Collections:Conference Paper
Files in This Item:
File Description SizeFormat 
Yao_Corpus-based_Statistical_Models.pdf323.02 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Show simple item record

Page views

200
Last Week
0
Last month
Citations as of Oct 6, 2025

Downloads

90
Citations as of Oct 6, 2025

Google ScholarTM

Check


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