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dc.contributor.authorBerzak, Yevgeni
dc.contributor.authorReichart, Roi
dc.contributor.authorKatz, Boris
dc.date.accessioned2015-12-10T18:21:48Z
dc.date.available2015-12-10T18:21:48Z
dc.date.issued2014-04-25
dc.identifier.urihttp://hdl.handle.net/1721.1/100171
dc.description.abstractLinguists and psychologists have long been studying cross-linguistic transfer, the influence of native language properties on linguistic performance in a foreign language. In this work we provide empirical evidence for this process in the form of a strong correlation between language similarities derived from structural features in English as Second Language (ESL) texts and equivalent similarities obtained directly from the typological features of the native languages. We leverage this finding to recover native language typological similarity structure directly from ESL text, and perform prediction of typological features in an unsupervised fashion with respect to the target languages. Our method achieves 72.2% accuracy on the typology prediction task, a result that is highly competitive with equivalent methods that rely on typological resources.en_US
dc.description.sponsorshipThis work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216.en_US
dc.language.isoen_USen_US
dc.publisherCenter for Brains, Minds and Machines (CBMM), arXiven_US
dc.relation.ispartofseriesCBMM Memo Series;007
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subjectLanguageen_US
dc.subjectComputer Languageen_US
dc.subjectLinguisticsen_US
dc.subjectVisual Intelligenceen_US
dc.titleReconstructing Native Language Typology from Foreign Language Usageen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US
dc.typeOtheren_US
dc.identifier.citationarXiv:1404.6312v1en_US


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