Identifying translationese at the word and sub-word level.
We use text classification to distinguish automatically between original and translated texts in Hebrew, a morphologically complex language. To this end, we design several linguistically informed feature sets that capture word-level and sub-word-level (in particular, morphological) properties of Heb...
| Published in: | Digital Scholarship in the Humanities Vol. 31; no. 1; pp. 30 - 55 |
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| Main Authors: | , , |
| Format: | Article |
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Oxford University Press / USA
4/1/2016
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=114160245&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 114160245 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 2055768X JEO9 jtl: Digital Scholarship in the Humanities issn: 2055768X maglogo: N pubinfo: dt: 4/1/2016 vid: 31 iid: 1 pid: 622 pub: Oxford University Press / USA artinfo: ui: 114160245 10.1093/llc/fqu047 ppf: 30 ppct: 25 formats: fmt: @attributes: type: P size: 1.7MB tig: atl: Identifying translationese at the word and sub-word level. aug: au: Avner, Ehud Alexander Ordan, Noam Wintner, Shuly affil: Universität Potsdam, Germany Universität des Saarlandes, Germany University of Haifa, Israel su: Hebrew language Biblical language & style Jewish languages Morphology (Grammar) Humanities research sug: subj: Hebrew language Biblical language & style Jewish languages Morphology (Grammar) Humanities research ab: We use text classification to distinguish automatically between original and translated texts in Hebrew, a morphologically complex language. To this end, we design several linguistically informed feature sets that capture word-level and sub-word-level (in particular, morphological) properties of Hebrew. Such features are abstract enough to allow for the development of accurate, robust classifiers, and they also lend themselves to linguistic interpretation. Careful evaluation shows that some of the classifiers we define are, indeed, highly accurate, and scale up nicely to domains that they were not trained on. In addition, analysis of the best features provides insight into the morphological properties of translated texts. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: © 2019 EADH: The European Association for Digital Humanities. item: Digital Scholarship in the Humanities holder: Oxford University Press / USA dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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