- On the features of translationese | Digital Scholarship in the . . .
We demonstrate that some feature sets are indeed good indicators of translationese, thereby corroborating some hypotheses, whereas others perform much worse (sometimes at chance level), indicating that some ‘universal’ assumptions have to be reconsidered
- On the Features of Translationese
When generating many of the features, we normalize the feature's value, v, by the number of tokens in the chunk, n: v0 = v 2000=n This balances the values over chunks that have slightly more or less than 2000 tokens each (recall that chunks respect sentence boundaries)
- On the features of translationese - University of Haifa
Volansky, V , Ordan, N , Wintner, S (2015) On the features of translationese Digital Scholarship in the Humanities, 30 (1), 98-118 https: doi org 10 1093 llc fqt031
- On the features of translationese - ResearchGate
Volansky, Ordan, and Wintner (2015) also employ SVMs Their data consist of translations of the proceedings of the European Parliament from ten SLs (Danish, Dutch, Finnish, French, German,
- THE FEATURES OF TRANSLATIONESE - Semantic Scholar
Vered Volansky, Noam Ordan, and Shuly Wintner, \On the Features of Translationese", Literary and Linguistic Computing, forthcoming Goal: test Translation Studies hypotheses using classi cation as a methodology Experimental setup: EUROPARL, 4M tokens in English (O) and 400K tokens translated from each of ten European languages (T) After
- Noam Ordan - Google Scholar
unaffiliated - Cited by 1,169 - text classification - machine translation - semantics
- Sci-Hub | On the features of translationese. Digital Scholarship in the . . .
Sci-Hub | On the features of translationese Digital Scholarship in the Humanities, 30 (1), 98–118 | 10 1093 llc fqt031 hubto open science ↓ save
- arXiv:1509. 03611v1 [cs. CL] 11 Sep 2015
bersky, Noam Ordan, and Shuly Wintner Language models for machine trans lation: Original vs translated texts In Proceedings of the 2011 Conference on Empiri-cal Methods in Natural Language Processing, pages 363{3
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