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Copyright and the reuse of translation as data

Moorkens, Joss orcid logoORCID: 0000-0003-0766-0071 and Lewis, David orcid logoORCID: 0000-0002-3503-4644 (2019) Copyright and the reuse of translation as data. In: O'Hagan, Minako, (ed.) The Routledge Handbook of Translation and Technology. Routledge Translation Handbooks . Routledge, Abingdon, UK, pp. 469-481. ISBN 9781138232846

Abstract
Translation copyright was first codified as a derivative work in the Berne Convention of 1886, subject to the rights of the creator of the original work. While most countries are now contracting parties to the Berne Convention, differing interpretations and additional laws and directives mean that rights to ownership of a translation are not consistent in all jurisdictions. The original intention of the Berne Convention was to protect authors’ rights and to prevent piracy, and the authors could not have foreseen the large scale reuse of translations, initially via translation memory tools, then as training data for machine translation (MT) systems. Parallel data is repurposed in ever-increasing amounts, but broken down to word and subword levels. At present, rights to ownership are rarely passed to the translator, meaning that, while an initial translation may be costly, secondary uses are very inexpensive. This chapter explores the history of translation copyright and leveraging, and introduces concerns relating to machine learning more generally and applies them to translation.
Metadata
Item Type:Book Section
Refereed:Yes
Uncontrolled Keywords:translation copyright; machine learning; machine translation; language resources; translation memory; data dispossession
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Applied Language and Intercultural Studies
Research Initiatives and Centres > Centre for Translation and Textual Studies (CTTS)
Research Initiatives and Centres > ADAPT
Publisher:Routledge
Official URL:http://dx.doi.org/10.4324/9781315311258-28
Copyright Information:© 2019
Funders:Science Foundation Ireland 13/RC/2106 (ADAPT)
ID Code:23974
Deposited On:29 Nov 2019 15:44 by Joss Moorkens . Last Modified 20 May 2021 13:58
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