Proceedings chapter
OA Policy
English

Preferences of end-users for raw and post-edited NMT in a business environment

Presented atLondon (UK), 21-22 November 2019
Publication date2019
Abstract

This paper presents an evaluation conducted with end-users of translations produced by Swiss Post's in-house Language Service. The aim is to assess whether end-users i) would rate post-edited MT more highly than raw MT; ii) would find that Swiss Post's customized NMT system produces better results than a general-purpose, off-the-shelf NMT engine (DeepL) and, lastly, when aware of translation production metadata, iii) would be willing to pay for post-edited texts. This latter aspect in particular was intended to help determine whether the customers would still value human intervention or whether they would rather accept a lower quality translation and associated risks if this means they can save on costs. Results show that the post-edited texts are preferred by the majority of the participants, even when production metadata are revealed. The in-house customized engine seems to produce better results than DeepL, since the end-users choose the raw output from our system more often than from DeepL.

Keywords
  • End-users
  • Neural machine translation
  • NMT
  • DeepL
  • Language service
Citation (ISO format)
GIRLETTI, Sabrina et al. Preferences of end-users for raw and post-edited NMT in a business environment. In: Proceedings of the 41st Conference Translating and the Computer. London (UK). [s.l.] : [s.n.], 2019. p. 47–59.
Main files (1)
Proceedings chapter (Published version)
Identifiers
  • PID : unige:127099
ISBN978-2970-10957-0
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181downloads

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