Issue #10 – Evaluating Neural MT post-editing
20 Sep18
Issue #10 – Evaluating Neural MT post-editing
Author: Dr. Joss Moorkens, Assistant Professor, Dublin City University
This week, we have a guest post from Prof. Joss Moorkens of Dublin City University. Joss is renowned for his work in the area of translation technology and, particularly, the evaluation of MT output for certain use cases. Building on the “human parity” topic from Issue #8 of this series, Joss describes his recent work on evaluation of Neural MT post-editing for dissemination.
Dissemination vs. Assimilation
The previous articles in the Neural MT Weekly have looked at various aspects of NMT training, data preparation, and evaluation. Once you’ve produced the NMT output, what happens next? MT for assimilation means that raw MT is the end product, giving a gist translation; MT for dissemination means that MT output is “an intermediate step in the production” of the final text, usually followed by post-editing (there’s a good definition of this in Forcada 2010), and it’s that latter use of MT that’s the topic of this article.
Is NMT post-editing faster than SMT post-editing?
When we carried out a comparative evaluation of statistical and neural MT as part of the
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