Currently, post-editing of machine translation (MT) has been introduced as a regular practice in the translation workflow, especially since the good results in quality obtained by neural MT (NMT). This fact is linked to the efforts LSPs and customers have done to reduce costs due to the recent global crisis and the increasing globalization, which has had a negative impact on translators' revenues and on their working practices. In this context, post-editing is often perceived with a negative bias ...
Currently, post-editing of machine translation (MT) has been introduced as a regular practice in the translation workflow, especially since the good results in quality obtained by neural MT (NMT). This fact is linked to the efforts LSPs and customers have done to reduce costs due to the recent global crisis and the increasing globalization, which has had a negative impact on translators' revenues and on their working practices. In this context, post-editing is often perceived with a negative bias by translators. We study attitudes of translators post-editing for the first time and relate them to their productivity rates. We also compare the results with a survey answered by professional post-editors assessing their perception of the task in the current marketplace.
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