Machine Translation Quality and Post-Editor Productivity
We assessed how different machine translation (MT) systems affect the post-editing (PE) process and product of professional English–Spanish translators. Our model found that for each 1-point increase in BLEU, there is a PE time decrease of 0.16 seconds per word, about 3-4%. The MT system with the lowest BLEU score produced the output that was post-edited to the lowest quality and with the highest PE effort, measured both in HTER and actual PE operations.
PDF Abstract
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
