  The overall translation quality reached by current machine translation (MT)
systems for high-resourced language pairs is remarkably good. Standard methods
of evaluation are not suitable nor intended to uncover the many translation
errors and quality deficiencies that still persist. Furthermore, the quality of
standard reference translations is commonly questioned and comparable quality
levels have been reached by MT alone in several language pairs. Navigating
further research in these high-resource settings is thus difficult. In this
article, we propose a methodology for creating more reliable document-level
human reference translations, called "optimal reference translations," with the
simple aim to raise the bar of what should be deemed "human translation
quality." We evaluate the obtained document-level optimal reference
translations in comparison with "standard" ones, confirming a significant
quality increase and also documenting the relationship between evaluation and
translation editing.
