  Length-controllable machine translation is a type of constrained translation.
It aims to contain the original meaning as much as possible while controlling
the length of the translation. We can use automatic summarization or machine
translation evaluation metrics for length-controllable machine translation, but
this is not necessarily suitable and accurate. This work is the first attempt
to evaluate the automatic metrics for length-controllable machine translation
tasks systematically. We conduct a rigorous human evaluation on two translation
directions and evaluate 18 summarization or translation evaluation metrics. We
find that BLEURT and COMET have the highest correlation with human evaluation
and are most suitable as evaluation metrics for length-controllable machine
translation.
