  Re-speaking is a mechanism for obtaining high quality subtitles for use in
live broadcast and other public events. Because it relies on humans performing
the actual re-speaking, the task of estimating the quality of the results is
non-trivial. Most organisations rely on humans to perform the actual quality
assessment, but purely automatic methods have been developed for other similar
problems, like Machine Translation. This paper will try to compare several of
these methods: BLEU, EBLEU, NIST, METEOR, METEOR-PL, TER and RIBES. These will
then be matched to the human-derived NER metric, commonly used in re-speaking.
