  Machine translation evaluation is a very important activity in machine
translation development. Automatic evaluation metrics proposed in literature
are inadequate as they require one or more human reference translations to
compare them with output produced by machine translation. This does not always
give accurate results as a text can have several different translations. Human
evaluation metrics, on the other hand, lacks inter-annotator agreement and
repeatability. In this paper we have proposed a new human evaluation metric
which addresses these issues. Moreover this metric also provides solid grounds
for making sound assumptions on the quality of the text produced by a machine
translation.
