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A machine translationness typology for MT evaluations

In this article we present machine translationness (MTness, henceforth) as an approach for MT evaluations, in contrast to the notion of human likeness which is the basic criteria for state-of-the-art automatic evaluations. Our approach is based on the detection of phenomena that contribute to the MTness of a translation and, consequently, its poor fluency. We present here a typology of MTness based on an empirical study in which human and machine translations were Turing tested. We also discuss the types of the typology that should be focused on in MT evaluations, the subjective quality of the human likeness assumption, and the advantages of the MTness approach, in terms of time and financial costs.