A Comparative Study and Analysis of Evaluation Matrices in Machine Translation

Machine translation is a process of translating one natural language to another without much human interaction. Evaluation of any Machine Translation System (MTS) is the most important factor in a machine learning environment. There are many techniques existing to determine and optimize the quality of output in any MTS. Earlier methods are based on human judgments. Even though human evaluation methods are very much reliable, they suffer due to some disadvantages such as high cost, more time consuming and also poor re-usability. Hence, automatic methods have been proposed to reduce time and cost. In this survey, we have discussed different metrics under the automatic evaluation techniques in order to evaluate the output quality of MTS. It is believed that machine learning system developers at large would get befitted by this survey.