Using Linguistic Knowledge for Machine Translation Evaluation with Hindi as a Target Language

Abstract

Several proposed metrics of MT Evaluation like BLEU have been criticized for their poor performance in evaluating machine translations. Languages like Hindi which have relatively free word-order and are morphologically rich pose additional problems in such evaluation. We attempt here to make use of linguistic knowledge to evaluate machine translations with Hindi as a target language. We formulate the problem of MT Evaluation as minimum cost assignment problem between test and reference translations with cost function based on linguistic knowledge.