Abstract:Due to the wide-spread development of Machine Translation (MT) systems-especially Neural Machine Translation (NMT) systems-MT evaluation, both automatic and human, has become more and more important as it helps us establish how MT systems perform. Yet, automatic evaluation metrics have lagged behind, as the most popular choices (e.g., BLEU, METEOR and ROUGE) may correlate poorly with human judgments. This paper seeks to put to the test an evaluation model based on a novel deep learning schema (NoDeeLe) used to… Show more
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