Improvement of machine translation evaluation by simple linguistically motivated features
Journal of Computer Science and Technology - Special issue on natural language processing
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Human evaluation of translation involves many aspects. In this paper we try to make some quantitative analyses on factors influencing translation scores generated by human. We focus on some linguistic features especially some translation error types which may affect human evaluation. The experiment shows that the inconsistency in thematic knowledge and the semantic incoherence in target text have a high correlation with human evaluation. We also show that correlations can be achieved by adopting some linguistic features into the automatic translation evaluation models.