Paper: The Contribution of Linguistic Features to Automatic Machine Translation Evaluation

ACL ID P09-1035
Title The Contribution of Linguistic Features to Automatic Machine Translation Evaluation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2009
Authors

A number of approaches to Automatic MT Evaluation based on deep linguistic knowledge have been suggested. How- ever, n-gram based metrics are still to- day the dominant approach. The main reason is that the advantages of employ- ing deeper linguistic information have not been clarified yet. In this work, we pro- pose a novel approach for meta-evaluation of MT evaluation metrics, since correla- tion cofficient against human judges do not reveal details about the advantages and disadvantages of particular metrics. We then use this approach to investigate the benefits of introducing linguistic features into evaluation metrics. Overall, our ex- periments show that (i) both lexical and linguistic metrics present complementary advantages and (ii) combining both kinds of metrics yields the most r...