Meta-evaluation of Machine Translation Using Parallel Legal Texts

In this paper we report our recent work on the evaluation of a number of popular automatic evaluation metrics for machine translation using parallel legal texts. The evaluation is carried Out, following a recognized evaluation protocol, to assess the reliability, the strengths and weaknesses of these evaluation metrics in terms of their correlation with human judgment of translation quality. The evaluation results confirm the reliability of the well-known evaluation metrics, BLEU and NIST for English-to-Chinese translation, and also show that our evaluation metric ATEC outperforms all others for Chinese-to-English translation. We also demonstrate the remarkable impact of different evaluation metrics on the ranking of online machine translation systems for legal translation.