Scrambling is acceptable reordering of verb arguments in languages such as Japanese and German. In automatic evaluation of translation quality, BLEU is the de facto standard method, but BLEU has only very weak correlation with human judgements in case of Japanese-to-English/English-to-Japanese translations. Therefore, alternative methods, IMPACT and RIBES, were proposed and they have shown much stronger correlation than BLEU. Now, RIBES is widely used in recent papers on Japanese-related translations. RIBES compares word order of MT output with manually translated reference sentences but it does not regard scrambling at all. In this paper, we present a method to enumerate scrambled sentences from dependency trees of reference sentences. Our experiments based on NTCIR Patent MT data show that the method improves sentence-level correlation between RIBES and human-judged adequacy.
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