(32) Automatic Evaluation Method for Machine Translation using Noun-Phrase Chunking
Hiroshi Echizen-ya, Kenji Araki
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, pp.108-117, 2010-7
As described in this paper, we propose a new automatic evaluation method for machine translation using noun-phrase chunking. Our method correctly determines the matching words between two sentences using corresponding noun phrases. Moreover, our method determines the similarity between two sentences in terms of the noun-phrase order of appearance. Evaluation experiments were conducted to calculate the correlation among human judgments, along with the scores produced using automatic evaluation methods for MT outputs obtained from the 12 machine translation systems in NTCIR-7. Experimental results show that our method obtained the highest correlations among the methods in both sentence-level adequacy and fluency.
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