An unsupervised learning method for associative relationships between verb phrases
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Lexical query paraphrasing for document retrieval
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Automatic evaluation of texts by using paraphrases
LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
"I thou thee, thou traitor": predicting formal vs. informal address in English literature
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Combining sentence length with location information to align monolingual parallel texts
AIRS'04 Proceedings of the 2004 international conference on Asian Information Retrieval Technology
Towards a model of formal and informal address in English
EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
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Automatic evaluation of translation quality has proved to be useful when the target language is English. In this paper the evaluation of translation into Japanese is studied. An existing method based on n-gram similarity between translations and reference sentences is difficult to apply to the evaluation of Japanese because of the agglutinativeness and variation of semantically similar expressions in Japanese. The proposed method applies a set of paraphrasing rules to the reference sentences in order to increase the similarity score for the expressions that differ only in their writing styles. Experimental results show the paraphrasing rules improved the correlation between automatic evaluation and human evaluation from 0.80 to 0.93.