Interpreting compounds for machine translation
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Automatic translation of noun compounds
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 4
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
SenseRelate::TargetWord: a generalized framework for word sense disambiguation
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Translation by machine of complex nominals: getting it right
MWE '04 Proceedings of the Workshop on Multiword Expressions: Integrating Processing
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Noun Compounds are a frequently occurring multiword expression in English written texts. English noun compounds are translated into varied syntactic constructs in Hindi. The performance of existing translation system makes the point clear that there exists no satisfactorily efficient Noun Compound translation tool from English to Hindi although the need of one is unprecedented in the context of machine translation. In this paper we integrate Noun Compound Translator [13], a statistical tool for Noun Compound translation, with the state-of-the-art machine translation tool, Moses [10]. We evaluate the integrated system on test data of 300 source language sentences which contain Noun Compounds and are translated manually into Hindi. A gain of 29% on BLEU score and 27% on Human evaluation has been observed on the test data.