Automatic Rule Learning for Resource-Limited MT
AMTA '02 Proceedings of the 5th Conference of the Association for Machine Translation in the Americas on Machine Translation: From Research to Real Users
A new statistical parser based on bigram lexical dependencies
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Evaluating translational correspondence using annotation projection
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Word alignment with cohesion constraint
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
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The frequent occurrence of divergences—structural differences between languages---presents a great challenge for statistical word-level alignment and machine translation. This paper describes the adaptation of DUSTer, a divergence unraveling package, to Hindi during the DARPA TIDES-2003 Surprise Language Exercise. We show that it is possible to port DUSTer to Hindi in under 3 days.