A statistical approach to machine translation
Computational Linguistics
Empirical Methods for MT Lexicon Development
AMTA '98 Proceedings of the Third Conference of the Association for Machine Translation in the Americas on Machine Translation and the Information Soup
AMTA '00 Proceedings of the 4th Conference of the Association for Machine Translation in the Americas on Envisioning Machine Translation in the Information Future
Learning dependency translation models as collections of finite-state head transducers
Computational Linguistics - Special issue on finite-state methods in NLP
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
A framework for MT and multilingual NLG systems based on uniform lexico-structural processing
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Learning parse and translation decisions from examples with rich context
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Chart-based transfer rule application in Machine Translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Finding structural correspondences from bilingual parsed corpus for corpus-based translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th 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
Inducing multilingual POS taggers and NP bracketers via robust projection across aligned corpora
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Sample selection for statistical grammar induction
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
Inducing lexico-structural transfer rules from parsed Bi-texts
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
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 categorial variation database for English
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
Improving bitext word alignments via syntax-based reordering of English
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
NeurAlign: combining word alignments using neural networks
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Alignment link projection using transformation-based learning
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Dependency-Based Chinese-English Statistical Machine Translation
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
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The frequent occurrence of divergences--structural differences between languages--presents a great challenge for statistical word-level alignment. In this paper, we introduce DUSTer, a method for systematically identifying common divergence types and transforming an English sentence structure to bear a closer resemblance to that of another language. Our ultimate goal is to enable more accurate alignment and projection of dependency trees in another language without requiring any training on dependency-tree data in that language. We present an empirical analysis comparing the complexities of performing word-level alignments with and without divergence handling. Our results suggest that our approach facilitates word-level alignment, particularly for sentence pairs containing divergences.