A systematic comparison of various statistical alignment models
Computational Linguistics
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Reliable measures for aligning Japanese-English news articles and sentences
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A comparative study on reordering constraints in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The Alignment Template Approach to Statistical Machine Translation
Computational Linguistics
A phrase-based, joint probability model for statistical machine translation
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Statistical machine translation by parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Dependency treelet translation: syntactically informed phrasal SMT
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Machine translation using probabilistic synchronous dependency insertion grammars
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Tree-to-string alignment template for statistical machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Scalable inference and training of context-rich syntactic translation models
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Reordering constraints for phrase-based statistical machine translation
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
SPMT: statistical machine translation with syntactified target language phrases
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A unigram orientation model for statistical machine translation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Cohesive constraints in a beam search phrase-based decoder
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Reordering model using syntactic information of a source tree for statistical machine translation
SSST '09 Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation
Filtering syntactic constraints for statistical machine translation
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Linguistically annotated reordering: Evaluation and analysis
Computational Linguistics
Reordering constraint based on document-level context
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Hi-index | 0.00 |
In current statistical machine translation (SMT), erroneous word reordering is one of the most serious problems. To resolve this problem, many word-reordering constraint techniques have been proposed. The inversion transduction grammar (ITG) is one of these constraints. In ITG constraints, target-side word order is obtained by rotating nodes of the source-side binary tree. In these node rotations, the source binary tree instance is not considered. Therefore, stronger constraints for word reordering can be obtained by imposing further constraints derived from the source tree on the ITG constraints. For example, for the source word sequence { a b c d }, ITG constraints allow a total of twenty-two target word orderings. However, when the source binary tree instance ((a b) (c d)) is given, our proposed "imposing source tree on ITG" (IST-ITG) constraints allow only eight word orderings. The reduction in the number of word-order permutations by our proposed stronger constraints efficiently suppresses erroneous word orderings. In our experiments with IST-ITG using the NIST MT08 English-to-Chinese translation track's data, the proposed method resulted in a 1.8-points improvement in character BLEU-4 (35.2 to 37.0) and a 6.2% lower CER (74.1 to 67.9%) compared with our baseline condition.