A systematic comparison of various statistical alignment models
Computational Linguistics
Models of translational equivalence among words
Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Maximum entropy based phrase reordering model 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
Combining clues for lexical level aligning using the null hypothesis approach
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Hierarchical Phrase-Based Translation
Computational Linguistics
Machine translation system combination using ITG-based alignments
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
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
Improving alignments for better confusion networks for combining machine translation systems
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Regenerating hypotheses for statistical machine translation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Indirect-HMM-based hypothesis alignment for combining outputs from machine translation systems
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
N-gram posterior probabilities for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
System Combination for Machine Translation of Spoken and Written Language
IEEE Transactions on Audio, Speech, and Language Processing
A hybrid morpheme-word representation for machine translation of morphologically rich languages
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
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Recently confusion network decoding shows the best performance in combining outputs from multiple machine translation (MT) systems. However, overcoming different word orders presented in multiple MT systems during hypothesis alignment still remains the biggest challenge to confusion network-based MT system combination. In this paper, we compare four commonly used word alignment methods, namely GIZA++, TER, CLA and IHMM, for hypothesis alignment. Then we propose a method to build the confusion network from intersection word alignment, which utilizes both direct and inverse word alignment between the backbone and hypothesis to improve the reliability of hypothesis alignment. Experimental results demonstrate that the intersection word alignment yields consistent performance improvement for all four word alignment methods on both Chinese-to-English spoken and written language tasks.