A systematic comparison of various statistical alignment models
Computational Linguistics
Word reordering and a dynamic programming beam search algorithm for statistical machine translation
Computational Linguistics
Models of translational equivalence among words
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
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
A probability model to improve word alignment
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - 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
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
A word-to-phrase statistical translation model
ACM Transactions on Speech and Language Processing (TSLP)
Combining clues for lexical level aligning using the null hypothesis approach
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Association-based bilingual word alignment
ParaText '05 Proceedings of the ACL Workshop on Building and Using Parallel Texts
Discriminative alignment training without annotated data for machine translation
NAACL-Short '07 Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers
What types of word alignment improve statistical machine translation?
Machine Translation
| Hi-index | 0.01 |
This paper investigates the combination of word-alignments computed with the competitive linking algorithm and well-established IBM models. New training methods for phrase-based statistical translation are proposed, which have been evaluated on a popular traveling domain task, with English as target language, and Chinese, Japanese, Arabic and Italian as source languages. Experiments were performed with a highly competitive phrase-based translation system, which ranked at the top in the 2005 IWSLT evaluation campaign. By applying the proposed techniques, even under very different data-sparseness conditions, consistent improvements in BLEU and NIST scores were obtained on all considered language pairs.