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Unlike traditional HMMs whose parameters are trained via maximum likelihood estimation (MLE), the parameters of the IHMM are estimated indirectly from a variety of sources including word semantic similarity, word surface similarity, and a distance-based distortion penalty. The IHMM-based method significantly outperforms the state-of-the-art, TER-based alignment model in our experiments on NIST benchmark datasets. Our combined SMT system using the proposed method achieved the best Chinese-to-English translation result in the constrained training track of the 2008 NIST Open MT Evaluation.<\/jats:p>","DOI":"10.1145\/1526252.1526254","type":"journal-article","created":{"date-parts":[[2009,6,2]],"date-time":"2009-06-02T14:51:08Z","timestamp":1243954268000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Improved Monolingual Hypothesis Alignment for Machine Translation System Combination"],"prefix":"10.1145","volume":"8","author":[{"given":"Xiaodong","family":"He","sequence":"first","affiliation":[{"name":"Microsoft Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mei","family":"Yang","sequence":"additional","affiliation":[{"name":"University of Washington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianfeng","family":"Gao","sequence":"additional","affiliation":[{"name":"Microsoft Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Nguyen","sequence":"additional","affiliation":[{"name":"Microsoft Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Moore","sequence":"additional","affiliation":[{"name":"Microsoft Research"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2009,5]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1610075.1610140"},{"volume-title":"Proceedings of the IEEE Conference on Automatic Speech Recognition and Understanding (ASRU\u201901)","author":"Bangalore S.","key":"e_1_2_1_2_1","unstructured":"Bangalore , S. , Bordel , G. , and Riccardi , G . 2001. Computing consensus translation from multiple machine translation systems . In Proceedings of the IEEE Conference on Automatic Speech Recognition and Understanding (ASRU\u201901) . 351--354. Bangalore, S., Bordel, G., and Riccardi, G. 2001. Computing consensus translation from multiple machine translation systems. In Proceedings of the IEEE Conference on Automatic Speech Recognition and Understanding (ASRU\u201901). 351--354."},{"volume-title":"Algorithms for minimization without derivatives","author":"Brent R.","key":"e_1_2_1_3_1","unstructured":"Brent , R. 1973. Algorithms for minimization without derivatives . Prentice-Hall , Chapter 7. Brent, R. 1973. Algorithms for minimization without derivatives. 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In Proceedings of the Human Language Technology Conference (ACL-HLT\u201908) . 81--84. Karakos, D., Eisner, J., Khudanpur, S., and Dreyer, M. 2008. Machine translation system combination using ITG-based alignments. In Proceedings of the Human Language Technology Conference (ACL-HLT\u201908). 81--84."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.3115\/1073445.1073462"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3115\/1075096.1075152"},{"volume-title":"Proceedings of the Association on Computer Linguistics (ACL\u201907)","author":"Li C.-H.","key":"e_1_2_1_15_1","unstructured":"Li , C.-H. , Li , M. , Zhang , D. , Li , M. , Zhou , M. , and Guan , Y . 2007. A probabilistic approach to syntax-based reordering for statistical machine translation . In Proceedings of the Association on Computer Linguistics (ACL\u201907) . 720--727. Li, C.-H., Li, M., Zhang, D., Li, M., Zhou, M., and Guan, Y. 2007. 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