{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T00:16:59Z","timestamp":1782173819563,"version":"3.54.5"},"reference-count":48,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2011,12,1]],"date-time":"2011-12-01T00:00:00Z","timestamp":1322697600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["6.09E+15"],"award-info":[{"award-number":["6.09E+15"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Research Grants Council, University Grants Committee, Hong Kong","doi-asserted-by":"publisher","award":["2.01E+13"],"award-info":[{"award-number":["2.01E+13"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2011,12]]},"abstract":"<jats:p>The poor grammatical output of Machine Translation (MT) systems appeals syntax-based approaches within language modeling. However, previous studies showed that syntax-based language modeling using (Context-Free) Treebank Grammars was not very helpful in improving BLEU scores for Chinese-English machine translation. In this article we further study this issue in the context of Chinese-English syntax-based Statistical Machine Translation (SMT) where Synchronous Tree Substitution Grammars (STSGs) are utilized to model the translation process. In particular, we develop a Tree Substitution Grammar-based language model for syntax-based MT, and present three methods to efficiently integrate the proposed language model into MT decoding. In addition, we design a simple and effective method to adapt syntax-based language models for MT tasks. We demonstrate that the proposed methods are able to benefit a state-of-the-art syntax-based MT system. On the NIST Chinese-English MT evaluation corpora, we finally achieve an improvement of 0.6 BLEU points over the baseline.<\/jats:p>","DOI":"10.1145\/2025384.2025386","type":"journal-article","created":{"date-parts":[[2011,12,6]],"date-time":"2011-12-06T19:05:23Z","timestamp":1323198323000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Language Modeling for Syntax-Based Machine Translation Using Tree Substitution Grammars"],"prefix":"10.1145","volume":"10","author":[{"given":"Tong","family":"Xiao","sequence":"first","affiliation":[{"name":"Northeastern University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingbo","family":"Zhu","sequence":"additional","affiliation":[{"name":"Northeastern University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhua","family":"Zhu","sequence":"additional","affiliation":[{"name":"Northeastern University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2011,12]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL\u201904)","author":"Bacchiani M."},{"key":"e_1_2_1_2_1","unstructured":"Beal M. 2003. 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Head-driven statistical models for natural language parsing. PhD. dissertation. University of Pennsylvania. Collins M. 1999. Head-driven statistical models for natural language parsing. PhD. dissertation. 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Speech and Language Processing 2nd Ed. Prentice-Hall Upper Saddle River NJ. Jurafsky D. and Martin J. 2008. Speech and Language Processing 2nd Ed. Prentice-Hall Upper Saddle River NJ."},{"key":"e_1_2_1_21_1","unstructured":"Knight K. 2009. Bayesian Inference with Tears. Tutorial Workbook. Knight K. 2009. Bayesian Inference with Tears . Tutorial Workbook."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30586-6_1"},{"key":"e_1_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Knight K. and Koehn P. 2009. Topics in statistical machine translation. In Tutorial of the Association for Computational Linguistics (ACL\u201909). Knight K. and Koehn P. 2009. Topics in statistical machine translation . 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