Isao Goto
Skip Abstract Section
Abstract
When translating between languages with widely different word orders, word reordering can present a major challenge. Although some word reordering methods do not employ source-language syntactic structures, such structures are inherently useful for word reordering. However, high-quality syntactic parsers are not available for many languages. We propose a preordering method using a target-language syntactic parser to process source-language syntactic structures without a source-language syntactic parser. To train our preordering model based on ITG, we produced syntactic constituent structures for source-language training sentences by (1) parsing target-language training sentences, (2) projecting constituent structures of the target-language sentences to the corresponding source-language sentences, (3) selecting parallel sentences with highly synchronized parallel structures, (4) producing probabilistic models for parsing using the projected partial structures and the Pitman-Yor process, and (5) parsing to produce full binary syntactic structures maximally synchronized with the corresponding target-language syntactic structures, using the constraints of the projected partial structures and the probabilistic models. Our ITG-based preordering model is trained using the produced binary syntactic structures and word alignments. The proposed method facilitates the learning of ITG by producing highly synchronized parallel syntactic structures based on cross-language syntactic projection and sentence selection. The preordering model jointly parses input sentences and identifies their reordered structures. Experiments with Japanese--English and Chinese--English patent translation indicate that our method outperforms existing methods, including string-to-tree syntax-based SMT, a preordering method that does not require a parser, and a preordering method that uses a source-language dependency parser.
- A. V. Aho and J. D. Ullman. 1969. Syntax directed translations and the pushdown assembler. J. Comput. Syst. Sci. 3, 1, 37--56. DOI: http://dx.doi.org/10.1016/S0022-0000(69)80006-1. Google Scholar
Digital Library
- Ibrahim Badr, Rabih Zbib, and James Glass. 2009. Syntactic phrase reordering for English-to-Arabic statistical machine translation. In Proceedings of the 12th Conference of the European Chapter of the ACL (EACL’09). Association for Computational Linguistics, 86--93. http://www.aclweb.org/anthology/E09-1011. Google ScholarDigital Library
- Pi-Chuan Chang, Huihsin Tseng, Dan Jurafsky, and Christopher D. Manning. 2009. Discriminative reordering with Chinese grammatical relations features. In Proceedings of the 3rd Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT. Association for Computational Linguistics, 51--59. http://www.aclweb.org/anthology/W09-2307. Google ScholarDigital Library
- Stanley F. Chen and Joshua T. Goodman. 1998. An empirical study of smoothing techniques for language modeling. Technical Report TR-10-98. Computer Science Group, Harvard University.Google Scholar
- David Chiang. 2007. Hierarchical phrase-based translation. Comput. Linguist. 33, 2, 201--228. Google ScholarDigital Library
- Michael Collins, Philipp Koehn, and Ivona Kucerova. 2005. Clause restructuring for statistical machine translation. In Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05). Association for Computational Linguistics, 531--540.DOI: http://dx.doi.org/10.3115/1219840.1219906. Google ScholarDigital Library
- John DeNero and Jakob Uszkoreit. 2011. Inducing sentence structure from parallel corpora for reordering. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 193--203.http://www.aclweb.org/anthology/D11-1018. Google ScholarDigital Library
- Chris Dyer and Philip Resnik. 2010. Context-free reordering, finite-state translation. In Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 858--866. http://www.aclweb.org/anthology/N10-1128. Google ScholarDigital Library
- Niyu Ge. 2010. A direct syntax-driven reordering model for phrase-based machine translation. In Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 849--857. http://www.aclweb.org/anthology/N10-1127. Google ScholarDigital Library
- Dmitriy Genzel. 2010. Automatically learning source-side reordering rules for large scale machine translation. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING’10), 376--384. http://www.aclweb.org/anthology/C10-1043. Google ScholarDigital Library
- Isao Goto, Bin Lu, Ka Po Chow, Eiichiro Sumita, and Benjamin K. Tsou. 2011. Overview of the patent machine translation task at the NTCIR-9 Workshop. In Proceedings of NTCIR-9. 559--578.Google Scholar
- Isao Goto, Ka Po Chow, Bin Lu, Eiichiro Sumita, and Benjamin K. Tsou. 2013a. Overview of the patent machine translation task at the NTCIR-10 Workshop. In Proceedings of NTCIR-10. 260--286.Google Scholar
- Isao Goto, Masao Utiyama, and Eiichiro Sumita. 2013b. Post-ordering by parsing with ITG for Japanese-English statistical machine translation. ACM Trans. Asian Lang. Inf. Process. 12, 4, Article 17, 22 pages. DOI: http://dx.doi.org/10.1145/2518100. Google ScholarDigital Library
- Isao Goto, Masao Utiyama, Eiichiro Sumita, Akihiro Tamura, and Sadao Kurohashi. 2014. Distortion model based on word sequence labeling for statistical machine translation.ACM Trans. Asian Lang. Inf. Process. 13, 1, Article 2, 21 pages. DOI: http://dx.doi.org/10.1145/2537128. Google ScholarDigital Library
- Nizar Habash. 2007. Syntactic preprocessing for statistical machine translation. In Proceedings of the Machine Translation Summit XI. 215--222.Google Scholar
- Katsuhiko Hayashi, Katsuhito Sudoh, Hajime Tsukada, Jun Suzuki, and Masaaki Nagata. 2013. Shift-reduce word reordering for machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics,1382--1386. http://www.aclweb.org/anthology/D13-1139.Google Scholar
- Hieu Hoang, Philipp Koehn, and Adam Lopez. 2009. A unified framework for phrase-based, hierarchical, and syntax-based statistical machine translation. In Proceedings of the International Workshop on Spoken Language Translation. 152--159.Google Scholar
- Sho Hoshino, Yusuke Miyao, Katsuhito Sudoh, and Masaaki Nagata. 2013. Two-stage preordering for Japanese-to-English statistical machine translation. In Proceedings of the 6th International Joint Conference on Natural Language Processing. Asian Federation of Natural Language Processing, 1062--1066. http://www.aclweb.org/anthology/I13-1147.Google Scholar
- Rebecca Hwa, Philip Resnik, Amy Weinberg, Clara Cabezas, and Okan Kolak. 2005. Bootstrapping parsers via syntactic projection across parallel texts. Nat. Lang. Eng. 11, 3, 311--325. DOI: http://dx.doi.org/10.1017/S1351324905003840. Google ScholarDigital Library
- Hideki Isozaki, Tsutomu Hirao, Kevin Duh, Katsuhito Sudoh, and Hajime Tsukada. 2010.Automatic evaluation of translation quality for distant language pairs. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. 944--952. Google ScholarDigital Library
- Hideki Isozaki, Katsuhito Sudoh, Hajime Tsukada, and Kevin Duh. 2012. HPSG-based preprocessing for English-to-Japanese translation. ACM Trans. Asian Lang. Inf. Process. 11, 3, Article 8, 16 pages. DOI: http://dx.doi.org/10.1145/2334801.2334802. Google ScholarDigital Library
- Wenbin Jiang, Qun Liu, and Yajuan Lv. 2011. Relaxed cross-lingual projection of constituent syntax. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 1192--1201. http://www.aclweb.org/anthology/D11-1110. Google ScholarDigital Library
- Mark Johnson, Thomas Griffiths, and Sharon Goldwater. 2007. Bayesian inference for PCFGs via Markov Chain Monte Carlo. In Human Language Technologies: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 139--146. http://www.aclweb.org/anthology/N/N07/N07-1018.Google Scholar
- Jason Katz-Brown and Michael Collins. 2008. Syntactic reordering in preprocessing for Japanese → English translation: MIT system description for NTCIR-7 patent translation task. In Proceedings of the NTCIO-7. 409--414.Google Scholar
- Mitesh M. Khapra, Ananthakrishnan Ramanathan, and Karthik Visweswariah. 2013.Improving reordering performance using higher order and structural features. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, 315--324. http://www.aclweb.org/anthology/N13-1032.Google Scholar
- Dan Klein. 2005. The unsupervised learning of natural language structure. Ph.D. Dissertation, Stanford University. Google ScholarDigital Library
- William R. Knight. 1966. A computer method for calculating Kendall’s tau with ungrouped data. J. Amer. Statist. Assoc. 61, 314.DOI: http://dx.doi.org/10.2307/2282833.Google ScholarCross Ref
- Philipp Koehn. 2004. Statistical significance tests for machine translation evaluation. In Proceedings of EMNLP, Dekang Lin and Dekai Wu Eds. Association for Computational Linguistics, 388--395.Google Scholar
- Philipp Koehn, Amittai Axelrod, Alexandra Birch Mayne, Chris Callison-Burch, Miles Osborne, and David Talbot. 2005. Edinburgh system description for the 2005 IWSLT speech translation evaluation. In Proceedings of the International Workshop on Spoken Language Translation.Google Scholar
- Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan Herbst. 2007. Moses: Open source toolkit for statistical machine translation. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics Companion Volume Proceedings of the Demo and Poster Sessions. Association for Computational Linguistics, 177--180. http://www.aclweb.org/anthology/P07-2045. Google ScholarDigital Library
- Shuhei Kondo, Mamoru Komachi, Yuji Matsumoto, Katsuhito Sudoh, Kevin Duh, and Hajime Tsukada. 2011. Learning of linear ordering problems and its application to J-E patent translation in NTCIR-9 PatentMT. In Proceedings of NTCIR-9. 641--645.Google Scholar
- Taku Kudo and Yuji Matsumoto. 2002. Japanese dependency analysis using cascaded chunking. In Proceedings of the 6th Conference on Natural Language Learning (CoNLL’02) (COLING 2002 Post-Conference Workshops). 63--69. Google ScholarDigital Library
- K. Lari and S. J. Young. 1991. Applications of stochastic context-free grammars using the Inside-Outside algorithm. Comput. Speech Lang. 5, 3, 237--257.DOI: http://dx.doi.org/10.1016/0885-2308(91)90009-F.Google ScholarCross Ref
- Uri Lerner and Slav Petrov. 2013. Source-side classifier preordering for machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 513--523. http://www.aclweb.org/anthology/D13-1049.Google Scholar
- Chi-Ho Li, Minghui Li, Dongdong Zhang, Mu Li, Ming Zhou, and Yi Guan. 2007. A probabilistic approach to syntax-based reordering for statistical machine translation. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. Association for Computational Linguistics, 720--727. http://www.aclweb.org/anthology/P07-1091.Google Scholar
- Yusuke Miyao and Junichi Tsujii. 2008. Feature forest models for probabilistic HPSG parsing. Comput. Linguist. 34, 1, 81-88. Google ScholarDigital Library
- Graham Neubig, Taro Watanabe, and Shinsuke Mori. 2012. Inducing a discriminative parser to optimize machine translation reordering. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Association for Computational Linguistics, 843--853. http://www.aclweb.org/anthology/D12-1077. Google ScholarDigital Library
- Franz Josef Och. 2003. Minimum error rate training in statistical machine translation. In Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 160--167. DOI: http://dx.doi.org/10.3115/1075096.1075117. Google ScholarDigital Library
- Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: A method for automatic evaluation of machine translation. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. 311--318. Google ScholarDigital Library
- Slav Petrov, Leon Barrett, Romain Thibaux, and Dan Klein. 2006. Learning accurate, compact, and interpretable tree annotation. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 433--440.DOI: http://dx.doi.org/10.3115/1220175.1220230. Google ScholarDigital Library
- Jim Pitman and Marc Yor. 1997. The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator. Ann. Probab. 25, 2, 855--900.Google ScholarCross Ref
- Ananthakrishnan Ramanathan, Hegde, Jayprasad, Ritesh M. Shah, Pushpak Bhattacharyya, and Sasikumar M. 2008. Simple syntactic and morphological processing can help English-Hindi statistical machine translation. In Proceedings of the 3rd International Joint Conference on Natural Language Processing. 171--180.Google Scholar
- Andreas Stolcke, Jing Zheng, Wen Wang, and Victor Abrash. 2011. SRILM at sixteen: Update and outlook. In Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop.Google Scholar
- Katsuhito Sudoh, Kevin Duh, Hajime Tsukada, Masaaki Nagata, Xianchao Wu, Takuya Matsuzaki, and Jun’ichi Tsujii. 2011a. NTT-UT statistical machine translation in NTCIR-9 PatentMT. In Proceedings of NTCIR-9. 585--592.Google Scholar
- Katsuhito Sudoh, Jun Suzuki, Hajime Tsukada, and Masaaki Nagata. 2013. NTT-NII statistical machine translation for NTCIR-10 PatentMT. In Proceedings of NTCIR-10. 294--300.Google Scholar
- Katsuhito Sudoh, Xianchao Wu, Kevin Duh, Hajime Tsukada, and Masaaki Nagata. 2011b. Post-ordering in statistical machine translation. In Proceedings of the 13th Machine Translation Summit. 316--323.Google Scholar
- Yee Whye Teh. 2006. A Bayesian interpretation of interpolated Kneser-Ney. Technical Report TRA2/06. NUS School of Computing.Google Scholar
- Christoph Tillman. 2004. A unigram orientation model for statistical machine translation. In Proceedings of the HLT-NAACL’04 (Short Papers), Daniel Marcu, Susan Dumais, and Salim Roukos (Eds.), Association for Computational Linguistics, USA, 101--104. Google ScholarDigital Library
- Roy Tromble and Jason Eisner. 2009. Learning linear ordering problems for better translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 1007--1016. http://www.aclweb.org/anthology/D/D09/D09-1105. Google ScholarDigital Library
- Karthik Visweswariah, Jiri Navratil, Jeffrey Sorensen, Vijil Chenthamarakshan, and Nandakishore Kambhatla. 2010. Syntax based reordering with automatically derived rules for improved statistical machine translation. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING’10). Coling 2010 Organizing Committee, 1119--1127. http://www.aclweb.org/anthology/C10-1126. Google ScholarDigital Library
- Karthik Visweswariah, Rajakrishnan Rajkumar, Ankur Gandhe, Ananthakrishnan Ramanathan, and Jiri Navratil. 2011. A word reordering model for improved machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 486--496. http://www.aclweb.org/anthology/D11-1045. Google ScholarDigital Library
- Chao Wang, Michael Collins, and Philipp Koehn. 2007. Chinese syntactic reordering for statistical machine translation. In Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Association for Computational Linguistics, 737--745. http://www.aclweb.org/anthology/D/D07/D07-1077.Google Scholar
- Dekai Wu. 1997. Stochastic inversion transduction grammars and bilingual parsing of parallel corpora. Comput. Linguist. 23, 3, 377--403. Google ScholarDigital Library
- Xianchao Wu, Katsuhito Sudoh, Kevin Duh, Hajime Tsukada, and Masaaki Nagata. 2011a. Extracting preordering rules from chunk-based dependency trees for Japanese-to-English translation. In Proceedings of the 13th Machine Translation Summit. 300--307.Google Scholar
- Xianchao Wu, Katsuhito Sudoh, Kevin Duh, Hajime Tsukada, and Masaaki Nagata. 2011b. Extracting preordering rules from predicate-argument structures. In Proceedings of the 5th International Joint Conference on Natural Language Processing. Asian Federation of Natural Language Processing, 29--37. http://www.aclweb.org/anthology/I11-1004.Google Scholar
- Fei Xia and Michael McCord. 2004. Improving a statistical MT system with automatically learned rewrite patterns. In Proceedings of COLING’04. 508--514. Google ScholarDigital Library
- Peng Xu, Jaeho Kang, Michael Ringgaard, and Franz Och. 2009. Using a dependency parser to improve SMT for subject-object-verb languages. In Human Language Technologies: Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, 245--253. http://www.aclweb.org/anthology/N/N09/N09-1028. Google ScholarDigital Library
- Kenji Yamada and Kevin Knight. 2001. A syntax-based statistical translation model. In Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, 523--530.DOI: http://dx.doi.org/10.3115/1073012.1073079. Google ScholarDigital Library
Index Terms
- Preordering using a Target-Language Parser via Cross-Language Syntactic Projection for Statistical Machine Translation
Recommendations
Post-Ordering by Parsing with ITG for Japanese-English Statistical Machine Translation
Word reordering is a difficult task for translation between languages with widely different word orders, such as Japanese and English. A previously proposed post-ordering method for Japanese-to-English translation first translates a Japanese sentence ...
Syntactic discriminative language model rerankers for statistical machine translation
This article describes a method that successfully exploits syntactic features for n-best translation candidate reranking using perceptrons. We motivate the utility of syntax by demonstrating the superior performance of parsers over n-gram language ...
Incremental syntactic language models for phrase-based translation
HLT '11: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1This paper describes a novel technique for incorporating syntactic knowledge into phrase-based machine translation through incremental syntactic parsing. Bottom-up and top-down parsers typically require a completed string as input. This requirement ...
Comments