acl acl2010 acl2010-51 acl2010-51-reference knowledge-graph by maker-knowledge-mining
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Author: Boxing Chen ; George Foster ; Roland Kuhn
Abstract: This paper proposes new algorithms to compute the sense similarity between two units (words, phrases, rules, etc.) from parallel corpora. The sense similarity scores are computed by using the vector space model. We then apply the algorithms to statistical machine translation by computing the sense similarity between the source and target side of translation rule pairs. Similarity scores are used as additional features of the translation model to improve translation performance. Significant improvements are obtained over a state-of-the-art hierarchical phrase-based machine translation system. 1
S. Bangalore, S. Kanthak, and P. Haffner. 2009. Statistical Machine Translation through Global Lexical Selection and Sentence Reconstruction. In: Goutte et al (ed.), Learning Machine Translation. MIT Press. P. F. Brown, V. J. Della Pietra, S. A. Della Pietra & R. L. Mercer. 1993. The Mathematics of Statistical Machine Translation: Parameter Estimation. Computational Linguistics, 19(2) 263-3 12. J. Bullinaria and J. Levy. 2007. Extracting semantic representations from word co-occurrence statistics: A computational study. Behavior Research Methods, 39 (3), 510–526. M. Carpuat and D. Wu. 2007. Improving Statistical Machine Translation using Word Sense Disambiguation. In: Proceedings of EMNLP, Prague. M. Carpuat. 2009. One Translation per Discourse. In: Proceedings of NAACL HLT Workshop on Semantic Evaluations, Boulder, CO. Y. Chan, H. Ng and D. Chiang. 2007. Word Sense Disambiguation Improves Statistical Machine Translation. In: Proceedings of ACL, Prague. D. Chiang. 2005. A hierarchical phrase-based model for statistical machine translation. In: Proceedings of ACL, pp. 263–270. D. Chiang. 2007. Hierarchical phrase-based translation. Computational Linguistics. 33(2):201–228. D. Chiang, W. Wang and K. Knight. 2009. 11,001 new features for statistical machine translation. In: Proc. NAACL HLT, pp. 218–226. K. W. Church and P. Hanks. 1990. Word association norms, mutual information, and lexicography. Computational Linguistics, 16(1):22–29. W. B. Frakes and R. Baeza-Yates, editors. 1992. Information Retrieval, Data Structure and Algorithms. Prentice Hall. P. Fung. 1998. A statistical view on bilingual lexicon extraction: From parallel corpora to non-parallel corpora. In: Proceedings of AMTA, pp. 1–17. Oct. Langhorne, PA, USA. J. Gimenez and L. Marquez. 2009. Discriminative Phrase Selection for SMT. In: Goutte et al (ed.), Learning Machine Translation. MIT Press. K. Gimpel and N. A. Smith. 2008. Rich Source-Side Context for Statistical Machine Translation. In: Proceedings of WMT, Columbus, OH. Z. Harris. 1954. Distributional 10(23): 146-162. structure. Word, Z. He, Q. Liu, and S. Lin. 2008. Improving Statistical Machine Translation using Lexicalized Rule Selection. In: Proceedings of COLING, Manchester, UK. D. Hindle. 1990. Noun classification from predicateargument structures. In: Proceedings of ACL. pp. 268-275. Pittsburgh, PA. P. Koehn, F. Och, D. Marcu. 2003. Statistical PhraseBased Translation. In: Proceedings of HLTNAACL. pp. 127-133, Edmonton, Canada P. Koehn. 2004. Statistical significance tests for machine translation evaluation. In: Proceedings of EMNLP, pp. 388–395. July, Barcelona, Spain. T. Landauer and S. T. Dumais. 1997. A solution to Plato’s problem: The Latent Semantic Analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review. 104:21 1240. Z. Li, C. Callison-Burch, C. Dyer, J. Ganitkevitch, S. Khudanpur, L. Schwartz, W. Thornton, J. Weese and O. Zaidan, 2009. Joshua: An Open Source Toolkit for Parsing-based Machine Translation. In: Proceedings of the WMT. March. Athens, Greece. D. Lin. 1998. Automatic retrieval and clustering of similar words. In: Proceedings of COLING/ACL98. pp. 768-774. Montreal, Canada. 842 Q. Liu, Z. He, Y. Liu and S. Lin. 2008. Maximum Entropy based Rule Selection Model for Syntax- based Statistical Machine Translation. In: Proceedings of EMNLP, Honolulu, Hawaii. K. Lund, and C. Burgess. dimensional occurrence. semantic Behavior 1996. spaces Research Producing from high- lexical Methods, co- Instru- ments, and Computers, 28 (2), 203–208. A. Mauser, S. Hasan and H. Ney. Statistical Machine Translation tive and Trigger-Based 2009. Extending with Discrimina- Lexicon Models. In: Pro- ceedings of EMNLP, Singapore. F. Och. 2003. Minimum error rate training in statistical machine translation. In: Proceedings of ACL. Sapporo, Japan. S. Pado and M. Lapata. 2007. Dependency-based construction of semantic space models. Computational Linguistics, 33 (2), 161–199. P. Pantel and D. Lin. 2002. Discovering word senses from text. In: Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 613–619. Edmonton, Canada. K. Papineni, S. Roukos, T. Ward, and W. Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of ACL, pp. 311– 318. July. Philadelphia, PA, USA. R. Rapp. 1999. Automatic Identification of Word Translations from Unrelated English and German Corpora. In: Proceedings of ACL, pp. 519–526. June. Maryland. G. Salton and M. J. McGill. 1983. Introduction to Modern Information Retrieval. McGraw-Hill, New York. P. Turney. 2001. Mining the Web for synonyms: PMI-IR versus LSA on TOEFL. In: Proceedings of the Twelfth European Conference on Machine Learning, pp. 491–502, Berlin, Germany. D. Wu and P. Fung. 2009. Semantic Roles for SMT: A Hybrid Two-Pass Model. In: Proceedings of NAACL/HLT, Boulder, CO. D. Yuret and M. A. Yatbaz. 2009. The Noisy Channel Model for Unsupervised Word Sense Disambiguation. In: Computational Linguistics. Vol. 1(1) 1-18. R. Zens and H. Ney. 2004. Improvements in phrasebased statistical machine translation. In: Proceedings of NAACL-HLT. Boston, MA. B. Zhao, S. Vogel, M. Eck, and A. Waibel. 2004. Phrase pair rescoring with term weighting for statistical machine translation. In Proceedings of EMNLP, pp. 206–213. July. Barcelona, Spain. 843