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Phrase Table Combination Deficiency Analyses in Pivot-Based SMT

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Natural Language Processing and Information Systems (NLDB 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7934))

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Abstract

As the parallel corpus is not available all the time, pivot language was introduced to solve the parallel corpus sparseness in statistical machine translation. In this paper, we carried out several phrase-based SMT experiments, and analyzed the detailed reasons that caused the decline in translation performance. Experimental results indicated that both covering rate of phrase pairs and translation probability accuracy affect the quality of translation.

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References

  1. de Gispert, A., Marino, J.B.: Catalan-English statistical machine translation without parallel corpus: bridging through Spanish. In: Proceedings of 5th International Conference on Language Resources and Evaluation, pp. 65–68 (2006)

    Google Scholar 

  2. Wu, H., Wang, H.: Pivot Language Approach for Phrase-Based Statistical Machine Translation. In: Proceedings of 45th Annual Meeting of ACL, pp. 856–863 (2007)

    Google Scholar 

  3. Utiyama, M., Isahara, H.: A comparison of pivot methods for phrase-based sta-tistical machine translation. In: Proceedings of HLT, pp. 484–491 (2007)

    Google Scholar 

  4. Cohn, T., Lapata, M.: Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora. In: Proceedings of the 45th ACL, pp. 348–355 (2007)

    Google Scholar 

  5. Paul, M., Sumita, E.: Translation Quality Indicators for Pivot-based Statistical MT. In: Proceedings of 5th IJCNLP, pp. 811–818 (2011)

    Google Scholar 

  6. Koehn, P., Och, F.J., Marcu, D.: Statistical phrase-based translation. In: Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, pp. 127–133 (2003)

    Google Scholar 

  7. Yang, M., Jiang, H., Zhao, T., Li, S.: Construct Trilingual Parallel Corpus on Demand. In: Huo, Q., Ma, B., Chng, E.-S., Li, H. (eds.) ISCSLP 2006. LNCS (LNAI), vol. 4274, pp. 760–767. Springer, Heidelberg (2006)

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© 2013 Springer-Verlag Berlin Heidelberg

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Cui, Y., Zhu, C., Zhu, X., Zhao, T., Zheng, D. (2013). Phrase Table Combination Deficiency Analyses in Pivot-Based SMT. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2013. Lecture Notes in Computer Science, vol 7934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38824-8_37

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  • DOI: https://doi.org/10.1007/978-3-642-38824-8_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38823-1

  • Online ISBN: 978-3-642-38824-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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