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khatami H, fadaei H, faili H. A Hybrid Machine Translation System Based on a Monotone Decoder. JSDP 2019; 16 (2) :77-90
URL: http://jsdp.rcisp.ac.ir/article-1-662-en.html
A Hybrid Machine Translation System Based on a Monotone Decoder
Hosein Khatami * , Hakime Fadaei , Hesham Faili
Abstract:   (3626 Views)

In this paper, a hybrid Machine Translation (MT) system is proposed by combining the result of a rule-based machine translation (RBMT) system with a statistical approach. The RBMT uses a set of linguistic rules for translation, which leads to better translation results in terms of word ordering and syntactic structure. On the other hand, SMT works better in lexical choice. Therefore, in our system, an initial translation is generated using RBMT. Then the proper lexical for the resulted sentence is chosen by using a decoder algorithm which is inspired by SMT architecture.
In the pure SMT approach, decoder is responsible for selecting proper final lexical during the translation procedure. Normally this method deals with lexical choice as well as reordering and required exponential order in time complexity. By fixing the word order in the output, a polynomial version of this method, named monotone decoding, is used in this paper. Monotone decoder algorithm selects the best lexical from a candidate list by maximizing the language model of resulted sentence. The candidate list is gathered from the outputs of both pure RBMT and pure SMT systems. 
The experiments of proposed hybrid method on English-Persian language pair show significant improvements over both RBMT and SMT results. The results show that the proposed hybrid method gains an improvement of almost +5 units over RBMT and about one unit over SMT in BLEU score.
 

Keywords: Machine translation, hybrid architecture, monotone decoder, translation reordering, lexical choice
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Type of Study: Research | Subject: Paper
Received: 2017/04/15 | Accepted: 2019/07/10 | Published: 2019/09/17 | ePublished: 2019/09/17
References
1. [1]A. Antonova and A. Misyurev, "Improving the precision of automatically constructed human-oriented translation dictionaries", in Proceedings of the 3rd Workshop on Hybrid Approaches to Translation (HyTra)@ EACL, 2014, pp. 58-66. [DOI:10.3115/v1/W14-1010]
2. [2]H. Béchara, R. Rubino, Y. He, Y. Ma, and J. van Genabith, "An Evaluation of Statistical Post-Editing Systems Applied to RBMT and SMT Systems.," in COLING, 2012, vol. 21, pp. 5-230.
3. [3]A. Birch and M. Osborne, "LRscore for evaluating lexical and reordering quality in MT," in Proceedings of the Joint Fifth Workshop on Stati-stical Machine Translation and MetricsMATR, 2010, pp. 327-332.
4. [4]Y. Chen and A. Eisele, "Hierarchical hybrid translation between english and german," in Proceedings of the 14th Annual Conference of the European Association for Machine Translation, 2010, pp. 90-97.
5. [5]M. R. Costa-Jussa, M. Farrús, J. B. Marino, and J. A. R. Fonollosa, "Study and Comparison of Rule-Based and Statistical Catalan-Spanish Machine Translation Systems.," Comput. informatics, vol. 31, no. 2, pp. 245-270, 2012.
6. [6]G. Doddington, "Automatic evaluation of machine translation quality using n-gram co-occurrence statistics," in Proceedings of the second international conference on Human Language Technology Research, 2002, pp. 138-145. [DOI:10.3115/1289189.1289273]
7. [7]A. Eisele, C. Federmann, H. Uszkoreit, H. Saint-Amand, M. Kay, M. Jellinghaus, S. Hunsicker, T. Herrmann, and Y. Chen, "Hybrid Architectures for Multi-Engine Machine Translation," Proc. Transl. Comput. 30. ASLIB Transl. Comput. Conf. (TATC), 30th, Novemb. 27-28, London, United Kingdom, 2008.
8. [8]C. España Bonet, L. Màrquez Villodre, G. Labaka, A. de Ilarraza Sánchez, and K. Sarasola Gabiola, "Hybrid machine translation guided by a rule-based system," in Machine translation summit XIII: proceedings of the 13th machine translation summit, September 19-23, 2011, Xiamen, China, 2011, pp. 554-561.
9. [9]S. FattanehJabbari and S. M. M. Ziabary, "Developing an open-domain English-Farsi translation system using AFEC: Amirkabir bilingual Farsi-English corpus," in The Fourth Workshop on Computational Approaches to Arabic Script-based Languages, 2012, pp. 17.
10. [10] N. Habash, B. Dorr, and C. Monz, "Symbolic-to-statistical hybridization: extending generation-heavy machine translation," Mach. Transl., vol. 23, no. 1, pp. 23-63, 2009. [DOI:10.1007/s10590-009-9056-7]
11. [11] P. Koehn, "Statistical Significance Tests for Machine Translation Evaluation," in EMNLP, 2004, pp. 388-395.
12. [12] P. Koehn, H. Hoang, A. Birch, C. Callison-Burch, M. Federico, N. Bertoldi, B. Cowan, W. Shen, C. Moran, R. Zens, and others, "Moses: Open source toolkit for statistical machine translation," in Proceedings of the 45th annual meeting of the ACL on interactive poster and demonstration sessions, 2007, pp. 177-180.
13. [13] G. Labaka, C. España-Bonet, L. Màrquez, and K. Sarasola, "A hybrid machine translation architecture guided by syntax," Mach. Transl., vol. 28, no. 2, pp. 91-125, 2014. [DOI:10.1007/s10590-014-9153-0]
14. [14] W. Macherey and F. J. Och, "Consensus translations from multiple machine translation systems." Google Patents, 2012.
15. [15] K. Papineni, S. Roukos, T. Ward, and W.-J. Zhu, "BLEU: a method for automatic evaluation of machine translation," in Proceedings of the 40th annual meeting on association for computational linguistics, 2002, pp. 311-318. [DOI:10.3115/1073083.1073135]
16. [16] E. Park, O. Kwon, K. Kim, and Y. Kim, "A Classification-based Approach for Hybridizing Statistical Machine Translation and Rule-based Machine Translation," pp. 1-9, 2015. [DOI:10.4218/etrij.15.0114.1017]
17. [17] V. M. Sánchez-Cartagena, F. Sánchez-Mart'inez, J. A. Pérez-Ortiz, and others, "Integrating shallow-transfer rules into phrase-based statistical machine translation," 2011.
18. [18] C. Tillmann, S. Vogel, H. Ney, and A. Zubiaga, "A DP based search using monotone alignments in statistical translation," in Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics, 1997, pp. 289-296. [DOI:10.3115/979617.979654]
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