Proceedings of International Conference on Applied Innovation in IT
2018/03/13, Volume 6, Issue 1, pp.85-92
Direct Machine Translation and Formalization Issues of Language Structures and Their Matches by Automated Machine Translation for the Russian-English Language Pair
Abstract: The present paper introduces a formalization language for sentences and text corpora that helps tackle the acute problem of formalizing semantic and structural matches of different language systems by direct machine translation. In the paper, a detailed look is taken at the elements of reference and situation-based analysis of the representations of surface and in-depth semantics of semantic contexts in the sphere of business communication relying on the meaning-text theory for automated formalization of language structures and their matches by machine translation. The study is aimed at working out an algorithm that will enhance the quality of machine translation excluding intermediary natural languages and post-editing of translated texts. A distinguishing feature of the suggested approach is structurization and formalization of language structures on the stage of text pre-processing. Such «input filter» of information will enable decoding system create literate messages in compliance with lexical and grammatical distributive principles both in a foreign language and native language, and use them for proofreading of texts in a native language and building structures that can be further translated by existing machine translation systems with high quality.
Keywords: Machine Translation, Semantic Match, Structural Match, Formalization Of Language Structures, Formalization Language, Distributive Principles, Surface Language Structures, Syntactic Positions, Skeleton Language Structure, In-Depth Model, Pre-Processing Of Text, Referential Text Corpus
- B. Henisz-Dostert, R. R. Macdonald, and M. Zarechnak, Machine translation. The Hague ; New York: Mouton, 1979.
- P. Sojka, Ed., Text, speech and dialogue: 13th international conference, TSD 2010, Brno, Czech Republic, September 6-10, 2010: proceedings. Berlin; New York: Springer, 2010.
- M. Aiken, K. Ghosh, J. Wee, and M. Vanjani, “An Evaluation of the Accuracy of Online Translation Systems,” Commun. IIMA, vol. 09, no. 04, 2009.
- A. Kazemi, A. Toral, A. Way, A. Monadjemi, and M. Nematbakhsh, “Syntax- and semantic-based reordering in hierarchical phrase-based statistical machine translation,” Expert Syst. Appl., vol. 84, pp. 186–199, Oct. 2017.
- J. B. Mariño et al., “N -gram-based Machine Translation,” Comput. Linguist., vol. 32, no. 4, pp. 527–549, Dec. 2006.
- O. Taeckstroem, R. McDonald, and J. Uszkoreit, Proceedings of the 2012 Conference of the North American Chapter Of. Saintoudsburg: Association for Computational Linguistics, 2012.
- R. Moore and C. Quirk, “Faster Beam Search Decoding for Phrasal Statistical Machine Translation.,” Proc. 11th Mach. Transl. Summit Cph., pp. 321–327, 2007.
- A. Bisazza and F. Marcello, “Efficient Solutions for Word Reordering in German-English Phrase-Based Statistical Machine Translation.,” Assoc. Comput. Linguist., pp. 440–451, 2013.
- N. Durrani, H. Schmid, A. Fraser, P. Koehn, and H. Schütze, “The Operation Sequence Model—Combining N-Gram-Based and Phrase-Based Statistical Machine Translation,” Comput. Linguist., vol. 41, no. 2, pp. 185–214, Jun. 2015.
- E. Hasler, A. de Gispert, F. Stahlberg, A. Waite, and B. Byrne, “Source sentence simplification for statistical machine translation,” Comput. Speech Lang., vol. 45, pp. 221–235, Sep. 2017.
- F. J. Och and H. Ney, “Discriminative training and maximum entropy models for statistical machine translation.,” Proc. 40th Annu. Meet. Assoc. Comput. Lin- Guistics ACL, pp. 295–302, 2002.
- Association for Computational Linguistics, P. Isabelle, and Association for Computational Linguistics, Eds., Proceedings of the conference, 40th annual meeting of the Association for Computational Linguistics: Philadelphia, [6 - 13] July 2002, University of Pennsylvania, Philadelphia, Pennsylvania. Hauptbd. ... San Francisco: Morgan Kaufmann, 2002.
- P. N. Astya et al., Proceeding, International Conference on Computing, Communication and Automation (ICCCA 2016): 29-30 April, 2016. 2016.
- A. V. Novikova and L. A. Mylnikov, “Problems of machine translation of business texts from Russian into English,” Autom. Doc. Math. Linguist., vol. 51, no. 3, pp. 159–169, Jun. 2017.
- S. Mazarweh, Fillmore Case Grammar Introduction to the Theory. München: GRIN Verlag GmbH, 2010.