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

Novikova Anna

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

DOI: 10.13142/kt10006.29

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