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JOURNALS // Informatika i Ee Primeneniya [Informatics and its Applications] // Archive

Inform. Primen., 2020 Volume 14, Issue 2, Pages 119–126 (Mi ia671)

This article is cited in 1 paper

Reducing the spectrum of translation models in supracorpora databases

V. A. Nuriev, I. M. Zatsman

Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation

Abstract: The paper describes an approach aimed at reducing the spectrum of translation models that are registered in supracorpora databases (SDB). This approach may be applied to both professional (made by the human) and machine translation. As of today, one can use the information resources of the SDB to research the problems of interest to computing, computer linguistics and linguistic theory. Here, the focus is on examining if and how the SDB can be used in translation practice — for reducing the spectrum of translation models. Very often while translating, a translator finds himself/herself in a multiple-choice situation: due to the synonymic potential, characteristic of natural languages, in translation instead of the only possible solution, there is a set of relatively interchangeable equivalents, i. e., “fan of alternatives.” Choosing from a (sometimes wide) range of variants, a translator, in order to narrow the choice, relies on some specific characteristics of the source text. Hence, the goal of the paper is to describe the approach that would allow one to use the SDB for narrowing the choice set of relevant translation models.

Keywords: parallel texts, translation, translation models, supracorpora database, multiple choice.

Received: 13.04.2020

DOI: 10.14357/19922264200217



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