Towards Automatic Text Adaptation In Russian

Nikolay Karpov () and Vera Sibirtseva ()
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Nikolay Karpov: National Research University Higher School of Economics
Vera Sibirtseva: National Research University Higher School of Economics

HSE Working papers from National Research University Higher School of Economics

Abstract: This article describes ways of using original texts in the National Russian Corpus and news texts to teach Russian as a foreign language. The two-year work of a scientific group from the Higher School of Economics (from Nizhny Novgorod and Moscow), called CorpLings was analyzed. Special attention was paid to the automatic adaptation of acute news texts, which was the basic principle of the research part of the project. We also describe ways of simplifying syntactical and morphological structures that may seem difficult for students at an elementary level. The stages used for lexical simplification are described in detail, such as the creation of an algorithm to find the most appropriate synonyms based on morphological rules, and an analysis of the statistical model of words’ contextual proximity. This article also addresses the difficulties faced by developers and the final results of our research

Keywords: Russian; electronic textbook; text simplification; contextual proximity; distributional semantic model. (search for similar items in EconPapers)
JEL-codes: Z (search for similar items in EconPapers)
Pages: 18 pages
Date: 2014
New Economics Papers: this item is included in nep-cis
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Published in WP BRP Series: Linguistics / LNG, December 2014, pages 1-18

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Persistent link: https://EconPapers.repec.org/RePEc:hig:wpaper:16/lng/2014

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