AUTOMATIC DETECTION OF NATURAL PHONOLOGICAL CLASSES IN RUSSIAN SIGN LANGUAGE

George Moroz (), Antonina Plaskovitskaya () and Pavel Rudnev ()
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George Moroz: National Research University Higher School of Economics
Antonina Plaskovitskaya: National Research University Higher School of Economics
Pavel Rudnev: National Research University Higher School of Economics

HSE Working papers from National Research University Higher School of Economics

Abstract: The present paper applies Multiple Correspondence Analysis to test the validity of an existing theoretical model of the phonological system of Russian Sign Language (RSL). We show that comparing the importance of phonological features using ratio plots and MCA is a promising way of revealing non-binary oppositions in phonological systems of human languages irrespective of modality.

Keywords: phonology; phonological features; sign languages; Multiple Correspondence Analysis; Russian Sign Language (search for similar items in EconPapers)
JEL-codes: Z (search for similar items in EconPapers)
Pages: 24 pages
Date: 2018
New Economics Papers: this item is included in nep-cis
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Published in WP BRP Series: Linguistics / LNG, December 2018, pages 1-24

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Persistent link: https://EconPapers.repec.org/RePEc:hig:wpaper:74/lng/2018

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