The paper reviews the results of the project aimed at describing everyday Russian language and analyzing the special characteristics of its usage by different social groups. The presented study was made on the material of 125,000 words annotated subcorpus of the ORD corpus, which contains speech fragments of 256 people representing different gender, age, professional and status groups. The linguistic features from different linguistic levels, which could be considered as diagnostic for different social groups, have been analyzed. It turned out that in terms of sociolinguistic variability all features under investigation may be divided into three categories: (1) the diagnostic features, which display statistically significant differences between certain social groups; (2) the linguistic features, which could be considered as common for all sociolects and referring to some permanent, universal properties of everyday language; and (3) the potentially diagnostic features, which have shown some quantitative difference between the considered groups, but the extent of this difference does not allow to regard them as statistically significant at the moment. The last group of features is the most extensive and requires additional studies on a larger amount of speech data.
Original languageEnglish
Title of host publicationSpeech and Computer
Subtitle of host publication19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings
PublisherSpringer Nature
Pages503-511
ISBN (Electronic)978-3-319-66429-3
ISBN (Print)978-3-319-66428-6
DOIs
StatePublished - 2017
Event19th International Conference on Speech and Computer - Hatfield, United Kingdom
Duration: 11 Sep 201715 Sep 2017

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Nature
Volume10458
ISSN (Print)0302-9743

Conference

Conference19th International Conference on Speech and Computer
Abbreviated titleSPECOM 2017
Country/TerritoryUnited Kingdom
CityHatfield
Period11/09/1715/09/17

    Scopus subject areas

  • Language and Linguistics

ID: 71327827