Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Linguistic features and sociolinguistic variability in everyday spoken Russian. / Bogdanova-Beglarian, Natalia ; Sherstinova, Tatiana ; Blinova, Olga ; Martynenko, Gregory .
Speech and Computer: 19th International Conference, SPECOM 2017, Hatfield, UK, September 12-16, 2017, Proceedings. Springer Nature, 2017. стр. 503-511 (Lecture Notes in Computer Science; Том 10458).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Linguistic features and sociolinguistic variability in everyday spoken Russian
AU - Bogdanova-Beglarian, Natalia
AU - Sherstinova, Tatiana
AU - Blinova, Olga
AU - Martynenko, Gregory
N1 - Bogdanova-Beglarian, N., Sherstinova, T., Blinova, O., Martynenko, G: Linguistic Features and Sociolinguistic Variability in Everyday Spoken Russian. In: Lecture Notes in Computer Science, vol 10458. Springer, Cham, pp. 503-511.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - русская спонтанная речь
KW - русский язык
KW - социолингвистика
UR - https://link.springer.com/chapter/10.1007/978-3-319-66429-3_50
U2 - 10.1007/978-3-319-66429-3_50
DO - 10.1007/978-3-319-66429-3_50
M3 - Conference contribution
SN - 978-3-319-66428-6
T3 - Lecture Notes in Computer Science
SP - 503
EP - 511
BT - Speech and Computer
PB - Springer Nature
T2 - 19th International Conference on Speech and Computer
Y2 - 11 September 2017 through 15 September 2017
ER -
ID: 71327827