Intonational Features of Spontaneous Narrations in Monolingual and Heritage Russian in the U.S.—An Exploration of the Rueg Corpus

Bibliographic Data

ID7903848
AuthorsSabine Zerbian (0000-0002-4631-369X, University of Stuttgart, corresponding author), Yulia Zuban (0009-0009-3033-1760, University of Stuttgart), Maren Klotz (0000-0002-8078-4516, Humboldt-Universität zu Berlin)
Year2023
Volume9
Issue1
Pages2
Publication date2023-12-19
Open AccessYes
TypeARTICLE
VenueLanguages (JOURNAL)
Journal identifiersISSN: 2226-471X • E-ISSN: 2226-471X
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/languages9010002
OpenAlexW4389979941
LanguageEN
Citations received1
References cited35

This article presents RuPro, a new corpus resource of prosodically annotated speech by Russian heritage speakers in the U.S. and monolingually raised Russian speakers. The corpus contains data elicited in formal and informal communicative situations, by male/female and adolescent/adult speakers. The resource is presented with its architecture and annotation, and it is shown how it is used for the analysis of intonational features of spontaneous mono- and bilingual Russian speech. The analyses investigate the length of intonation phrases, types and number of pitch accents, and boundary tones. It emerges that the speaker groups do not differ in the inventory of pitch accents and boundary tones or in the relative frequency of these tonal events. However, they do differ in the length of intonation phrases (IPs), with heritage speakers showing shorter IPs also in the informal communicative situation. Both groups also differ concerning the number of pitch accents used on content words, with heritage speakers using more pitch accents than monolingually raised speakers. The results are discussed with respect to register differentiation and differences in prosodic density across both speaker groups

Annotation · Heritage language · Linguistics · Computer Science · Linguistic Variation and Morphology · Natural Language Processing Techniques · Phonetics and Phonology Research · Psychology · Artificial Intelligence

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