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Dialect Recognition via Lexical Processing

Is It a Viable Litmus Test

Bibliographic Data

ID5900231
AuthorsTekabe Legesse Feleke (0000-0002-5627-2043, UiT The Arctic University of Norway, corresponding author)
Year2024
Volume9
Issue6
Pages186
Publication date2024-05-21
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueLanguages (JOURNAL)
Journal identifiersISSN: 2226-471X • E-ISSN: 2226-471X
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/languages9060186
OpenAlexW4398171045
LanguageEN
Citations received1
References cited83

For decades, linguists have been working to formulate an objective means of distinguishing dialects from languages, but dialect recognition has largely remained a subjective enterprise. Only recently have some studies proposed a processing-based psycholinguistic approach toward dialect recognition. These studies argued that dialect words are stored as a co-dependent representation, not as an independent representation of the words of bilingual speakers. Based on these studies, we investigated the lexical selection and processing mechanisms of bilingual and bidialectal speakers of two understudied languages, Oromo and Amharic, using the picture-word interference paradigm. We found independent lexical representations for both the bilingual and the bidialectal groups, which implies the involvement of the same cognitive mechanisms in both language and dialect processing. Thus, we argue that bidialectal speakers have flexible lexical representation and selection mechanisms that are dependent on the speakers' previous language experience. Here, we propose a dynamic lexical selection model that accommodates diverse dialect ecologies

Biology · Linguistics · Litmus · Natural language processing · Test (biology · Computer Science · Natural Language Processing Techniques · Neurobiology of Language and Bilingualism · Philosophy · Phonetics and Phonology Research · Psychology

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Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

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