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Quantifying Cantonese Influence: A Quantitative Study of Lexical Convergence in Yue Dialects (108110)

Session Information: Language/Linguistics
Session Chair: Jette Hansen Edwards

Monday, 11 May 2026 16:20
Session: Session 4
Room: Room G405 (4F)
Presentation Type: Oral Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

This project addresses a critical gap in Chinese dialectology by providing a comprehensive, quantitative analysis of lexical convergence among Yue dialects. While scholarly consensus acknowledges Cantonese as the dominant prestige variety influencing other Yue dialects, existing evidence relies primarily on scattered discussions and isolated case studies. On the other hand, current macro-level quantitative studies fail to distinguish between contact-induced borrowing and inherited similarities from common proto-Yue ancestry. To resolve this, the research employs an innovative methodology focusing on recent lexical innovations in Cantonese—items prevalent in contemporary usage but absent from historical texts and Standard Chinese.

Utilizing data from 79 Yue dialect sites collected through the Chinese Language Resource Protection Project, the study tracks the prevalence of representative lexical items across Yue subgroups. The analysis reveals distributional patterns in which some innovations achieve near-universal saturation, providing strong quantitative evidence of extensive contact-induced convergence. These findings not only quantify the reach of Cantonese influence but also offer a crucial insight for historical linguistics: the widespread distribution of a lexical item across dialect variants does not necessarily imply shared ancestry, illustrating how intense language contact can simulate patterns typically attributed to a common proto-language.

Authors:
Yik-Po Lai, Hong Kong Metropolitan University, Hong Kong


About the Presenter(s)
Dr. Lai is a Senior Lecturer in the School of Education and Languages at Hong Kong Metropolitan University.

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Posted by James Alexander Gordon

Last updated: 2023-02-23 23:45:00