Proceedings of the 2024 4th International Conference on Education, Language and Art (ICELA 2024)

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Experimental Research on Tone of Liuzhou Dialect Based on Big Data Measurement

Authors
Na Chen1, Ziyan Liu1, Hongli Deng1, 2, *, Zhengkai He3, *
1School of Literature and Media, Guangxi Science and Technology Normal University, Laibin, Guangxi, China
2School of Liberal Arts, Jinan University, Guangzhou, Guangdong, China
3Discipline Inspection and Supervision Office of Guangxi Normal, University of Science and Technology, Laibin, Guangxi, China
*Corresponding author. Email: 361389651@qq.com
*Corresponding author. Email: 911795875@qq.com
Corresponding Authors
Hongli Deng, Zhengkai He
Available Online 17 March 2025.
DOI
10.2991/978-2-38476-364-1_44How to use a DOI?
Keywords
Liuzhou Dialect; Data Corpus; Monogram Tone; Polysyllabic tone; Acoustic Model
Abstract

Based on big data measurement, this paper analyzes the acoustic parameters such as fundamental frequency and duration of Liuzhou dialect tones, constructs the acoustic patterns of monosyllabic and polysyllabic tones, and employs the Chinese dialect phoneme sound experimental analysis tool developed by Dr. Xiong Ziyu to analyze the correspondence between ancient and modern tones of Liuzhou dialect. The acoustic patterns of monosyllabic and polysyllabic tones, as well as the correspondence between ancient and modern tones, are visualized in the form of spectrograms. The experimental results indicate that: the pattern of monosyllabic tones is flat for Yin Ping, low-falling for Yang Ping, high-falling for Shang, and rising for Qu. The correspondence between ancient and modern tones is characterized by the division of Ping into Yin and Yang, the allocation of Zhuo Shang to Qu, the lack of division between Yin and Yang in Qu, and the reading of Ru as Yang Ping. The polysyllabic tone linkage patterns are largely consistent, retaining the main characteristics of monosyllabic tones without tonal position changes, only differing in tonal values, which are tonal position variants.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 4th International Conference on Education, Language and Art (ICELA 2024)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
17 March 2025
ISBN
978-2-38476-364-1
ISSN
2352-5398
DOI
10.2991/978-2-38476-364-1_44How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Na Chen
AU  - Ziyan Liu
AU  - Hongli Deng
AU  - Zhengkai He
PY  - 2025
DA  - 2025/03/17
TI  - Experimental Research on Tone of Liuzhou Dialect Based on Big Data Measurement
BT  - Proceedings of the 2024 4th International Conference on Education, Language and Art (ICELA 2024)
PB  - Atlantis Press
SP  - 346
EP  - 357
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-364-1_44
DO  - 10.2991/978-2-38476-364-1_44
ID  - Chen2025
ER  -