Article published In: Language and Linguistics
Vol. 26:4 (2025) ► pp.595–621
Automatic detection of phonological change in Chinese rhymed corpora
Available under the Creative Commons Attribution (CC BY) 4.0 license.
For any use beyond this license, please contact the publisher at rights@benjamins.nl.
Published online: 28 July 2025
https://doi.org/10.1075/lali.00246.bal
https://doi.org/10.1075/lali.00246.bal
Abstract
Large annotated corpora of Chinese rhymed poetry have recently become available, in part due to the development of
automatic annotation techniques, such as Baley, Julien. 2022. Leveraging
graph algorithms to speed up the annotation of large rhymed corpora. Cahiers de Linguistique –
Asie
Orientale 51(1). 46–80. . The availability of such
annotated corpora makes possible the computer-assisted analysis of rhyming practices from a diachronic point of view. This paper
proposes to couple such annotated rhymed corpora with the Harvard University & Academia Sinica & Peking
University. 2021. China Biographical Database. ([URL]) (Accessed 2025-05-07.) to assign individual poems to different time periods and, re-using the concept of rhyme communities, to apply
community evolution algorithms in order to follow the changes in the composition of rhyme communities. In the process, I
demonstrate that it is possible to highlight rhyme splits and mergers and date those changes. This further allows us to look at
sequences of mergers and establish the corresponding chronology of the phonological changes. The code is published so that the
approach can be replicated for other periods of the Chinese corpus and adapted to other languages.
Article outline
- 1.Introduction
- 2.Evolving rhyming practices as community change
- 3.Community change detection algorithm
- 4.Concrete process
- 4.1Corpus segmentation
- 4.2Sub-corpus rhyme communities
- 4.3Applying the rhyme community change detection algorithm
- 5.Case study
- 6.Discovering all splits & mergers
- 6.1Noise and remedies
- 7.Conclusion
- Notes
- List of abbreviations
References
References (17)
Baley, Julien. 2022. Leveraging
graph algorithms to speed up the annotation of large rhymed corpora. Cahiers de Linguistique –
Asie
Orientale 51(1). 46–80.
. 2023. Evaluating
rhyme annotations for large corpora: Metrics and data. Cahiers de Linguistique – Asie
Orientale 52(2). 137–162.
Baxter, William H. & Sagart, Laurent. 2014. Old
Chinese: A new reconstruction. Oxford: Oxford University Press.
Fairbank Center for Chinese Studies, Harvard University & Center for Historical
Geographical Studies, Fudan University. 2016. China Historical Geographic
Information System (CHGIS), version 6. ([URL]) (Accessed 2025-03-31.) (Data set.)
Harvard University & Academia Sinica & Peking
University. 2021. China Biographical Database. ([URL]) (Accessed 2025-05-07.)
List, Johann-Mattis. 2016. Using
network models to analyze Old Chinese rhyme data. Bulletin of Chinese
Linguistics 9(2). 218–241.
Liu, Xiaonan. 1998. Several
characteristics of the Min dialects in the 10th–13th centuries reflected in Fujian poets’ use of rime in the Song
Dynasty. Yuyan
Yanjiu 1998(1). 155–171.
Liu, Xiaonan & Luo, Xuemei. 2004. Sichuan
poets’ rhythmic style and several issues in Tongyu variations in the Song Dynasty. Sichuan
Daxue Xuebao (Zhexue Shehui Kexue
Ban) 2004(6). 79–88.
Pulleyblank, Edwin G. 1984. Middle Chinese: A study in historical
phonology. Vancouver: University of British Columbia (UBC) Press.
1991. Lexicon of reconstructed pronunciation:
In Early Middle Chinese, Late Middle Chinese, and Early
Mandarin. Vancouver: University of British Columbia (UBC) Press.
Rossetti, Giulio & Pappalardo, Luca & Pedreschi, Dino & Giannotti, Fosca. 2017. Tiles:
An online algorithm for community discovery in dynamic social networks. Machine
Learning 106(8). 1213–1241.
Takaffoli, Mansoureh & Sangi, Farzad & Fagnan, Justin & Zaïane, Osmar R. 2011. MODEC — Modeling and
detecting evolutions of communities. Proceedings of the International AAAI Conference on Web
and Social
Media 5(1). 626–629.
Takaffoli, Mansoureh & Rabbany, Reihaneh & Zaïane, Osmar R. 2014. Community evolution
prediction in dynamic social networks. In Wu, Xindong & Ester, Martin & Xu, Guandong (eds.), Proceedings
of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM
2014), 9–16. Piscataway: IEEE.
