Reference

Gubian, M., Cronenberg, J., Harrington, J. (2023). Phonetic and Phonological Sound Changes in an Agent-Based Model. Speech Communication, 147, 93-115.

BibTeX

@article{gubianPhoneticPhonologicalSound2023,
  title = {Phonetic and {{Phonological Sound Changes}} in an {{Agent-Based Model}}},
  author = {Gubian, Michele and Cronenberg, Johanna and Harrington, Jonathan},
  year = {2023},
  journal = {Speech Communication},
  volume = {147},
  pages = {93--115},
  doi = {10.1016/j.specom.2023.01.004},
  abstract = {The focus of the study is an agent-based model (ABM) concerned with simulating phonological~stability and change using real speech data from a population of speakers. At the core of the model~was a flexible and agent-specific association between acoustic exemplars and phonological~ categories.~This was achieved by means of two general-purpose~unsupervised machine learning algorithms: the~first grouped exemplars into acoustic clusters, the second identified sets of clusters which largely~contain exemplars of the same word classes. The model was tested first on data from Standard~Southern British English, where a shift of /u/ to the front of the vowel space was expected not to~cause any phonological re-categorisation. The simulation indeed showed phonological stability despite~the phonetic change. Using the same settings, the ABM was then applied to data from New Zealand~English in which a merger of /eə, ɪə/ diphthongs has taken place in the last 50 years. Compatibly~with that, the simulation showed a shift from /eə/ towards /ɪə/ along with the neutralisation of the~diphthong contrast. The results are discussed with respect to the conditions necessary to model a~merger, taking into account both findings on marginal~phonological relationships and principles from~exemplar theory.},
  keywords = {Agent-Based Modelling,Gaussian Mixture Models,New Zealand English,Non-Negative Matrix Factorisation,Sound Change}
}