Year: 2020
Type: conference-paper
Abstract: Analyzing the evolution of dialects remains a challenging problem because contact phenomena hinder the application of the standard tree model.Previous statistical approaches to this problem resort to admixture analysis, where each dialect is seen as a mixture of latent ancestral populations.However, such ancestral populations are hardly interpretable in the context of the tree model.In this paper, we propose a probabilistic generative model that represents latent factors as geographical distributions.We argue that the proposed model has higher affinity with the tree model because a tree can alternatively be represented as a set of geographical distributions.Experiments involving synthetic and real data suggest that the proposed method is both quantitatively and qualitatively superior to the admixture model.
Author: Yugo Murawaki
Institution: Kyoto University
Language: English
Subfield: Cultural Studies
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W3100464155