Latent Geographical Factors for Analyzing the Evolution of Dialects in Contact
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.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Similarities between Arabic Dialects: Investigating Geographical Proximity
The automatic classification of Arabic dialects is an ongoing research challenge, which has been explored in recent work that defines dialects based on increasingly limited geographic areas like cities and provinces. Thi…
Unification of Balti and trans-border sister dialects in the essence of LLMs and AI Technology
The language called Balti belongs to the Sino-Tibetan, specifically the Tibeto-Burman language family. It is understood with variations, across populations in India, China, Pakistan, Nepal, Tibet, Burma, and Bhutan, infl…
DiversityDialetto, ma Quanto Dialetto? Transcribing and Evaluating Dialects on a Continuum
There is increasing interest in looking at dialects in NLP. However, most work to date still treats dialects as discrete categories. For instance, evaluative work in variation-oriented NLP for English often works with In…
Speech-to-TextLearning about Spanish dialects through Twitter
This paper maps the large-scale variation of the Spanish language by employing a corpus based on geographically tagged Twitter messages. Lexical dialects are extracted from an analysis of variants of tens of concepts. Th…
BIG-bench Machine LearningCan Linguistic Distance help Language Classification? Assessing Hawrami-Zaza and Kurmanji-Sorani
To consider Hawrami and Zaza (Zazaki) standalone languages or dialects of a language have been discussed and debated for a while among linguists active in studying Iranian languages. The question of whether those languag…