2023
EACL
EACL 2023
A Measure for Linguistic Coherence in Spatial Language Variation
Abstract
AbstractBased on historical dialect data we introduce a local measure of linguistic coherence in spatial language variation aiming at the identification of regions which are particularly sensitive to language variation and change. Besides, we use a measure of global coherence for the automated detection of linguistic items (e.g., sounds or morphemes) with higher or lesser language variation. The paper describes both the data and the method and provides analyses examples.
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Keyword Pioneer
— spatial linguistics
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Speech & Audio