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Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis. This is largely due to the complexity and nuance involved in studying various dialects. We present a novel approach to extract distinguishing lexical features of dialects by utilizing interpretable dialect classifiers, even in the absence of human experts. We explore both posthoc and intrinsic approaches to interpretability, conduct experiments on Mandarin, Italian, and Low Saxon, and experimentally demonstrate that our method successfully identifies key language-specific lexical features that contribute to dialectal variationsmore » « lessFree, publicly-accessible full text available June 28, 2025
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Xie, Roy ; Ahia, Orevaoghene ; Tsvetkov, Yulia ; Anastasopoulos, Antonios ( , Association for Computational Linguistics)Free, publicly-accessible full text available June 1, 2025