Abstract

Dialect classification is a classical problem in traditional dialectology. In the course of the last few decades, several quantitative approaches have been suggested as solutions for this problem, one of which uses “Levenshtein distance” for measuring linguistic distances between dialects. In the present paper we shall introduce the Levenshtein algorithm as well as two methods with which the results of the measuring can be analyzed, viz. multidimensional scaling and clustering. Then we shall apply these methods to the Bulgarian language area and present a quantitative classification of Bulgarian dialects. Finally, we shall compare the classification obtained to the most widely accepted traditional Bulgarian dialect map, analyze the similarities and differences and evaluate our method.

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