Ethnic distance is a theoretical concept that is prevalent within political science and political economy as a metric in calculating group heterogeneity but has been difficult to apply in terms of making actual empirical measurements. Ethnic distance can be considered in two related ways. The first can be conceived as the relative variation within and between specific ethnic populations in social or geographic space and supervenes on the individual in the costs of identifying ethnic in-group members from out-group members. The most widely used metric in the literature is language which is made more complex in that there are multiple level differentiating linguistic forms and criteria for measurement. I suggest the development of a measure of linguistic distance that uses the Levenshtein algorithm to produce a numeric value of pronunciation distance by calculating the number of changes that is needed to transform one linguistic string into another. As this value is numeric it can be applied to statistical measures measuring linguistic heterogeneity at the population level and is sensitive enough to detect dialectical differences and can be applied to experimental work on the ethnic identification or location of individuals within a particular language community.