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Incorporating Phonological Knowledge into a Computational Model for Language Family Homeland Identification

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Incorporating Phonological Knowledge into a Computational Model for Language Family Homeland Identification Shen, Ziting Several computational models have been proposed which hypothesize the geographical homeland of a language family in a quantitative manner. Aiming at identifying the homeland accurately for the world's language families, especially those that have not been well-studied, we examine and propose modifications to one of these models, the ASJP model. Specifically, we incorporate more phonological information in the linguistic distance measurement. In the original ASJP model, the linguistic distance is calculated through Levenshtein distance. In the modified model, we apply a technique similar to the ALINE algorithm to assign weights to the feature changes in the Levenshtein distance calculation. The weights are chosen based on a priori knowledge about frequencies of types of phonological change. The model will be tested on the Indo-European family in the future, and the results will be compared to current major Indo-European homeland thecries, i.e. the Steppe Theory and the Anatolian Hypothesis.

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