Extracting Tuscan phonetic correspondences from dialect pronunciations automatically

We present a novel approach to identifying individual pairs of phonetic correspondences in a dataset of dialect pronunciations. This continues work identifying shibboleths (i.e., characteristic features of a given dialect), a category that has interested dialectology and that dialectometrical research has examined mostly in the form of categorical data or entire phonetic transcriptions. This article reaches into segmental sequences (phonetic transcriptions) to identify individual phonetic correspondences. We follow earlier work in examining how distinctive and how representative a given phonetic correspondence is for a selected group of varieties. We proceed from string alignments, and innovate in characterizing the important notions via information theory. Despite minor problems, the method improves on the generality of competing approaches and can be shown to be useful in detecting characteristic phonetic correspondences in Tuscan varieties. We argue that this facilitates deeper investigation into the relation between aggregating approaches to dialectology and approaches proceeding from features.