2026-08-15T16:12:02Zhttps://iris.cnr.it/oai/request

oai:iris.cnr.it:20.500.14243/5004212025-03-13T22:51:57Zcom_20.500.14243_22com_20.500.14243_21col_20.500.14243_23ou_ou239

Extracting Tuscan phonetic correspondences from dialect pronunciations automatically Arne Rubehn Simonetta Montemagni and John Nerbonne Rubehn, Arne Montemagni, Simonetta John Nerbonne, And sound correspondence dialectology information theory alignment Tuscan dialects 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. 2024 info:eu-repo/semantics/article https://hdl.handle.net/20.500.14243/500421 10.1163/22105832-bja10034 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85204999014 https://brill.com/view/journals/ldc/14/1/article-p1_1.xml?ebody=abstract/excerpt eng volume:14 issue:1 firstpage:1 lastpage:33 numberofpages:33 journal:LANGUAGE DYNAMICS AND CHANGE (PRINT) info:eu-repo/semantics/openAccess ELETTRONICO license:Creative commons license uri:http://creativecommons.org/licenses/by/4.0/