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Mirzaee, A., Modarresi Ghavami, G. (2024). Quantifying Macro-Rhythm in Persian: Evidence from Tehrani and Kermani Varieties of Persian. Glory of Art (Jelve-y Honar) Alzahra Scientific Quarterly Journal, (), -. doi: 10.22051/jlr.2024.48436.2496
Abedeh Mirzaee; Golnaz Modarresi Ghavami. "Quantifying Macro-Rhythm in Persian: Evidence from Tehrani and Kermani Varieties of Persian". Glory of Art (Jelve-y Honar) Alzahra Scientific Quarterly Journal, , , 2024, -. doi: 10.22051/jlr.2024.48436.2496
Mirzaee, A., Modarresi Ghavami, G. (2024). 'Quantifying Macro-Rhythm in Persian: Evidence from Tehrani and Kermani Varieties of Persian', Glory of Art (Jelve-y Honar) Alzahra Scientific Quarterly Journal, (), pp. -. doi: 10.22051/jlr.2024.48436.2496
Mirzaee, A., Modarresi Ghavami, G. Quantifying Macro-Rhythm in Persian: Evidence from Tehrani and Kermani Varieties of Persian. Glory of Art (Jelve-y Honar) Alzahra Scientific Quarterly Journal, 2024; (): -. doi: 10.22051/jlr.2024.48436.2496

Quantifying Macro-Rhythm in Persian: Evidence from Tehrani and Kermani Varieties of Persian

زبان پژوهی
Articles in Press, Corrected Proof, Available Online from 23 December 2024
Document Type: Research
DOI: 10.22051/jlr.2024.48436.2496
Authors
Abedeh Mirzaee1; Golnaz Modarresi Ghavami* 2
1PhD student at Allame Tabatab'i University
2Allameh Tabataba'i University
Abstract
Previous studies on Persian rhythm and prosodic typology have focused on micro-rhythm. However, micro-rhythm alone cannot explain the perceptible prosodic differences between language varieties such as Tehrani and Kermani varieties of Persian, which are classified under a single typological category, namely pitch-accent languages. In the current study, we have examined the prosodic differences between two Persian varieties, Tehrani and Kermani, using the parameter of macro-rhythm (Jun, 2014). We have quantified macro-rhythm using data from these two Persian varieties and compared their strength. The aim of this research is to introduce a quantitative method for measuring macro-rhythm using Persian language data and classify Tehrani and Kermani varieties based on the strength of macro-rhythm. To achieve this, we analyzed audio samples of speakers from Tehrani and Kermani varieties using Praat software (version 6.2.12) for acoustic analysis. We calculated three quantitative indices of macro-rhythm: nPVI (Normalized Pairwise Variability Index), MacR Variation Index (MacR_Var), and MacR Frequency Index (MacR_Freq). The values of these indices indicate that the macro-rhythm strength of Kermani variety is stronger than that of Tehrani variety, and quantifying macro-rhythm is a reliable method for studying the prosodic typology of languages.
Keywords
Macro-rhythm Speech rhythm; Prosodic typology; Persian language; Tehrani; Kermani
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