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Intervocalic lenition is not phonological: evidence from Campidanese Sardinian

Published online by Cambridge University Press:  21 February 2022

Jonah Katz*
Affiliation:
West Virginia University
*
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Abstract

This paper develops a model of lenition in Campidanese Sardinian. The model treats lenition (and its inverse, fortition) as a predictable consequence of gradient changes in duration associated with prosodic structure. A more typical approach to lenition processes in Campidanese and other languages is to treat them as changes in phonological features. I show here that a phonetic model operating on the output of phonological computations avoids some of the analytical problems associated with such phonological analyses, unifies the phonetic and phonological description of lenition, and captures the relationship between prosody, lenition and duration. While the detailed simulations here are specific to Campidanese, I suggest that the model is broadly applicable to languages with intervocalic lenition processes such as voicing, spirantisation and tapping.

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Articles
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press
Figure 0

Figure 1 A schematic illustration of the model used to generate lenition and fortition.

Figure 1

Figure 2 A schematic illustration of how the model applies to [k] (in the phrase ‘that dog’) and [b] (in the phrase ‘I want to come’) in phrase-initial and phrase-medial positions.

Figure 2

Table I Simulated duration distributions for singleton obstruents in phrase-medial and phrase-initial position. Units are z-transformed log ms.

Figure 3

Figure 3 Observed and simulated duration distributions for (a) phrase-medial and (b) phrase-initial intervocalic obstruents: unspecified stops (left), voiced stops (centre) and unspecified fricatives (right). Bars show observed frequencies in the corpus; curves show density generated by one run of the model with the sample size of the corpus.

Figure 4

Table II Fitting criterion values to duration distributions, showing the values for /T/ voicing in phrase-medial and phrase-initial positions. Duration units are z-transformed log ms.

Figure 5

Figure 4 Observed and simulated voicing for utterance-medial obstruents. Vertical lines show observed proportions fully voiced in the corpus in phrase-medial and phrase-initial positions. Density curves show proportions of voicing over 10,000 simulations for unspecified stops (left), voiced stops (centre) and unspecified fricatives (right) in both positions.

Figure 6

Figure 5 Observed and simulated burst probabilities for utterance-medial stops. Vertical lines show observed proportions with an audible or visible burst in the corpus in phrase-medial and phrase-initial position. Density curves show proportions over 10,000 simulations for unspecified stops (left) and voiced stops (right) in the respective positions.

Figure 7

Figure 6 Observed and simulated duration distributions for (a) phrase-medial and (b) phrase-initial cluster outputs: geminate stops (left), geminate fricatives (centre) and coalesced voiced stops (right). Bars show observed frequencies in the corpus; curves show density generated by one run of the model with the sample size of the corpus.

Figure 8

Table III Simulated duration distributions for postlexical geminates in phrase-medial and phrase-initial position. Units are z-transformed log ms.

Figure 9

Figure 7 Observed and simulated voicing for phrase-medial and phrase-initial cluster outputs. Vertical lines show observed proportions fully voiced in the corpus in phrase-medial and phrase-initial position. Density curves show proportions of voicing over 10,000 simulations for geminate stops (left), geminate fricatives (centre) and coalesced voiced stops (right) in both positions.

Figure 10

Figure 8 Observed and simulated burst probabilities for phrase-medial and phrase-initial cluster outputs. Vertical lines show observed proportions with an audible or visible burst in phrase-medial (dashed) and phrase-initial (solid) position. Density curves show proportions over 10,000 simulations for geminate stops (left) and coalesced voiced stops (right) in the respective positions.

Figure 11

Figure 9 Observed and simulated burst probabilities for coalesced voiced stops in phrase-medial position, when treated as equivalent to the ‘normal’ voiced stops (left) or voiceless stops (right). Vertical lines show observed proportions with an audible or visible burst in the corpus for ‘normal’ stops and sandhi consonants in phrase-medial position. Density curves show proportions over 10,000 simulations.

Figure 12

Figure 10 Observed and simulated phonetic features for phrase-initial singleton unspecified stops (left, centre) and fricatives (right), treated as geminates. Vertical lines show observed proportions with voicing or burst in the corpus for phrase-medial geminates and their phrase-initial singleton counterparts. Density curves show proportions over 10,000 simulations.

Figure 13

Figure 11 Observed and simulated phonetic features for non-voiced stops, treated as voiced stops (left) or continuants (right). Vertical lines show observed proportions with voicing or burst in the corpus for voiced stops or fricatives respectively and unspecified stops in phrase-medial position. Density curves show proportions over 10,000 simulations.

Figure 14

Figure 12 Observed and simulated minimum intensity for voiceless stops (left), nasals (centre) and vowel-to-vowel transitions (right). Vertical lines show observed mean values in the corpus for phrase-medial and phrase-initial positions. Density curves show mean values over 10,000 simulations with the sample size of the corpus.

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