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Prosodic Disambiguation of Disjunctive Declaratives and Disjunctive Questions in Jordanian Arabic

Published online by Cambridge University Press:  16 June 2025

Mohammad Ali Salah Bani Younes
Affiliation:
Department of English Language and Literature, Faculty of Foreign Languages, Al al-Bayt University, Mafraq, Jordan
Laura Colantoni*
Affiliation:
Department of Spanish and Portuguese, Faculty of Arts & Science, University of Toronto, Ontario, Canada
Muhammad Swaileh A. Alzaidi
Affiliation:
Muhammad Swaileh A. Alzaidi, Department of English Language, College of Language Sciences, King Saud University, Riyadh, Saudi Arabia
*
*Corresponding author. Email: laura.colantoni@utoronto.ca
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Abstract

This study investigates phonological and phonetic details of disjunctive declaratives (ddcls) and alternative questions (altqs) in Arabic. The aim of the phonological and phonetic analyses of these syntactically identical utterances is to find out the cues that are responsible for the disambiguation. Consequently, a production study eliciting ddcls and altqs was run with 20 participants producing 160 utterances (80 ddcls and 80 altqs). Findings reveal that ddcls and altqs are similar in having a global rise-fall contour, but differ in the phonetic implementation of the fall, since minimum F0 values are significantly higher in altqs than in ddcls, suggesting that there is a fall to mid in the former (proposing !H%) and a fall to low in the latter (L%). There are also significant phonological differences in the accentual features between both sentence types, i.e., the conjuncts are always accented in altqs, but they are deaccented in ddcls. The findings are a contribution to the prosody-meaning literature, showing the importance of prosody for syntactic disambiguation. The findings are used to propose a theory for the disambiguation of disjunctive sentences.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of The International Phonetic Association
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Figure 1

Figure 1. An example of a model prediction from Hellmuth (2018: 992), showing the overall contour of altqs in eight Arabic dialects (egca: Egyptian, irba: Iraqi, joka: Jordanian, kwur: Kuwaiti, moca: Moroccan, ombu: Omani, syda: Syrian, and tuns: Tunisian Arabic) over C1 (X), C2 (or), and C3 (Y).

Figure 2

Figure 2. An example of the four tiers used in the analysis of the X or Y constituents: words, glosses, boundary tones, and pitch accents [joaa-ddcl2-m5]. The whole ddcl is raːmi zaːr landan ʔaw r-rjaːdʕ, ‘Rami visited London or Riyadh’. Note: The last tier here is empty for C1 (X, landan), C2 (ʔaw), and C3 (Y, r-rjaːdʕ) in this declarative utterance because they were unaccented. The nuclear pitch accent of the whole utterance fell on the verb zaːr before C1.

Figure 3

Figure 3. The list of IPrA ToBI-like labels used in this paper (adapted from Hellmuth, in preparation) and Bani Younes (2020, p. 42). The shaded columns represent stressed syllables for the list under pitch accents; for the list under boundary tones, they represent last syllables.

Figure 4

Figure 4. Two examples of an altq where the IPrA notations were assigned to pitch accented words on the fourth tier to indicate the presence of a pitch accent. The altq in (a) is ˈraːmi ˈzaːr ˈlandan ʔaw r-rˈjaːdʕ? ‘Did Rami visit London or Riyadh?’, which forms a minimal pair with the ddcl utterance in Figure 2. The altq in (b) is dijiruːħ ʕdʒdʒaːmʕa l-ʔalmaːnijja ʔaw l-ʔʊrdʊnijja? ‘Did he choose to study at the German University or the University of Jordan?’.

Figure 5

Figure 5. (Colour online) SSANOVA of the smoothed and time normalized mean F0 values for the X or Y constituents in all target utterances (N = 160), by sentence type. The three vertical lines represent the three constituents (C1(X), C2 (or), and C3 (Y)). The line on top represents the rise-fall contour of altqs (N = 80) over the X or Y; the one on the bottom shows the rise-fall contour of ddcls (N = 80) over the X or Y. The shaded area around each contour line (the ribbon) shows 95% confidence interval.

Figure 6

Figure 6. Examples of each sentence type as produced by a male participant (M5); (a) altq: raːmi zaːr landan ʔaw r-rjaːdʕ? ‘Did Rami visit London or Riyadh?’; (b) ddcl: raːmi zaːr landan ʔaw r-rjaːdʕ ‘Rami visited London or Riyadh’.

Figure 7

Figure 7. Violin plots containing boxplots showing the difference in the minimum F0 of the last syllables for both sentence types. The boxplots show the median and the interquartile range; the violin plots display datapoint distribution, across all participants.

Figure 8

Table 1. Estimates and statistical results of the linear mixed-effects regression model

Figure 9

Table 2. Percentage and frequency of accented X and Y constituents by utterance type

Figure 10

Figure 8. An example of an accented C1 (X) in a ddcl produced by a female speaker (F2); the sentence reads raːmi zaːr landan ʔaw r-rjaːdʕ, ‘Rami visited London or Riyadh’.

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Table 3. Types and frequency of pitch accents associated with C1 (X) constituent by utterance type

Figure 12

Table 4. Types and frequency of pitch accents associated with C3 (Y) constituent by utterance type

Figure 13

Figure 9. (Colour online) Violin plots containing boxplots showing the difference in maxF0 associated with X or Y constituents in both sentence types. The boxplots show the median and the interquartile range; the violin plots display datapoint distribution across all participants.

Figure 14

Table 5. Estimates and statistical results of the linear mixed-effects regression model for the maxF0 of the first constituent (C1, i.e., X)a in the ‘X or Y’

Figure 15

Table 6. Estimates and statistical results of the linear mixed-effects regression model for the maxF0 of the second constituent (C2, i.e., or) a in the ‘X or Y’

Figure 16

Table 7. Estimates and statistical results of the linear mixed-effects regression model for the maxF0 of the third constituent (C3, i.e., Y)a in the ‘X or Y’

Figure 17

Figure 10. (Colour online) Violin plots containing boxplots showing the difference in minF0 of the X or Y constituents in both sentence types. The boxplots show the median and the interquartile range; the violin plots display datapoint distribution across all participants.

Figure 18

Table 8. Estimates and statistical results of the linear mixed-effects regression model for the minF0 of the first constituent (C1, i.e., X)a in the ‘X or Y’

Figure 19

Table 9. Estimates and statistical results of the linear mixed-effects regression model for the minF0 of the second constituent (C2, i.e., or) a in the ‘X or Y’

Figure 20

Table 10. Estimates and statistical results of the linear mixed-effects regression model for the minF0 of the third constituent (C3, i.e., Y) a in the ‘X or Y’