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When accent preservation leads to clash

Published online by Cambridge University Press:  15 September 2017

QUENTIN DABOUIS*
Affiliation:
Université François-Rabelais de Tours, Département d'anglais, 3 Rue des Tanneurs, 37041 Tours CEDEX 1, Francequentin.dabouis@gmail.com
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Abstract

In English, some complex words can display exceptional accent preservation (EAP): they can preserve an accent from their base even when this would violate a general restriction against adjacent accents (e.g. retúrn → retùrnée). This article analyses EAP both empirically and theoretically. The analysis of a set of 291 derivatives from Wells (2008) shows that this phenomenon can be partially attributed to the relative frequency of the base and its derivative and partially also to syllable structure, and that these two factors have a cumulative effect. It is also shown that the existence of a more deeply embedded base (e.g. colléct→ colléctive → còllectívity ~ collèctívity) can increase the likelihood for a derivative to display EAP. A formal account of the phenomenon is proposed building on Collie's (2007, 2008) ‘fake cyclicity’ analysis, using weighted constraints (Pater 2009, 2016) and Max-Ent-OT (Goldwater & Johnson 2003). Finally, a model of lexical access building on Hay's (2001, 2003) model and integrating more deeply embedded bases is proposed.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2017 
Figure 0

Figure 1. Schematized dual-route model from Hay (2001). The solid line represents the decomposed route and the dashed line represents the direct route. Resting activation levels are represented by the thickness of the circles (BNC frequencies: sane (289), insane (360)).

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Figure 2. The x = y line is represented by the dashed line. Hay & Baayen's (2002) parsing line is represented by the solid line.

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Figure 3. Relative log frequencies in Condition A. The solid line represents the regression line for Group 1 and the dashed line represents the regression line for Group 2.

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Table 1. Logistic regression for Condition A

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Figure 4. Relative log frequencies in Condition B. The solid line represents the regression line for Group 1 and the dashed line represents the regression line for Group 2.

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Table 2. Logistic regression for Condition B – relative frequency

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Table 3. Logistic regression for Condition B – absolute frequency

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Table 4. Distribution between Group 1 and Group 2 depending on the existence of a remote base that is more frequent than the local base

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Table 5. Detailed distribution of the data according to the two significant parameters in Condition B

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Table 6. Distribution between Group 1 and Group 2 per suffix

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Figure 5. Proportion of items in Group 1 and above Hay & Baayen's (2002) parsing line per suffix

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Table 7. Constraint weights

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Figure 6. Percentage and number of Group 1 and Group 2 words per derivative/base frequency ratio40

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Figure 7. The four possible routes of lexical access with a remote base