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Korean n-insertion: a mismatch between data and learning*

Published online by Cambridge University Press:  15 February 2016

Jongho Jun*
Affiliation:
Seoul National University
*
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Abstract

This paper explores the variable application of n-insertion in Korean. Several tendencies emerge from the distribution of n-insertion in existing Korean words, using data drawn from a dictionary and from surveys and experimental studies. Most, but not all, of these tendencies are mirrored in the results of experiments involving novel words, suggesting that Korean speakers are aware of the differential influence of certain phonological factors on the probability of the application of n-insertion. The observed patterns of variation are analysed within the framework of a probabilistic version of Optimality Theory. In addition, the paper shows that the main aspects of n-insertion are motivated by the requirement of perceptually minimal modification, employing an analysis based on Steriade's P-map theory. The observed data vs. learning mismatch is also attributed to the lack of a perceptual basis for the tendency in question.

Information

Type
Articles
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - SA
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © Cambridge University Press 2016
Figure 0

Table I Results of Hwang's (2008) experiment with novel words, giving rate of insertion as a percentage of the number of inserted outputs divided by the total number of outputs. The total number in each cell varies because outputs were excluded from the analysis when the listeners’ perceptual judgements failed to reach a certain level of consensus on the occurrence of n-insertion (see Hwang 2008 on the details of the judgement process.)

Figure 1

Table II Insertion rate (%) in Hwang's (2008) experiment, by C1 type (son=sonorant except /ŋ/, obs=obstruent).

Figure 2

Table III Distribution of n-insertion (%) in the SKD, by morphological complexity. The number of words in each category is also shown. Variable forms are those which are listed in the dictionary both with and without insertion.

Figure 3

Table IV Distribution of n-insertion (%) in the SKD in multimorphemic words, by M2-initial vocoid type.

Figure 4

Table V Insertion rate (%) in the SKD in multimorphemic words, by C1 and M2-initial vocoid type.

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Table VI Numbers of subjects and test words employed in previous surveys and experimental studies. The total number of words is 268, rather than 298, because some words were used in more than one study. All the overlapping words appear in Kook et al. (2005).

Figure 6

Table VII Response frequencies for some of the test words employed by Choi (2002) and Kim (2003).

Figure 7

Table VIII Insertion rate (%) in previous studies, by M2-initial vocoid type. The number of words in each category is also shown.

Figure 8

Table IX Insertion rate (%) in previous studies, by C1 and M2-initial vocoid types.

Figure 9

Table X Logistic regression results for data from previous studies: coefficients. Significance is indicated by * (p<0·05), ** (p<0·01) and *** (p<0·001).

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Table XI Insertion rate (%) in the current survey of existing Korean words, by C1 type.

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Table XII Mixed effects logistic regression results in the current survey of existing Korean words (fixed effects).

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Table XIII Insertion rate (%) in the current survey of existing Korean words, by M2 initial vocoid sequence.

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Table XIV Insertion rate (%) in the current survey of existing Korean words, by M1 length.

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Table XV Possible variant forms and constraints violated.

Figure 15

Table XVI Mean durations (in ms) and standard deviations (in parentheses) of nasals in Korean (from Hwang 2002). C=lenis stop.

Figure 16

Table XVII Training data for Korean n-insertion.

Figure 17

Table XVIII Constraint weights returned by the learner.

Figure 18

Table XIX Insertion rates (%) in the learning simulation: comparison of the survey data (observed) with the maxent model (learned).

Figure 19

Table XX Insertion rate (%) in the wug test, by C1 type.

Figure 20

Table XXI Mixed effects logistic regression results for the wug test.

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Table XXII Insertion rate (%) in the wug test, by M2 initial vocoid sequence (n/a indicates that an item was not available).

Figure 22

Table XXIII Insertion rate (%) in the wug test, by C1 and M2-initial vocoid types.