25.3621, Diss: Phonology, Typology: Moran: 'Phonetics Information Base and Lexicon'

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LINGUIST List: Vol-25-3621. Mon Sep 15 2014. ISSN: 1069 - 4875.

Subject: 25.3621, Diss: Phonology, Typology: Moran: 'Phonetics Information Base and Lexicon'

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Date: Mon, 15 Sep 2014 21:34:39
From: Steven Moran [steven.moran at uzh.ch]
Subject: Phonetics Information Base and Lexicon

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Institution: University of Washington 
Program: Department of Linguistics 
Dissertation Status: Completed 
Degree Date: 2012 

Author: Steven Moran

Dissertation Title: Phonetics Information Base and Lexicon 

Dissertation URL:  https://digital.lib.washington.edu/researchworks/handle/1773/22452

Linguistic Field(s): Phonology
                     Typology


Dissertation Director(s):
Emily Menon Bender
Scott O. Farrar
Sharon L. Hargus
Richard A. Wright

Dissertation Abstract:

In this dissertation, I investigate the linguistic and technological
challenges involved in creating a cross-linguistic data set to undertake
phonological typology. I then address the question of whether more
sophisticated, knowledge-based approaches to data modeling, coupled with a
broad cross-linguistic data set, can extend previous typological observations
and provide new ways of querying segment inventories. The model that I
implement facilitates testing typological observations by aligning data models
to questions that typologists wish to ask. The technological infrastructure
that I create is conducive to data sharing, extensibility and reproducibility
of results. I use the data set and data models in this work to validate and
extend previous typological observations. 
In doing so, I revisit the typological facts proposed in the linguistics
literature about the size, shape and composition of segment inventories in the
world's languages and find that they remain similar even with a much larger
sample of languages. I also show that as the number of segment inventories
increases, the number of distinct segments also continues to increase. And
when vowel systems grow beyond the basic cardinal vowels, they do so first by
length and nasalization, and then diphthongization.
Moving beyond segments, I show that distinctive feature sets in general lack
the typological representation needed to straightforwardly map sets of
features to the segment types found in a broad set of language descriptions.
Therefore, I extend a distinctive feature set, devise a method to
computationally encode features by combining feature vectors and assigning
them to segment types, and create a system in which users can query by
feature, by sets of features that define natural classes, or by omitting
features in queries to utilize the underspecification of segments. I use this
system and reinvestigate proposed descriptive universals about phonological
systems and find that some, but not all universals hold up to the more
rigorous testing made possible with this larger data set and a graph data
model.
Lastly, I reevaluate one of the many purported correlations between a
non-linguistic factor and language: the claim that there exists a relationship
between population size and phoneme inventory size. I show that this finding
is actually an artifact of a small data set, which constrains the use of more
nuanced statistical approaches that can control for the genealogical
relatedness of languages. Thus, in this work I illustrate how researchers can
leverage the data set and data models that I have implemented to investigate
different aspects of languages' phonological systems, including the possible
impact of non-linguistic factors on phonology.







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