A phonological approach to the unsupervised learning of root-and-pattern morphology

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Serval ID
serval:BIB_89D7F2B729B9
Type
A part of a book
Publication sub-type
Chapter: chapter ou part
Collection
Publications
Institution
Title
A phonological approach to the unsupervised learning of root-and-pattern morphology
Title of the book
Shaping Phonology
Author(s)
Xanthos Aris
Publisher
University of Chicago Press
Address of publication
Chicago
ISBN
9780226562452
Publication state
Published
Issued date
08/2018
Peer-reviewed
Oui
Editor
Brentari Diane, Lee Jackson L.
Chapter
14
Pages
309-327
Language
english
Abstract
This contribution describes an algorithm for the unsupervised learning of root-and-pattern morphology. The algorithm relies on a phonological heuristic to bootstrap the morphological analysis and identify a preliminary set of reliable roots and patterns. The analysis is then incrementally extended based on the minimum description length principle, in line with the approach to morphological learning embodied in John Goldsmith's Linguistica algorithm. The algorithm is implemented as a computer program named Arabica and evaluated with regard to its ability to learn the system of Arabic noun plurals. The tension between the universality of the consonant–vowel distinction and the specificity of root-and-pattern morphology turns out to be crucial for understanding the strengths and weaknesses of this approach.
Create date
13/11/2017 11:05
Last modification date
20/08/2019 15:48
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