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Stochastic Time Models of Syllable Structure
Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography an...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440707/ https://www.ncbi.nlm.nih.gov/pubmed/25996153 http://dx.doi.org/10.1371/journal.pone.0124714 |
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author | Shaw, Jason A. Gafos, Adamantios I. |
author_facet | Shaw, Jason A. Gafos, Adamantios I. |
author_sort | Shaw, Jason A. |
collection | PubMed |
description | Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. |
format | Online Article Text |
id | pubmed-4440707 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44407072015-05-29 Stochastic Time Models of Syllable Structure Shaw, Jason A. Gafos, Adamantios I. PLoS One Research Article Drawing on phonology research within the generative linguistics tradition, stochastic methods, and notions from complex systems, we develop a modelling paradigm linking phonological structure, expressed in terms of syllables, to speech movement data acquired with 3D electromagnetic articulography and X-ray microbeam methods. The essential variable in the models is syllable structure. When mapped to discrete coordination topologies, syllabic organization imposes systematic patterns of variability on the temporal dynamics of speech articulation. We simulated these dynamics under different syllabic parses and evaluated simulations against experimental data from Arabic and English, two languages claimed to parse similar strings of segments into different syllabic structures. Model simulations replicated several key experimental results, including the fallibility of past phonetic heuristics for syllable structure, and exposed the range of conditions under which such heuristics remain valid. More importantly, the modelling approach consistently diagnosed syllable structure proving resilient to multiple sources of variability in experimental data including measurement variability, speaker variability, and contextual variability. Prospects for extensions of our modelling paradigm to acoustic data are also discussed. Public Library of Science 2015-05-21 /pmc/articles/PMC4440707/ /pubmed/25996153 http://dx.doi.org/10.1371/journal.pone.0124714 Text en © 2015 Shaw, Gafos http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Shaw, Jason A. Gafos, Adamantios I. Stochastic Time Models of Syllable Structure |
title | Stochastic Time Models of Syllable Structure |
title_full | Stochastic Time Models of Syllable Structure |
title_fullStr | Stochastic Time Models of Syllable Structure |
title_full_unstemmed | Stochastic Time Models of Syllable Structure |
title_short | Stochastic Time Models of Syllable Structure |
title_sort | stochastic time models of syllable structure |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440707/ https://www.ncbi.nlm.nih.gov/pubmed/25996153 http://dx.doi.org/10.1371/journal.pone.0124714 |
work_keys_str_mv | AT shawjasona stochastictimemodelsofsyllablestructure AT gafosadamantiosi stochastictimemodelsofsyllablestructure |