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 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 approachDrawing 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.…
Author details: | Jason A. Shaw, Adamantios I. GafosORCiDGND |
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DOI: | https://doi.org/10.1371/journal.pone.0124714 |
ISSN: | 1932-6203 |
Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/25996153 |
Title of parent work (English): | PLoS one |
Publisher: | PLoS |
Place of publishing: | San Fransisco |
Publication type: | Article |
Language: | English |
Year of first publication: | 2015 |
Publication year: | 2015 |
Release date: | 2017/03/27 |
Volume: | 10 |
Issue: | 5 |
Number of pages: | 36 |
Funding institution: | European Research Council, ERC [STIMOS 249440]; Australian Research Council, ARC [DECRA DE120101289]; National Science Foundation, NSF [0922437] |
Organizational units: | Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Linguistik |
Peer review: | Referiert |
Publishing method: | Open Access |
Institution name at the time of the publication: | Humanwissenschaftliche Fakultät / Institut für Linguistik / Allgemeine Sprachwissenschaft |
External remark: | Zweitveröffentlichung in der Schriftenreihe Postprints der Universität Potsdam : Humanwissenschaftliche Reihe ; 514 |