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Article

Data-Driven Critical Tract Variable Determination for European Portuguese

1
Telecomunications and Informatics (DETI), Department of Electronics, Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal
2
Institute of Phonetics and Speech Processing, Ludwig-Maximilians-Universität München, 80333 München, Germany
3
Max Planck Institute for Biophysical Chemistry, 37077 Göttingen, Germany
*
Author to whom correspondence should be addressed.
This article is an extended version of work presented by the authors at the International Conference on Computational Processing of Portuguese (PROPOR).
Information 2020, 11(10), 491; https://doi.org/10.3390/info11100491
Received: 9 August 2020 / Revised: 15 October 2020 / Accepted: 16 October 2020 / Published: 21 October 2020
(This article belongs to the Special Issue Selected Papers from PROPOR 2020)
Technologies, such as real-time magnetic resonance (RT-MRI), can provide valuable information to evolve our understanding of the static and dynamic aspects of speech by contributing to the determination of which articulators are essential (critical) in producing specific sounds and how (gestures). While a visual analysis and comparison of imaging data or vocal tract profiles can already provide relevant findings, the sheer amount of available data demands and can strongly profit from unsupervised data-driven approaches. Recent work, in this regard, has asserted the possibility of determining critical articulators from RT-MRI data by considering a representation of vocal tract configurations based on landmarks placed on the tongue, lips, and velum, yielding meaningful results for European Portuguese (EP). Advancing this previous work to obtain a characterization of EP sounds grounded on Articulatory Phonology, important to explore critical gestures and advance, for example, articulatory speech synthesis, entails the consideration of a novel set of tract variables. To this end, this article explores critical variable determination considering a vocal tract representation aligned with Articulatory Phonology and the Task Dynamics framework. The overall results, obtained considering data for three EP speakers, show the applicability of this approach and are consistent with existing descriptions of EP sounds. View Full-Text
Keywords: critical articulator; critical tract variable; speech production model; data-driven approach; real-time magnetic resonance critical articulator; critical tract variable; speech production model; data-driven approach; real-time magnetic resonance
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MDPI and ACS Style

Silva, S.; Almeida, N.; Cunha, C.; Joseph, A.; Frahm, J.; Teixeira, A. Data-Driven Critical Tract Variable Determination for European Portuguese. Information 2020, 11, 491. https://doi.org/10.3390/info11100491

AMA Style

Silva S, Almeida N, Cunha C, Joseph A, Frahm J, Teixeira A. Data-Driven Critical Tract Variable Determination for European Portuguese. Information. 2020; 11(10):491. https://doi.org/10.3390/info11100491

Chicago/Turabian Style

Silva, Samuel, Nuno Almeida, Conceição Cunha, Arun Joseph, Jens Frahm, and António Teixeira. 2020. "Data-Driven Critical Tract Variable Determination for European Portuguese" Information 11, no. 10: 491. https://doi.org/10.3390/info11100491

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