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JSLHR-S-16-0395traser_SuppS1.tif (4.03 MB)

Teeth in 3D vocal tract models (Traser et al., 2017)

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posted on 2017-09-12, 17:23 authored by Louisa Traser, Peter Birkholz, Tabea Viktoria Flügge, Robert Kamberger, Michael Burdumy, Bernhard Richter, Jan Gerrit Korvink, Matthias Echternach
Purpose: Recently, efforts have been made to investigate the vocal tract using magnetic resonance imaging (MRI). Due to technical limitations, teeth were omitted in many previous studies on vocal tract acoustics. However, the knowledge of how teeth influence vocal tract acoustics might be important in order to estimate the necessity of implementing teeth in vocal tract models. The aim of this study was therefore to estimate the effect of teeth on vocal tract acoustics.
Method: The acoustic properties of 18 solid (3-dimensional printed) vocal tract models without teeth were compared to the same 18 models including teeth in terms of resonance frequencies (fRn). The fRn were obtained from the transfer functions of these models excited by white noise at the glottis level. The models were derived from MRI data of 2 trained singers performing 3 different vowel conditions (/i/, /a /, and /u/) in speech and low-pitched and high-pitched singing.
Results: Depending on the oral configuration, models exhibiting side cavities or side branches were characterized by major changes in the transfer function when teeth were implemented via the introduction of pole-zero pairs.
Conclusions: To avoid errors in modeling, teeth should be included in 3-dimensional vocal tract models for acoustic evaluation.

Supplemental Material S1. Display of the 36 3D-printed models (three vowels, three tasks, two subjects, with and without teeth).

Traser, L., Birkholz, P., Flügge, T. V., Kamberger, R., Burdumy, M., Richter, B., ... Echternach, M. (2017). Relevance of the implementation of teeth in three-dimensional vocal tract models. Journal of Speech, Language, and Hearing Research, 60, 2379–2393.


Matthias Echternach’s and Bernhard Richter’s work is supported by the Deutsche Forschungsgemeinschaft (DFG), Grant EC 409/1-2 and RI 1050/4-3.