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Determining The Relevant Criteria For 3D Vocal Tract Characterisation

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JournalJournal of Voice
DateAccepted/In press - 3 Apr 2017
DateE-pub ahead of print (current) - 21 Jun 2017
Number of pages13
Pages (from-to)1-13
Early online date21/06/17
Original languageEnglish

Abstract

0.1. Introduction
Soprano singers face a number of specific challenges when singing vowels at high frequencies, due to the wide spacing of
harmonics in the voice source. The varied and complex techniques used to overcome these are still not fully understood.
Magnetic resonance imaging (MRI) has become increasingly popular in recent years for singing voice analysis. This study
proposes a new protocol using 3D MRI to investigate the articulatory parameters relevant to resonance tuning, a technique whereby
the singer alters their vocal tract to shift its resonances nearer to a voice source harmonic, increasing the amplitude of the sound
produced.
0.2. Method
The protocol was tested with a single soprano opera singer. Drawing on previous MRI studies, articulatory measurements from
3D MRI images were compared to vocal tract resonances measured directly using broad-band noise excitation. The suitability of
the protocol was assessed using statistical analysis.
0.3. Results
No clear linear relationships were apparent between articulatory characteristics and vocal tract resonances. The results were
highly vowel-dependent, showing dierent patterns of resonance tuning and interactions between variables. This potentially indicates
a complex interaction between the vocal tract and sung vowels in soprano voices, meriting further investigation.
0.4. Conclusion
The eective interpretation of MRI data is essential for a deeper understanding of soprano voice production, and in particular
the phenomenon of resonance tuning. This paper presents a new protocol that contributes towards this aim, and the results suggest
that a more vowel-specific approach is necessary in the wider investigation of resonance tuning in female voices.

Bibliographical note

Crown Copyright © 2017 Published by Elsevier Inc. on behalf of The Voice Foundation. All rights reserved. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy.

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