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FonaDyn

Phonatory Dynamics and States

The voice has several non-linear and context-dependent mechanisms that can give rise to distinct phonatory states. We submit that much of the observed variability in objective voice metrics results from the influence of such states, and will attempt to account for some of them, using a state-based analysis paradigm.

Falsetto and normal voice are two examples of phonatory states. The vocal folds can be made to vibrate (phonation) in several different ways, each covering a certain range in frequency and sound level. Because the voice is so complex and flexible, conventional voice metrics typically have large variability across individuals, which is a problem when establishing normative data for clinical voice assessment. While the static parameters of voice production and their acoustic correlates are well understood, for one sound at a time, little is known of the temporal dynamics of phonation in speech and singing. Established voice measures seek to eliminate variation by averaging or by constraining the context, which discards information. The voice has several non-linear and context-dependent mechanisms that can give rise to distinct phonatory states. We submit that much of the observed variability results from the influence of such states, and will attempt to account for some of them, using a state-based analysis paradigm. We investigate specifically (a) the existence of state-like conditions that are traversed with varying vocal effort level (dynamics); (b) how selected mainstream voice problems might be represented in terms of transitions between such states, mapped into the well-established reference frame of the Voice Range Profile (phonetogram). The outcome will be of fundamental importance to the correct interpretation of acoustic voice measures in general.

Group: Sound and Music Computing

Staff:
Sten Ternström (Project leader)
Peter Pabon
Andreas Selamtzis

Funding: VR ( 2010-4565)

Duration: 2011-01-01 - 2018-12-31

KTH research database: http://researchprojects.kth.se/index.php/kb_1/io_10677/io.html

Keywords: voice, analysis, non-linear dynamics, voice range profile, electroglottography

Related publications:

2017

Selamtzis, A., & Ternström, S. (2017). Investigation of the relationship between the electroglottogram waveform, fundamental frequency and sound pressure level using clustering. Journal of Voice, available online 8 December 2016, 8. [abstract] [link]

2016

Ternström, S., Pabon, P., & Södersten, M. (2016). The Voice Range Profile: its function, applications, pitfalls and potential. Acta Acustica united with Acustica, 102(2), 268-283. [abstract] [link]

2014

Selamtzis, A., & Ternström, S. (2014). Analysis of vibratory states in phonation using spectral features of the electroglottographic signal. Journal of the Acoustical Society of America, 136(5), 2773-2783. [abstract] [link]

2011

Pabon, P., Ternström, S., & Lamarche, A. (2011). Fourier descriptor analysis and unification of Voice Range Profile contours: method and applications. Journal of Speech, Language, and Hearing Research, 54, 755-776. [abstract]







Published by: TMH, Speech, Music and Hearing
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Last updated: 2012-11-09