Controlling chaotic oscillations in a symmetric two-mass model of the vocal folds

Guasch, Oriol; Hirtum, Annemie van; Álvarez, Inés; Arnela, Marc

doi:10.1016/j.chaos.2022.112188

Cited by 7 publications

(3 citation statements)

References 63 publications

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“…(1) respectively stand for the identity and zero matrices, while in the first row we get the mass matrix M, the damping matrix C, the stiffness matrix K and the collision matrix Θ. Explicit expressions for them can be found in [4]. The force vector is given by f v = (P 1 Ld 1l , 0) ⊤ , where L is the glottis length, d 1l the thickness of m 1l and P 1 the glottal pressure,…”

Section: Theory 21 Vocal Fold Modelmentioning

confidence: 99%

“…It was first proposed in [4], that it might be possible to regulate the chaotic motion of the VFs by means of a theoretical phonation pacemaker attached to one of the model masses and whose parameters could be tuned to alter the energy of the system appropriately [5,6]. In this work we want to explore the effects that the pacemaker might have on the numerical generation of vowel /a/.…”

Section: Introductionmentioning

confidence: 99%

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Effects of controlling chaotic vocal fold vibrations on finite element generated vowels

Guasch,

Freixes,

Arnela

et al. 2024

Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023

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Lumped mass models of the vocal folds have been widely used to analyze the physics of human phonation. This is a strongly non-linear process that results in regular selfoscillations of the vocal folds. However, various factors such as polyps, excessive subglottal pressure, etc., can alter such motion and make it chaotic. Ideally, it would be possible to use a smart material to control the dynamics of the vocal folds and restore its regularity. In this paper, we will see the effects of such a control strategy on the generation of vowels. The chaotic and the controlled train of glottal pulses will be imposed as boundary conditions at the glottis of a three-dimensional model of the vocal tract (VT). Then, the finite element method will be used to solve the wave equation inside the VT and the spectra and sound of the generated vowels will be compared to check the performance of the chaos control strategy on phonation.

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Section: Theory 21 Vocal Fold Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effects of controlling chaotic vocal fold vibrations on finite element generated vowels

Guasch,

Freixes,

Arnela

et al. 2024

Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023

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“…Deterministic chaos makes the spectrum noisy, and the distorted harmonics in high-pitched vocalizations are easily mistaken for formants on spectrograms [21]. As a result, it is often assumed that chaos would make vowels difficult to recognize [58], but again we are not aware of any perceptual data to confirm this.…”

Section: Introductionmentioning

confidence: 99%

NLP and speech intelligibility

Anikin,

Pisanski,

Reby

2024

Preprint

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At some point in our evolutionary history, humans lost vocal membranes and air sacs, representing an unexpected simplification of the vocal apparatus relative to other apes. One hypothesis is that these simplifications represent anatomical adaptations for speech because a simpler larynx provides a suitably stable and tonal vocal source with fewer nonlinear vocal phenomena (NLP). The key assumption that NLP reduce speech intelligibility is indirectly supported by studies of dysphonia, but it has not been experimentally tested. Here, we manipulate NLP in vocal stimuli ranging from single vowels to sentences, showing that the source needs to be stable, but not necessarily tonal. When the task is to discriminate synthesized monophthong and diphthong vowels, continuous NLP (subharmonics, amplitude modulation, and even deterministic chaos) actually improve vowel perception in high-pitched voices, likely because the resulting dense spectrum reveals formant transitions. Rough-sounding voices also remain highly intelligible when continuous NLP are added to recorded words and sentences. In contrast, voicing interruptions and pitch jumps dramatically reduce speech intelligibility, likely by interfering with voicing contrasts and normal intonation. We argue that NLP were not eliminated from the human vocal repertoire as we evolved for speech, but only brought under better control.

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