scholarly journals Efficient numerical simulation of the human voice

2021 ◽  
Author(s):  
Paul Maurerlehner ◽  
Stefan Schoder ◽  
Clemens Freidhager ◽  
Andreas Wurzinger ◽  
Alexander Hauser ◽  
...  
Keyword(s):  
Vocal Tract ◽  
Numerical Models ◽  
Hybrid Approach ◽  
Three Dimensional ◽  
Flow Simulation ◽  
Vocal Folds ◽  
Material Behavior ◽  
Voice Source ◽  
Voice Treatment ◽  
Key Factor

AbstractThe process of voice production is a complex process and depends on the correct interaction of the vocal folds and the glottal airstream inducing the primary voice source, which is subsequently modulated by the vocal tract. Due to the restricted access to the glottis, not all aspects of the three-dimensional process can be captured by measurements without influencing the measurement object. Hence, the application of a numerical tool capturing the physical process of phonation can provide an extended database for voice treatment and, therefore, can contribute to an increased effectiveness of voice treatment. However, such numerical models involve complex and demanding procedures to model the material behavior and the mechanical contact of the vocal folds and to realize moving boundaries of the involved physical domains. The present paper proposes a numerical model called simVoice, which circumvents these computational expenses by prescribing the experimentally obtained vocal fold motion within the simulation. Additionally, a hybrid approach for sound computation further enhances the computational efficiency and yields good agreement with acoustic measurements. An analysis of the computational workloads suggests that the key factor for a further increase in efficiency is an optimized flow simulation and source term computation.

Deep Learning for Three-Dimensional Volumetric Recovery of Cloud Fields

2021 ◽  
Author(s):  
Yael Sde-Chen ◽  
Yoav Y. Schechner ◽  
Vadim Holodovsky ◽  
Eshkol Eytan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Large Scale ◽  
Optimization Technique ◽  
Hybrid Approach ◽  
Three Dimensional ◽  
Physical Nature ◽  
Key Factor ◽  
Volumetric Reconstruction ◽  
Real World Datasets

<p>Clouds are a key factor in Earth's energy budget and thus significantly affect climate and weather predictions. These effects are dominated by shallow warm clouds (shown by Sherwood et al., 2014, Zelinka et al., 2020) which tend to be small and heterogenous. Therefore, remote sensing of clouds and three-dimensional (3D) volumetric reconstruction of their internal properties are of significant importance.</p><p>Recovery of the volumetric information of the clouds relies on 3D radiative transfer, that models 3D multiple scattering. This model is complex and nonlinear. Thus, inverting the model poses a major challenge and typically requires using a simplification. A common relaxation assumes that clouds are horizontally uniform and infinitely broad, leading to one-dimensional modeling. However, generally this assumption is invalid since clouds are naturally highly heterogeneous. A novel alternative is to perform cloud retrieval by developing tools of 3D scattering tomography. Then, multiple satellite images of the clouds are acquired from different points of view. For example, simultaneous multi-view radiometric images of clouds are proposed by the CloudCT project, funded by the ERC. Unfortunately, 3D scattering tomography require high computational resources. This results, in practice, in slow run times and prevents large scale analysis. Moreover, existing scattering tomography is based on iterative optimization, which is sensitive to initialization.</p><p>In this work we introduce a deep neural network for 3D volumetric reconstruction of clouds. In recent years, supervised learning using deep neural networks has led to remarkable results in various fields ranging from computer vision to medical imaging. However, these deep learning techniques have not been extensively studied in the context of volumetric atmospheric science and specifically cloud research.</p><p>We present a convolutional neural network (CNN) whose architecture is inspired by the physical nature of clouds. Due to the lack of real-world datasets, we train the network in a supervised manner using a physics-based simulator that generates realistic volumetric cloud fields. In addition, we propose a hybrid approach, which combines the proposed neural network with an iterative physics-based optimization technique.</p><p>We demonstrate the recovery performance of our proposed method in cloud fields. In a single cloud-scale, our resulting quality is comparable to state-of-the-art methods, while run time improves by orders of magnitude. In contrast to existing physics-based methods, our network offers scalability, which enables the reconstruction of wider cloud fields. Finally, we show that the hybrid approach leads to improved retrieval in a fast process.</p>

The Singing Voice

2018 ◽  
pp. 116-142
Author(s):  
Johan Sundberg
Keyword(s):  
Mechanical Properties ◽  
Vocal Tract ◽  
Voice Quality ◽  
Vocal Folds ◽  
Sound Level ◽  
Vowel Sound ◽  
Formant Frequency ◽  
Voice Source ◽  
Subglottal Pressure ◽  
The Voice

The sound quality of singing is determined by three basic factors—the air pressure under the vocal folds (or the subglottal pressure), the mechanical properties of the vocal folds, and the resonance properties of the vocal tract. Subglottal pressure is controlled by the respiratory apparatus. It regulates vocal loudness and is varied with pitch in singing. Together with the mechanical properties of the folds, which are controlled by laryngeal muscles, it has a decisive influence on vocal fold vibrationswhich convert the tracheal airstream to a pulsating airflow, the voice source. The voice source determines pitch, vibrato, and register, and also the overall slope of the spectrum. The sound of the voice source is filtered by the resonances of the vocal tract, or the formants, of which the two lowest determine the vowel quality and the higher ones the personal voice quality. Timing is crucial for creating emotional expressivity; it uses an acoustic code that shows striking similarities to that used in speech. The perceived loudness of a vowel sound seems more closely related to the subglottal pressure with which it was produced than with the acoustical sound level. Some investigations of acoustical correlates of tone placement and variation of larynx height are described, as are properties that affect the perceived naturalness of synthesized singing. Finally, subglottal pressure, voice source, and formant-frequency characteristics of some non-classical styles of singing are discussed.

On the Apparent Propagation Speed in Transmission Line Matrix Uniform Grid Meshes

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Alexandre S. Brandão ◽  
Edson Cataldo ◽  
Fabiana R. Leta
Keyword(s):  
Transmission Line ◽  
Sound Propagation ◽  
Vocal Tract ◽  
Numerical Models ◽  
A Priori ◽  
Three Dimensional ◽  
Propagation Speed ◽  
Uniform Grid ◽  
Transmission Line Matrix ◽  
Resonance Frequencies

Numerical models consisting of two-dimensional (2D) and three-dimensional (3D) uniform grid meshes for the transmission line matrix method (TLM) currently use 2 and 3, respectively, to compensate for the apparent sound speed. In this paper, new compensation factors are determined from a priori simulations, performed without compensation, in 2D and 3D TLM one-section tube models. The frequency values of the first mistuned resonance peaks, obtained from these simulations, are substituted in the corresponding equations for the resonance frequencies in one-section tubes to find the apparent sound propagation speed in the mesh environment and, thus, the necessary compensation. The new factors have been tested in more complex models like a two-tube concatenation model and a realistic magnetic resonance imaging (MRI)-reconstructed human vocal tract (VT) model. Important VT modeling results confirm the improvement over the conventional compensation factors, particularly for frequencies above 4 kHz. Among these results are the identification of the spectral trough at about 5200 Hz caused by the piriform fossa and the application of a pitch extraction algorithm to the 3D TLM output signal, finding a difference smaller than 0.66% relatively to human voice pitch.

scholarly journals Vibrations of Nonlinear Elastic Structure Excited by Compressible Flow

2021 ◽  
Vol 11 (11) ◽  
pp. 4748
Author(s):  
Monika Balázsová ◽  
Miloslav Feistauer ◽  
Jaromír Horáček ◽  
Adam Kosík
Keyword(s):  
Compressible Flow ◽  
Nonlinear Elasticity ◽  
Vocal Tract ◽  
Stokes Equations ◽  
Vocal Folds ◽  
Nonlinear Material ◽  
Navier Stokes ◽  
Arbitrary Lagrangian Eulerian ◽  
Navier Stokes Equations ◽  
Reliable Solution

This study deals with the development of an accurate, efficient and robust method for the numerical solution of the interaction of compressible flow and nonlinear dynamic elasticity. This problem requires the reliable solution of flow in time-dependent domains and the solution of deformations of elastic bodies formed by several materials with complicated geometry depending on time. In this paper, the fluid–structure interaction (FSI) problem is solved numerically by the space-time discontinuous Galerkin method (STDGM). In the case of compressible flow, we use the compressible Navier–Stokes equations formulated by the arbitrary Lagrangian–Eulerian (ALE) method. The elasticity problem uses the non-stationary formulation of the dynamic system using the St. Venant–Kirchhoff and neo-Hookean models. The STDGM for the nonlinear elasticity is tested on the Hron–Turek benchmark. The main novelty of the study is the numerical simulation of the nonlinear vocal fold vibrations excited by the compressible airflow coming from the trachea to the simplified model of the vocal tract. The computations show that the nonlinear elasticity model of the vocal folds is needed in order to obtain substantially higher accuracy of the computed vocal folds deformation than for the linear elasticity model. Moreover, the numerical simulations showed that the differences between the two considered nonlinear material models are very small.

scholarly journals Experimental and Numerical Investigation of 3D Dam-Break Wave Propagation in an Enclosed Domain with Dry and Wet Bottom

2021 ◽  
Vol 11 (12) ◽  
pp. 5638
Author(s):  
Selahattin Kocaman ◽  
Stefania Evangelista ◽  
Hasan Guzel ◽  
Kaan Dal ◽  
Ada Yilmaz ◽  
...  
Keyword(s):  
Wave Propagation ◽  
Numerical Models ◽  
Three Dimensional ◽  
Dam Break ◽  
Dam Failure ◽  
Navier Stokes ◽  
Negative Wave ◽  
Through Flow ◽  
Instantaneous Removal ◽  
Surface Patterns

Dam-break flood waves represent a severe threat to people and properties located in downstream regions. Although dam failure has been among the main subjects investigated in academia, little effort has been made toward investigating wave propagation under the influence of tailwater depth. This work presents three-dimensional (3D) numerical simulations of laboratory experiments of dam-breaks with tailwater performed at the Laboratory of Hydraulics of Iskenderun Technical University, Turkey. The dam-break wave was generated by the instantaneous removal of a sluice gate positioned at the center of a transversal wall forming the reservoir. Specifically, in order to understand the influence of tailwater level on wave propagation, three tests were conducted under the conditions of dry and wet downstream bottom with two different tailwater depths, respectively. The present research analyzes the propagation of the positive and negative wave originated by the dam-break, as well as the wave reflection against the channel’s downstream closed boundary. Digital image processing was used to track water surface patterns, and ultrasonic sensors were positioned at five different locations along the channel in order to obtain water stage hydrographs. Laboratory measurements were compared against the numerical results obtained through FLOW-3D commercial software, solving the 3D Reynolds-Averaged Navier–Stokes (RANS) with the k-ε turbulence model for closure, and Shallow Water Equations (SWEs). The comparison achieved a reasonable agreement with both numerical models, although the RANS showed in general, as expected, a better performance.

scholarly journals Impact of the Sub-Grid Scale Turbulence Model in Aeroacoustic Simulation of Human Voice

2021 ◽  
Vol 11 (4) ◽  
pp. 1970
Author(s):  
Martin Lasota ◽  
Petr Šidlof ◽  
Manfred Kaltenbacher ◽  
Stefan Schoder
Keyword(s):  
Sound Propagation ◽  
Vocal Tract ◽  
Vocal Folds ◽  
Equation Model ◽  
Voice Production ◽  
Human Voice ◽  
Large Eddy ◽  
Aeroacoustic Simulation ◽  
Scale Turbulence ◽  
The One

In an aeroacoustic simulation of human voice production, the effect of the sub-grid scale (SGS) model on the acoustic spectrum was investigated. In the first step, incompressible airflow in a 3D model of larynx with vocal folds undergoing prescribed two-degree-of-freedom oscillation was simulated by laminar and Large-Eddy Simulations (LES), using the One-Equation and Wall-Adaptive Local-Eddy (WALE) SGS models. Second, the aeroacoustic sources and the sound propagation in a domain composed of the larynx and vocal tract were computed by the Perturbed Convective Wave Equation (PCWE) for vowels [u:] and [i:]. The results show that the SGS model has a significant impact not only on the flow field, but also on the spectrum of the sound sampled 1 cm downstream of the lips. With the WALE model, which is known to handle the near-wall and high-shear regions more precisely, the simulations predict significantly higher peak volumetric flow rates of air than those of the One-Equation model, only slightly lower than the laminar simulation. The usage of the WALE SGS model also results in higher sound pressure levels of the higher harmonic frequencies.

Ice-Phase Precipitation

2017 ◽  
Vol 58 ◽  
pp. 6.1-6.36 ◽  
Author(s):  
I. Gultepe ◽  
A. J. Heymsfield ◽  
P. R. Field ◽  
D. Axisa
Keyword(s):  
Collection Efficiency ◽  
Numerical Models ◽  
Mass Density ◽  
Three Dimensional ◽  
Phase Precipitation ◽  
Microphysical Parameters ◽  
Mass Size ◽  
Ice Water ◽  
Ice Phase

AbstractIce-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

scholarly journals The Formation of a Cavity in a 3D Flux Rope

2013 ◽  
Vol 8 (S300) ◽  
pp. 147-150 ◽  
Author(s):  
Donald Schmit ◽  
Sarah Gibson
Keyword(s):  
Ad Hoc ◽  
Numerical Models ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Flux Rope ◽  
Multiple Structures ◽  
Field Lines ◽  
Hydrostatic Balance ◽  
Distinct Field ◽  
Three Dimensional Space

AbstractThere are currently no three dimensional numerical models which describe the magnetic and energetic formation of prominences self-consistently. Consequently, there has not been significant progress made in understanding the connection between the dense prominence plasma and the coronal cavity. We have taken an ad-hoc approach to understanding the energetic implications of the magnetic models of prominence structure. We extract one dimensional magnetic field lines from a 3D MHD model of a flux rope and solve for hydrostatic balance along these field lines incorporating field-aligned thermal conduction, uniform heating, and radiative losses. The 1D hydrostatic solutions for density and temperature are then mapped back into three dimensional space, which allows us to consider the projection of multiple structures. We find that the 3D flux rope is composed of several distinct field line types. A majority of the flux rope interior field lines are twisted but not dipped. These field lines are density-reduced relative to unsheared arcade field lines. We suggest the cavity may form along these short interior field lines which are surrounded by a sheath of dipped field lines. This geometric arrangement would create a cavity on top of a prominence, but the two structures would not share field lines or plasma.

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