High-fidelity continuum modeling predicts avian voiced sound production

Evolutionary novelties underlie sound production in baleen whales

Baleen whales (mysticetes) use vocalizations to mediate their complex social and reproductive behaviours in vast, opaque marine environments1. Adapting to an obligate aquatic lifestyle demanded fundamental physiological changes to efficiently produce sound, including laryngeal specializations2-4. Whereas toothed whales (odontocetes) evolved a nasal vocal organ5, mysticetes have been thought to use the larynx for sound production1,6-8. However, there has been no direct demonstration that the mysticete larynx can phonate, or if it does, how it produces the great diversity of mysticete sounds9. Here we combine experiments on the excised larynx of three mysticete species with detailed anatomy and computational models to show that mysticetes evolved unique laryngeal structures for sound production. These structures allow some of the largest animals that ever lived to efficiently produce frequency-modulated, low-frequency calls. Furthermore, we show that this phonation mechanism is likely to be ancestral to all mysticetes and shares its fundamental physical basis with most terrestrial mammals, including humans10, birds11, and their closest relatives, odontocetes5. However, these laryngeal structures set insurmountable physiological limits to the frequency range and depth of their vocalizations, preventing them from escaping anthropogenic vessel noise12,13 and communicating at great depths14, thereby greatly reducing their active communication range.

Predicting 3D soft tissue dynamics from 2D imaging using physics informed neural networks

Tissue dynamics play critical roles in many physiological functions and provide important metrics for clinical diagnosis. Capturing real-time high-resolution 3D images of tissue dynamics, however, remains a challenge. This study presents a hybrid physics-informed neural network algorithm that infers 3D flow-induced tissue dynamics and other physical quantities from sparse 2D images. The algorithm combines a recurrent neural network model of soft tissue with a differentiable fluid solver, leveraging prior knowledge in solid mechanics to project the governing equation on a discrete eigen space. The algorithm uses a Long-short-term memory-based recurrent encoder-decoder connected with a fully connected neural network to capture the temporal dependence of flow-structure-interaction. The effectiveness and merit of the proposed algorithm is demonstrated on synthetic data from a canine vocal fold model and experimental data from excised pigeon syringes. The results showed that the algorithm accurately reconstructs 3D vocal dynamics, aerodynamics, and acoustics from sparse 2D vibration profiles.

Subject-Specific Computational Fluid-Structure Interaction Modeling of Rabbit Vocal Fold Vibration

A full three-dimensional (3D) fluid-structure interaction (FSI) study of subject-specific vocal fold vibration is carried out based on the previously reconstructed vocal fold models of rabbit larynges. Our primary focuses are the vibration characteristics of the vocal fold, the unsteady 3D flow field, and comparison with a recently developed 1D glottal flow model that incorporates machine learning. The 3D FSI model applies strong coupling between the finite-element model for the vocal fold tissue and the incompressible Navier-Stokes equation for the flow. Five different samples of the rabbit larynx, reconstructed from the magnetic resonance imaging (MRI) scans after the in vivo phonation experiments, are used in the FSI simulation. These samples have distinct geometries and a different inlet pressure measured in the experiment. Furthermore, the material properties of the vocal fold tissue were determined previously for each individual sample. The results demonstrate that the vibration and the intraglottal pressure from the 3D flow simulation agree well with those from the 1D flow model based simulation. Further 3D analyses show that the inferior and supraglottal geometries play significant roles in the FSI process. Similarity of the flow pattern with the human vocal fold is discussed. This study supports the effective usage of rabbit larynges to understand human phonation and will help guide our future computational studies that address vocal fold disorders.

Computational Modeling of Voice Production Using Excised Canine Larynx

A combined experimental-numerical work was conducted to comprehensively validate a subject-specific continuum model of voice production in larynx using excised canine laryngeal experiments. The computational model is a coupling of the Navier-Stokes equations for glottal flow dynamics and a finite element model of vocal fold dynamics. The numerical simulations employed a cover-body vocal fold structure with the geometry reconstructed from magnetic resonance imaging scans and the material properties determined through an optimization-based inverse process of experimental indentation measurement. The results showed that the simulations predicted key features of the dynamics observed in the experiments, including the skewing of the glottal flow waveform, mucosal wave propagation, continuous increase of the divergent angle and intraglottal swirl strength during glottal closing, and flow recirculation between glottal jet and vocal fold. The simulations also predicted the increase of the divergent angle, glottal jet speed, and intraglottal flow swirl strength with the subglottal pressure, same as in the experiments. Quantitatively, the simulations over-predicted the frequency and jet speed and under-predicted the flow rate and divergent angle for the larynx under study. The limitations of the model and their implications were discussed.

Flow-signal correlation in seal whisker array sensing

Phocid seals detect and track artificial or biogenic hydrodynamic trails based on mechanical signals of their whisker arrays. In this paper, we investigated the correlations between flow structures and whisker array signals using a simplified numerical model of fluid-structure interaction (FSI). Three-dimensional (3D) wakes of moving paddles in three different shapes (rectangular plate, undulated plate, and circular cylinder) were simulated using an in-house immersed-boundary-method-based computational fluid dynamics solver. One-way FSI was then simulated to obtain the dynamic behavior and root signal of each whisker in the two whisker arrays on a seal head in each wake. The position, geometry, and material properties of each whisker were modeled based on the measurements reported in literatures. The correlations between the wake structures and whisker array signals were analyzed. It was found that the patterns of the signals on the whisker arrays can reflect the strength, timing, and moving trajectories of the jets induced by the vortices in the wakes. Specifically, the rectangular plate generates the strongest starting vortex ring as well as the strongest jets, while the undulated plate generates the weakest ones. These flow features are fully reflected by the largest whisker signal magnitude in the rectangular plate sensing and the smallest one in the undulated plate sensing. Moreover, the timing of the signal initiation and the maximum signal agree well with the timing of the jet reaching the arrays and the maximum flow speed, respectively. The correlation coefficient between the moving trajectories of the jet and the movement of the high signal level region in the array was found to be higher than 0.9 in the rectangular plate case. The results provide a physical insight into the mechanisms of seal whisker flow sensing.

How Loud Can you go? Physical and Physiological Constraints to Producing High Sound Pressures in Animal Vocalizations

Sound is vital for communication and navigation across the animal kingdom and sound communication is unrivaled in accuracy and information richness over long distances both in air and water. The source level (SL) of the sound is a key factor in determining the range at which animals can communicate and the range at which echolocators can operate their biosonar. Here we compile, standardize and compare measurements of the loudest animals both in air and water. In air we find a remarkable similarity in the highest SLs produced across the different taxa. Within all taxa we find species that produce sound above 100 dBpeak re 20 μPa at 1 m, and a few bird and mammal species have SLs as high as 125 dBpeak re 20 μPa at 1 m. We next used pulsating sphere and piston models to estimate the maximum sound pressures generated in the radiated sound field. These data suggest that the loudest species within all taxa converge upon maximum pressures of 140–150 dBpeak re 20 μPa in air. In water, the toothed whales produce by far the loudest SLs up to 240 dBpeak re 1 μPa at 1 m. We discuss possible physical limitations to the production, radiation and propagation of high sound pressures. Furthermore, we discuss physiological limitations to the wide variety of sound generating mechanisms that have evolved in air and water of which many are still not well-understood or even unknown. We propose that in air, non-linear sound propagation forms a limit to producing louder sounds. While non-linear sound propagation may play a role in water as well, both sperm whale and pistol shrimp reach another physical limit of sound production, the cavitation limit in water. Taken together, our data suggests that both in air and water, animals evolved that produce sound so loud that they are pushing against physical rather than physiological limits of sound production, radiation and propagation.

Effect of Supraglottal Acoustics on Fluid-Structure Interaction During Human Voice Production

A hydrodynamic/acoustic splitting method was used to examine the effect of supraglottal acoustics on fluid-structure interactions during human voice production in a two-dimensional computational model. The accuracy of the method in simulating compressible flows in typical human airway conditions was verified by comparing it to full compressible flow simulations. The method was coupled with a three-mass model of vocal fold lateral motion to simulate fluid-structure interactions during human voice production. By separating the acoustic perturbation components of the airflow, the method allows isolation of the role of supraglottal acoustics in fluid-structure interactions. The results showed that an acoustic resonance between a higher harmonic of the sound source and the first formant of the supraglottal tract occurred during normal human phonation when the fundamental frequency was much lower than the formants. The resonance resulted in acoustic pressure perturbation at the glottis which was of the same order as the incompressible flow pressure and found to affect vocal fold vibrations and glottal flow rate waveform. Specifically, the acoustic perturbation delayed the opening of the glottis, reduced the vertical phase difference of vocal fold vibrations, decreased flow rate and maximum flow deceleration rate (MFDR) at the glottal exit; yet, they had little effect on glottal opening. The results imply that the sound generation in the glottis and acoustic resonance in the supraglottal tract are coupled processes during human voice production and computer modeling of vocal fold vibrations needs to include supraglottal acoustics for accurate predictions.

Syringeal vocal folds do not have a voice in zebra finch vocal development

Vocal behavior can be dramatically changed by both neural circuit development and postnatal maturation of the body. During song learning in songbirds, both the song system and syringeal muscles are functionally changing, but it is unknown if maturation of sound generators within the syrinx contributes to vocal development. Here we densely sample the respiratory pressure control space of the zebra finch syrinx in vitro. We show that the syrinx produces sound very efficiently and that key acoustic parameters, minimal fundamental frequency, entropy and source level, do not change over development in both sexes. Thus, our data suggest that the observed acoustic changes in vocal development must be attributed to changes in the motor control pathway, from song system circuitry to muscle force, and not by material property changes in the avian analog of the vocal folds. We propose that in songbirds, muscle use and training driven by the sexually dimorphic song system are the crucial drivers that lead to sexual dimorphism of the syringeal skeleton and musculature. The size and properties of the instrument are thus not changing, while its player is.