The 50 most-cited articles in The Journal of the Acoustical Society of America, 2023

This work examines the use of generative adversarial networks for reconstructing sound fields from experimental data. It is investigated whether generative models, which learn the underlying statistics of a given signal or process, can improve the spatio-temporal reconstruction of a sound field by extending its bandwidth. The problem is significant as acoustic array processing is naturally band limited by the spatial sampling of the sound field (due to the difficulty to satisfy the Nyquist criterion in space domain at high frequencies). In this study, the reconstruction of spatial room impulse responses in a conventional room is tested based on three different generative adversarial models. The results indicate that the models can improve the reconstruction, mostly by recovering some of the sound field energy that would otherwise be lost at high frequencies. There is an encouraging outlook in the use of statistical learning models to overcome the bandwidth limitations of acoustic sensor arrays. The approach can be of interest in other areas, such as computational acoustics, to…

The classification of underwater acoustic signals has garnered a great deal of attention in recent years due to its potential applications in military and civilian contexts. While deep neural networks have emerged as the preferred method for this task, the representation of the signals plays a crucial role in determining the performance of the classification. However, the representation of underwater acoustic signals remains an under-explored area. In addition, the annotation of large-scale datasets for the training of deep networks is a challenging and expensive task. To tackle these challenges, we propose a novel self-supervised representation learning method for underwater acoustic signal classification. Our approach consists of two stages: a pretext learning stage using unlabeled data and a downstream fine-tuning stage using a small amount of labeled data. The pretext learning stage involves randomly masking the log Mel spectrogram and reconstructing the masked part using the Swin Transformer architecture. This allows us to learn a general representation of the acoustic signal.…

When a bilingual switches languages, do they switch their voice? Using a conversational corpus of speech from early Cantonese-English bilinguals (n = 34), this paper examines the talker-specific acoustic signatures of bilingual voices. Following the psychoacoustic model of voice, 24 filter and source-based acoustic measurements are estimated. The analysis summarizes mean differences for these dimensions and identifies the underlying structure of each talker's voice across languages with principal component analyses. Canonical redundancy analyses demonstrate that while talkers vary in the degree to which they have the same voice across languages, all talkers show strong similarity with themselves, suggesting an individual's voice remains relatively constant across languages. Voice variability is sensitive to sample size, and we establish the required sample to settle on a consistent impression of one's voice. These results have implications for human and machine voice recognition for bilinguals and monolinguals and speak to the substance of voice prototypes.

Throughout history, many buildings of significant cultural value have been lost due to natural disasters (e.g., earthquakes, volcanic eruptions, subsidence, etc.) as well as other human causes (e.g., fire, war destruction, etc.). The Tajo Opera theatre was hit by an earthquake that led to the collapse of the entire structure eight months after it was built. This paper deals with the revival of the acoustic characteristics of one of the masterpieces of the architect Giovanni Carlo Sicinio Galli Bibiena. The realization of a three-dimensional (3D) model that faithfully reproduces the architectural features of the Royal Tajo Opera theatre of Lisbon allows the authors to perform acoustic simulations that reveal the sound field representing the environment perceived by the audience during artistic performances in Lisbon in 1755. In addition, the simulated results have been compared with the values of the Teatro Comunale of Bologna, which has a similar bell-shaped plan layout and has already been studied by the authors. For the comparison of the two opera theatres, both the stalls and the…

Source localization with a geoacoustic model requires optimizing the model over a parameter space of range and depth with the objective of matching a predicted sound field to a field measured on an array. We propose a sample-efficient sequential Bayesian optimization strategy that models the objective function as a Gaussian process (GP) surrogate model conditioned on observed data. Using the mean and covariance functions of the GP, a heuristic acquisition function proposes a candidate in parameter space to sample, balancing exploitation (sampling around the best observed objective function value) and exploration (sampling in regions of high variance in the GP). The candidate sample is evaluated, and the GP conditioned on the updated data. Optimization proceeds sequentially until a fixed budget of evaluations is expended. We demonstrate source localization for a shallow-water waveguide using Monte Carlo simulations and experimental data from an acoustic source tow. Compared to grid search and quasi-random sampling strategies, simulations and experimental results indicate the Bayesian…

We theoretically, numerically, and experimentally study a lightweight metastructure that can simultaneously reduce vibration and noise in a broad low-frequency range. We introduce spiral slits and micro-perforations in the panel and core plate of a face-centered cubic sandwich structure, respectively. A bottom-up acoustic impedance theory is developed to describe the impedance of a single unit cell. Broadband low-frequency sound absorption is achieved for a 3 × 3 supercell via reinforcement learning optimization. The resonant coupling of the upper spiral panel and the lower panel of the unit can form a wide hybridized bandgap for flexural waves, which is further validated for vibration isolation with a one-dimensional supercell. The proposed multifunctional metastructure provides a new route to design lightweight load-bearing structures with noise and vibration reduction performance for potential applications such as aerospace engineering and transportation vehicles, among others.

Performing reproducible vessel source level (SL) measurements is complicated by seabed reflections in shallow water. In deep water, with a hydrophone far from the seabed, it is straightforward to estimate propagation loss (PL) and convert sound pressure level (SPL) into SL using the method codified in the international standard ISO 17208-2 [International Organization for Standardization (ISO), Geneva, Switzerland (2019)]. Estimating PL is more difficult in shallow water because of the way that sound reflects from the seabed such that multiple propagation paths contribute to SPL. Obtaining reproducible SL measurements in shallow water requires straightforward and robust methods to estimate PL. From May to July 2021, a field experiment evaluated different methods of measuring vessel SL in shallow water. The same vessels were measured many times in water depths of 30, 70, and 180 m. In total, 12 079 SL measurements were obtained from 1880 vessel transits and 16 hydrophones, distributed across 3 moored vertical line arrays and 2 moored horizontal line arrays. The experiment confirmed…

Intelligibility measures, which assess the number of words or phonemes a listener correctly transcribes or repeats, are commonly used metrics for speech perception research. While these measures have many benefits for researchers, they also come with a number of limitations. By pointing out the strengths and limitations of this approach, including how it fails to capture aspects of perception such as listening effort, this article argues that the role of intelligibility measures must be reconsidered in fields such as linguistics, communication disorders, and psychology. Recommendations for future work in this area are presented.

Acoustic metamaterials (AMMs) offer innovative solutions for physics and engineering problems, allowing lighter, multiphysics, and sustainable systems. They are usually studied analytically or numerically and then tested on prototypes. For this reason, additive manufacturing (AM) techniques are a popular way of quickly realising AMMs' innovative geometrical designs. However, AM parameters are often standardised without considering the specific issues of each AMM geometrical shape, leading to a possible mismatch between the analytical (or numerical) and experimental results. In this study, a simple AMM-a coiled-up resonator-has been produced with different AM technologies [fused deposition modeling (FDM), stereolithography (SLA), and selective laser melting and materials (polylactic acid, polyethylene terephthalate glycol, resin, flexible resin, and stainless steel). The sound absorption performance of these samples has been measured in two research labs in Italy and compared with the analytical and numerical calculations. This permitted the identification of the best combinations of…

The underwater sound absorption technique in low-frequency and broadband has far-reaching prospects since it is essential for noise reduction of deep-sea operation requirements and evading advanced underwater target detection. Here, we propose an underwater sound-absorbing composite lattice with low-frequency and ultra-broadband characteristics. The composite lattice is constructed by regular spatially stacking cells with different sizes of metallic core spheres. All the core spheres are coated with silicon rubbers, and cells are embedded in the rubber matrix. In the composite lattice stereostructure, the lattice cells convert incident longitudinal waves into transverse waves through multiple local resonance coupling and multiple scattering. The energy is localized and dissipated in the composite lattice. We analyze the relationship among the corresponding absorption spectrums, the displacement clouds, and the resonance modes of lattice cells. Then, we construct a composite lattice and realize low-frequency broadband absorption from 693 to 1106 Hz with absorptance above 0.8.…

The influence of cultural background on the soundscape experience in public spaces has been widely acknowledged. However, most studies have not used standardized protocols for soundscape perception data collection, nor have they gathered large datasets across different regions of the world to investigate possible cultural differences. This study explored the relationships between soundscape descriptors, perceived dominance of sound sources, and overall soundscape qualities and whether these relationships differ across world regions. A database of over 2000 soundscape surveys was collected in situ in outdoor public spaces in Europe and China. Results highlighted differences in how European and Chinese participants perceived the pleasantness and dominance of different sound sources. Specifically, the positive correlation between perceived pleasantness and natural sounds was stronger for European participants. For Chinese participants, vibrant soundscapes were positively correlated with perceived dominance of natural sounds, whereas in Europe, they were associated more with…

Soundscape research on indoor environments is emerging as a topic to be addressed for the design of supportive, healthier, and more comfortable spaces. Only a few studies so far addressed the context of educational buildings, mainly focusing on high schools and universities. This pilot study uses questionnaires based on pictorial scales to investigate the indoor soundscape of classrooms for primary school children (n = 130; 8-10 years old). Perceived loudness and the affective dimensions of pleasantness and arousal were explored. Besides the actual soundscape, the children's ideal soundscape was investigated as well. The results of the study indicate that the most frequent sounds in classrooms are generated by the students themselves (voices, movements) followed by the traffic. The urban context of the school modulates the children's perception when windows are open to ensure natural ventilation. Pleasantness is associated with students' age, perceived loudness, and frequency of children's voices in nearby classrooms. The frequency of hearing indoor sounds (children's voices) and…

Many acoustic studies have been conducted in the San Carlo Theatre of Naples over the centuries. The discovery of valuable acoustic measurements from 1998 led the authors to photograph the architectural and acoustic conditions of the Theatre prior to restoration works in 2008. As the first opera house built in Europe, the San Carlo Theatre has always offered a rich artistic programme, making this historic building synonymous with classical music in Naples. From the great variety of operas, three specific sceneries have been selected to analyse the acoustic response based on different geometries and materials located on stage. Acoustic simulations have been performed based on site measurements, starting from a digital model that reproduces the geometry and absorbing coefficients of the materials existing in the Theatre. Using the recorded impulse response, the monoaural and binaural acoustic parameters have been obtained from the acoustic simulations and thereafter compared among the Elektra, Traviata, and La clemenza di Tito sceneries. The results in terms of reverberation highlight…

Parabolic equations (PEs) are useful for modeling sound propagation in a range-dependent environment. However, this approach entails approximating a leading-order cross-derivative term in the PE square-root operators. Deep operator networks (DeepONets) are designed to approximate operators. In this paper, we train DeepONets to take complex sound pressure and speed of sound at any depth location of interest as inputs and approximate the PE square operator in modeling two-dimensional sound propagation. Once trained, a network can predict the far field for a wide variety of environmental conditions, without needing to approximate the operator or calculate the whole mode trajectory and at a lower computational cost. The original DeepONet learns the operator of a single function. By contrast, the modified version presented here learns multiple-input operators with Fourier features. Using computational and theoretical examples, we demonstrate that DeepONet is efficient for learning complex ocean acoustic physics with good accuracy.

In deep water, multipath time delays or frequency-domain interference periods of the acoustic intensity combined with multipath arrival angles are typically used for source localization. However, depth estimate is hard to achieve for a narrowband source at a remote part of the direct arrival zone as the required bandwidth increases with the source range. In this paper, a passive source localization method with a vertical line array, suitable for both broadband and narrowband sources, is proposed. Based on the variation trends of multipath angles with source range and depth, source localization is achieved by only matching the measured angles of the direct path and surface-reflected path with model-based values of a predefined grid of potential source locations. Considering the angle resolution limited by the array aperture and the presence of coherent multipath, sparse Bayesian learning is used and compared with the conventional beamforming and the minimum-variance distortionless-response beamforming to resolve and estimate the multipath angles. Simulations and experimental data of…

Conventional double differential phase-shift keying modulation amplifies the phase noise and performs poorly under the time-varying direct-sequence spread-spectrum (DSSS) communication system. Therefore, the authors propose an iterative reception for DSSS communication in time-varying underwater acoustic channels. First, bit-interleaved coded modulation with iterative decoding integrated with multi-symbol differential detection is used. Second, this paper uses cross correlation method to estimate and track the Doppler shift of each symbol. Based on Doppler estimates, a dynamic linear prediction model is proposed to estimate and track the channel phase variation. Third, an algorithm for adaptive selection of reference signals is utilized to recover the magnitude attenuation of correlation peaks. Numerical simulation results demonstrate that the proposed reception achieves around 9 dB gain compared to conventional differential decision reception under constant acceleration of 0.14 m/s2. During the acoustic communication experiment in Songhua Lake, the proposed reception was tested by…

Accurately reconstructing a three-dimensional (3D) ocean sound speed field (SSF) is essential for various ocean acoustic applications, but the sparsity and uncertainty of sound speed samples across a vast ocean region make it a challenging task. To tackle this challenge, a large body of reconstruction methods has been developed, including spline interpolation, matrix/tensor-based completion, and deep neural networks (DNNs)-based reconstruction. However, a principled analysis of their effectiveness in 3D SSF reconstruction is still lacking. This paper performs a thorough analysis of the reconstruction error and highlights the need for a balanced representation model that integrates expressiveness and conciseness. To meet this requirement, a 3D SSF-tailored tensor DNN is proposed, which uses tensor computations and DNN architectures to achieve remarkable 3D SSF reconstruction. The proposed model not only includes the previous tensor-based SSF representation model as a special case but also has a natural ability to reject noise. The numerical results using the South China Sea 3D SSF…

This paper proposes a deep transfer learning (DTL)-based variable Doppler frequency-hopping binary frequency-shift keying underwater acoustic communication system. The system uses a convolutional neural network (CNN) as the demodulation module of the receiver. This approach directly demodulates the received signal without estimating the Doppler. The DTL first uses the simulated communication signal data to complete the CNN training. It then copies a part of the convolution layers from the pre-trained CNN to the target CNN. After randomly initializing the remaining layers for the target CNN, it is trained by the data samples from the specific communication scenarios. During the training process, the CNN learns the corresponding frequency from each symbol in the selected frequency-hopping group through the Mel-spectrograms. Simulation and experimental data processing results show that the performance of the proposed system is better than conventional systems, especially when the transmitter and receiver of the communication system are in variable speed motion in shallow water acoustic…

A thin-film absorber with tunable acoustic properties over a wideband is designed based on the acoustic metamaterial theory. The thin-film acoustic metamaterial absorber (TFAMA) consists of a frame made of piezoelectric material and several flexible films with attached mass blocks (mass-spring vibration system). Based on the vibration mechanism of the mass-spring vibration system, a cellular model of local resonance form is established, and the material properties of negative effective mass are discussed. Combined with the vibration modal analysis of the coupling of mass block, elastic film, and piezoelectric material, the acoustic characteristics of the TFAMA under alternating voltage excitation are studied by finite element and experimental methods. The simulation and experimental results show that the sound wave can be well absorbed when it is incident on TFAMA to cause the membrane-cavity coupling resonance. By applying an alternating voltage to the TFAMA to excite the mass-spring vibration system to generate local resonance, the absorption of sound waves can be further enhanced…

This paper outlines my research path over three decades while providing a review on the role of fish sounds in mate choice and reproduction. It also intends to provide advice to young scientists and point toward future avenues in this field of research. An overview of studies on different fish model species shows that male mating acoustic signals can inform females and male competitors about their size (dominant frequency, amplitude, and sound pulse rate modulation), body condition (calling activity and sound pulse rate), and readiness to mate (calling rate, number of pulses in a sound). At least in species with parental care, such as toadfishes, gobies, and pomacentrids, calling activity seems to be the main driver of reproductive success. Playback experiments ran on a restricted number of species consistently revealed that females prefer vocal to silent males and select for higher calling rates. This personal synthesis concludes with the suggestion to increase knowledge on fish mating signals, especially considering the emerging use of fish sounds to monitor aquatic environments…

It is hypothesized that sound quality metrics, particularly loudness, sharpness, tonality, impulsiveness, fluctuation strength, and roughness, could all be possible indicators of the reported annoyance to helicopter noise. To test this hypothesis, a psychoacoustic test was conducted in which subjects rated their annoyance levels to synthesized helicopter sounds. After controlling for loudness, a previous analysis using linear regression identified sharpness and tonality as important factors in predicting annoyance, followed by fluctuation strength. The current work focuses on multilevel regression techniques in which the regression slopes and intercepts are assumed to take on normal distributions across subjects. The importance of each metric is evaluated, and the variation of regression parameters among subjects is evaluated using simple models. Then more complete models are investigated, which include the combination of selected metrics and subject-specific effects. While the conclusions from linear regression analysis are affirmed by multilevel analysis, other important effects…

Dispersion curves of elastic waveguides exhibit points where the group velocity vanishes while the wavenumber remains finite. These are the so-called zero-group-velocity (ZGV) points. As the elastodynamic energy at these points remains confined close to the source, they are of practical interest for nondestructive testing and quantitative characterization of structures. These applications rely on the correct prediction of the ZGV points. In this contribution, we first model the ZGV resonances in anisotropic plates based on the appearance of an additional modal solution. The resulting governing equation is interpreted as a two-parameter eigenvalue problem. Subsequently, we present three complementary numerical procedures capable of computing ZGV points in arbitrary nondissipative elastic waveguides in the conventional sense that their axial power flux vanishes. The first method is globally convergent and guarantees to find all ZGV points but can only be used for small problems. The second procedure is a very fast, generally-applicable, Newton-type iteration that is locally convergent…

We report in this study how ocean-bottom seismometers (OBS) can be used as passive sonars to automatically detect, localize, and track moving acoustic sources at the ocean surface. We developed single-station methods based on direction of arrival and on multi-path interference measurements capable of handling continuous erratic signals emitted by ships. Based on a Bayesian mathematical framework, we developed an azimuthal detector and a radial detector and combined them into a fully automatic tracker. We tested the developed algorithm on seismic and hydroacoustic data recorded in the Indian Ocean by an OBS deployed at 4300 m depth, 200 km west of La Réunion Island. We quantified the performances using archives of commercial-vessel trajectories in the area provided by the Automatic Identification System. Detectors demonstrate capabilities in the detection range up to 100 km from the OBS with azimuthal accuracies of a few degrees and with distance accuracies of a few hundred of meters. We expect the method to be easily transposed to any other kind of sources (such as marine mammals).

Soundscape studies typically attempt to capture the perception and understanding of sonic environments by surveying users. However, for long-term monitoring or assessing interventions, sound-signal-based approaches are required. To this end, most previous research focused on psycho-acoustic quantities or automatic sound recognition. Few attempts were made to include appraisal (e.g., in circumplex frameworks). This paper proposes an artificial intelligence (AI)-based dual-branch convolutional neural network with cross-attention-based fusion (DCNN-CaF) to analyze automatic soundscape characterization, including sound recognition and appraisal. Using the DeLTA dataset containing human-annotated sound source labels and perceived annoyance, the DCNN-CaF is proposed to perform sound source classification (SSC) and human-perceived annoyance rating prediction (ARP). Experimental findings indicate that (1) the proposed DCNN-CaF using loudness and Mel features outperforms the DCNN-CaF using only one of them. (2) The proposed DCNN-CaF with cross-attention fusion outperforms other typical…

Mice communicate through audible vocalizations, which are within the human hearing range, and ultrasonic vocalizations (USVs), which are above the upper limit of human hearing. USVs are produced by rodents in social contexts including pup separation, territorial, and courting assays. Like birdsong, an established model for human speech, USVs in mice have been used as a model for understanding human communication. Their utility as a model of social communication is illustrated in neurodevelopmental conditions with a genetic basis, like autism spectrum disorders and Rett syndrome. As mice do not exhibit clear visual cues when they vocalize, the source of vocalization is often assumed. Therefore, there is potential to better discern the true vocal contribution of individual mice if the upper limit of human hearing were to be extended. Currently, there are efforts to increase the precision of sound-localizing technology, which will develop our understanding of communication in mice and other animal models.

Sound waves can be used to carry out underwater activities. Rapidly and accurately simulating sound propagation is the basis for underwater detection. The wide-angle parabolic model has a good computational speed and accuracy and is currently the main numerical model for mid- and low-frequency sound propagation. The classical wide-angle parabolic equation model is discretized by the finite difference method and a low-order difference scheme is generally adopted. In this paper, a wide-angle parabolic equation model based on a spectral method is proposed. The depth operators of each layer are discretized via the Chebyshev spectral method and then assembled into a global matrix for the forward step. Lateral inhomogeneity is addressed by updating the global depth matrix while stepping forward. In the proposed spectral algorithm, both soft and hard seabeds can be accurately simulated by imposing boundary conditions, and the perfectly matched layer technique is used to truncate the unbounded acoustic half-space. Several representative numerical experiments prove the accuracy and…

Roman theatres have always been the subject of research that takes into account not only acoustics, but also archaeological and architectural aspects. It is difficult to draw the boundary line between these disciplines since the interrelation between the different types of expertise is necessary to allow a good production of contemporary architecture in a specific context, such as a Roman theatre. This paper deals with the acoustic analysis of three specific scenarios in the context of the Roman theatre of Pompeii. The reconstruction of the original form, which represents the first scenario, is based on the recent archaeological findings of the ancient city, which was buried for almost two millennia after the eruption of the volcano Vesuvius. The second scenario envisions a future acoustic shell in the form of a mushroom, where the ceiling is the continuation of the vertical surface. The third scenario consists of a parametric design of a shell, representing a modern style velarium; as the curve creates focusing effects, the addition of reflective panels directs the sound evenly to…

Means of characterizing acoustic signals of fricatives with a few parameters have long been sought. When Forrest, Weismer, Milenkovic, and Dougall [(1988) J. Acoust. Soc. Am. 84, 115-123] described their system of treating spectra as probability density functions and computing the first four spectral moments, others quickly adopted their clearly described method, although it did not distinguish /f/ and /θ/. Various problems with their method are described, including the lack of spectral averaging, the necessity of normalizing the amplitude, and correlation between pairs of moments. Even when these issues are rectified by alternative methods, the fact remains that moments are not ideal descriptors because they can only describe departures from the shape of a normal Gaussian distribution. Fricative spectra, particularly of non-sibilants, are often quite dissimilar in shape from Gaussians. Furthermore, shape descriptors do not lend themselves to direct inferences about the production variables that caused the acoustic effects. Here, alternative parameters are defined, it is shown how…

An auditory model has been developed with a time-varying, gain-control signal based on the physiology of the efferent system and subcortical neural pathways. The medial olivocochlear (MOC) efferent stage of the model receives excitatory projections from fluctuation-sensitive model neurons of the inferior colliculus (IC) and wide-dynamic-range model neurons of the cochlear nucleus. The response of the model MOC stage dynamically controls cochlear gain via simulated outer hair cells. In response to amplitude-modulated (AM) noise, firing rates of most IC neurons with band-enhanced modulation transfer functions in awake rabbits increase over a time course consistent with the dynamics of the MOC efferent feedback. These changes in the rates of IC neurons in awake rabbits were employed to adjust the parameters of the efferent stage of the proposed model. Responses of the proposed model to AM noise were able to simulate the increasing IC rate over time, whereas the model without the efferent system did not show this trend. The proposed model with efferent gain control provides a powerful…

Anthropogenic noise is globally increasing in aquatic ecosystems, and there is concern that it may have adverse consequences in many fish species, yet the effects of noise in field settings are not well understood. Concern over the applicability of laboratory-conducted bioacoustic experiments has led to a call for, and a recent increase in, field-based studies, but the results have been mixed, perhaps due to the wide variety of techniques used and species studied. Previous reviews have explored the behavioral, physiological, and/or anatomical costs of fish exposed to anthropogenic noise, but few, if any, have focused on the field techniques and sound sources themselves. This review, therefore, aims to summarize, quantify, and interpret field-based literature, highlight novel approaches, and provide recommendations for future research into the effects of noise on fish.

This paper presents a deep learning-based approach for the spatiotemporal reconstruction of sound fields using generative adversarial networks. The method utilises a plane wave basis and learns the underlying statistical distributions of pressure in rooms to accurately reconstruct sound fields from a limited number of measurements. The performance of the method is evaluated using two established datasets and compared to state-of-the-art methods. The results show that the model is able to achieve an improved reconstruction performance in terms of accuracy and energy retention, particularly in the high-frequency range and when extrapolating beyond the measurement region. Furthermore, the proposed method can handle a varying number of measurement positions and configurations without sacrificing performance. The results suggest that this approach provides a promising approach to sound field reconstruction using generative models that allow for a physically informed prior to acoustics problems.

Recently, full-waveform inversion (FWI) has become a promising tool for ultrasound computed tomography (USCT). However, as a computationally intensive technique, FWI suffers from computational burden, especially in conventional time-domain full-waveform inversion (TDFWI). On the contrary, frequency-domain full-waveform inversion (FDFWI) provides a relatively high computational efficiency as the propagation of discrete frequencies is much cheaper than full time-domain modeling. FDFWI has already been applied in soft tissue imaging, such as breast, but for the musculoskeletal model with high impedance contrast between hard and soft tissues, there is still a lack of an effective source estimation method. In this paper, a water-referenced data calibration method is proposed to address the source estimation challenge in the presence of bones, which achieves consistency between the measured and simulated data before the FDFWI procedure. To avoid the cycle-skipping local minimum effect and facilitate the algorithm convergence, a starting frequency criterion for musculoskeletal FDFWI is…

Large Eddy Simulation (LES) and Ffowcs Williams-Hawkings acoustic analogy are performed to study the effect of trailing-edge blowing on airfoil self-noise. Simulations were conducted using a National Advisory Committee for Aeronautics 0012 airfoil at zero angle of attack and a chord-based Reynolds number of 4 × 10 5. The aerodynamic and aeroacoustic characteristics of the baseline airfoil were thoroughly verified by comparison with previous numerical and experimental data. The noise reduction effects of continuous and local blowing with different blowing ratios and blowing momentum coefficients were compared. A maximum noise reduction of 20 dB was achieved via trailing-edge blowing and the noise reduction mechanisms of the two blowing methods were discussed. The LES results show a pair of recirculation bubbles in the airfoil wake which are suppressed by trailing-edge blowing. As the blowing vortices convect into the wake, they stretch and stabilize the shear flows from airfoil surfaces. Instantaneous vorticity and root mean square velocity fluctuations are also weakened. There is a…

Environmental noise has long been considered one of the unwelcome aspects of urban life at home. An increasing number of scholars have studied improving indoor acoustic comfort by using the soundscape approach. However, much uncertainty still exists about the relationship between the audio-visual environment and indoor soundscape perception. The current study investigates the interaction effects of traffic sound and window views on indoor soundscape perceptions in residential contexts. Thirty-two participants were presented with 51 scenarios (a combination of 17 window views and three aural stimuli) and requested to assess their soundscape perceptions in a VR experiment. Results showed that traffic noise could moderate the impact of nature, road, and building views on pleasantness, while it can also moderate the effect of water sound and road view on eventfulness. In particular, natural window views were found not to lead to a more pleasant indoor soundscape necessarily; natural window views even decrease the pleasantness of indoor soundscape in the case of heavy traffic noise…

A publication by McCargar and Zurk [J. Acoust. Soc. Am. 133(4), EL320-EL325 (2013)] introduced a passive source depth estimation method for a moving tonal source with a vertical line array (VLA), utilizing the depth-dependent modulation in the arrival angle domain caused by the interference between the direct and surface-reflected acoustic arrivals. Under the isovelocity approximation, this method can estimate the depth of sources at close ranges, but the depth estimation error will increase with the increase in source range, as the impact of the sound speed profile on sound propagation is ignored. This paper presents a theoretical formula for calculating the modeled interference structure in the arrival angle domain with the knowledge of the sound speed profile. By matching the measured interference structure obtained from the beamforming of the acoustic data received by the VLA with the modeled structure under different assumed source depths, the tonal source depth estimation is achieved, even for sources at the remote part of the direct arrival zone. The performance of this…

Guided ultrasonic waves are used for the inspection of multilayered composite aerospace structures. Calculating the corresponding dispersion diagrams is challenging for thick-walled composites with more than 100 layers, such as in modern rocket booster pressure vessels. The Dispersion Calculator (DC) is an open source software for calculating such dispersion diagrams and mode shapes of guided waves. Attenuation caused by viscoelasticity and fluid-loading makes the dispersion curve tracing much more difficult than in the nonattenuated case because the modal solutions are sought in the complex wavenumber plane. The tracing problem is mastered by a reliable algorithm. Whereas leaky Lamb and Scholte waves in coupled and decoupled cases are modeled using the stiffness matrix method, shear horizontal (SH) waves are traced using the transfer matrix method without facing the numerical instability. Through implementation of mode family specific dispersion equations in both matrix techniques for nonattenuated and attenuated cases, symmetric, antisymmetric, and nonsymmetric leaky Lamb,…

Recent advances in sonic black hole (SBH) provide new opportunities for controlling sound waves and designing wave manipulation devices. SBH is a device that consists of partitions with gradually decreasing inner radii inserted into an acoustic duct. Several studies have reported that SBH can achieve a broadband sound absorption coefficient close to 1, avoiding the issue of alternating high and low absorption coefficients observed in traditional sound absorbers. However, the fundamental mechanisms and principles behind this behavior are not yet fully understood. This study aims to investigate the detailed sound absorption mechanisms of SBH, including the progressive slow-sound effect and the critical coupling condition that leads to broadband sound absorption. To achieve this goal, an analytical model based on the effective medium approach is developed to investigate the layer-by-layer retardation in sound propagation. The sound absorption coefficient is then determined based on the surface impedance calculation. The effective medium analysis reveals that SBH enables a unique…

Muddy sediments cover significant portions of continental shelves, but their physical properties remain poorly understood compared to sandy sediments. This paper presents a generally applicable model for sediment-column structure and variability on the New England Mud Patch (NEMP), based on trans-dimensional Bayesian inversion of wide-angle, broadband reflection-coefficient data in this work and in two previously published reflection-coefficient inversions at different sites on the NEMP. The data considered here include higher frequencies and larger bandwidth and cover lower reflection grazing angles than the previous studies, hence, resulting in geoacoustic profiles with significantly better structural resolution and smaller uncertainties. The general sediment-column structure model includes an upper mud layer in which sediment properties change slightly with depth due to near-surface processes, an intermediate mud layer with nearly uniform properties, and a geoacoustic transition layer where properties change rapidly with depth (porosity decreases and sound speed, density, and…

Localization and tracking of marine animals can reveal key insights into their behaviors underwater that would otherwise remain unexplored. A promising nonintrusive approach to obtaining location information of marine animals is to process their bioacoustic signals, which are passively recorded using multiple hydrophones. In this paper, a data processing chain that automatically detects and tracks multiple odontocetes (toothed whales) in three dimensions (3-D) from their echolocation clicks recorded with volumetric hydrophone arrays is proposed. First, the time-difference-of-arrival (TDOA) measurements are extracted with a generalized cross-correlation that whitens the received acoustic signals based on the instrument noise statistics. Subsequently, odontocetes are tracked in the TDOA domain using a graph-based multi-target tracking (MTT) method to reject false TDOA measurements and close gaps of missed detections. The resulting TDOA estimates are then used by another graph-based MTT stage that estimates odontocete tracks in 3-D. The tracking capability of the proposed data…

Target direction-of-arrival (DOA) estimation is often difficult in the presence of strong interference-especially when the target DOA is very close to the interference DOA-since the strong interference signal can mask the weak target signal and make the DOA estimation hard. To address this problem, an efficient sparse method for DOA estimation is proposed in this paper, in which the effect of strong interference on the target DOA estimation is significantly reduced. An on-grid version of the grid evolution technique is then developed to nonuniformly refine the grid, thereby reducing the computational complexity while retaining reasonable accuracy. Numerical simulations and experimental results demonstrate that, compared to state-of-art methods, the proposed method achieves higher efficiency and better DOA estimation performance in the presence of strong interference.

Since their introduction to sociolinguistics by Hay, Warren, and Drager [(2006). J. Phon. (Modell. Sociophon. Var.) 34(4), 458-484], Pillai scores have become a standard metric for quantifying vowel overlap. However, there is no established threshold value for determining whether two vowels are merged, leading to conflicting ad hoc measures. Furthermore, as a parametric measure, Pillai scores are sensitive to sample size. In this paper, we use generated data from a simulated pair of underlyingly merged vowels to demonstrate (1) larger sample sizes yield reliably more accurate Pillai scores, (2) unequal group sizes across the two vowel classes are irrelevant in the calculation of Pillai scores, and (3) it takes many more data than many sociolinguistic studies typically analyze to return a reliably low Pillai score for underlyingly merged data. We provide some recommendations for maximizing reliability in the use of Pillai scores and provide a formula to assist researchers in determining a reasonable threshold to use as an indicator of merged status given their sample size. We…

Recent studies have found that envelope following responses (EFRs) are a marker of age-related and noise- or ototoxic-induced cochlear synaptopathy (CS) in research animals. Whereas the cochlear injury can be well controlled in animal research studies, humans may have an unknown mixture of sensorineural hearing loss [SNHL; e.g., inner- or outer-hair-cell (OHC) damage or CS] that cannot be teased apart in a standard hearing evaluation. Hence, a direct translation of EFR markers of CS to a differential CS diagnosis in humans might be compromised by the influence of SNHL subtypes and differences in recording modalities between research animals and humans. To quantify the robustness of EFR markers for use in human studies, this study investigates the impact of methodological considerations related to electrode montage, stimulus characteristics, and presentation, as well as analysis method on human-recorded EFR markers. The main focus is on rectangularly modulated pure-tone stimuli to evoke the EFR based on a recent auditory modelling study that showed that the EFR was least affected by…

The goal of this computational study is to quantify global effects of vocal tract constriction at various locations (false vocal folds, aryepiglottic folds, pharynx, oral cavity, and lips) on the voice source across a large range of vocal fold conditions. The results showed that while inclusion of a uniform vocal tract had notable effects on the voice source, further constricting the vocal tract only had small effects except for conditions of extreme constriction, at which constrictions at any location along the vocal tract decreased the mean and peak-to-peak amplitude of the glottal flow waveform. Although narrowing in the epilarynx increased the normalized maximum flow declination rate, vocal tract constriction in general slightly reduced the source strength and high-frequency harmonic production at the glottis, except for a limited set of vocal fold conditions (e.g., soft, long vocal folds subject to relatively high pressure). This suggests that simultaneous laryngeal and vocal tract adjustments are required to maximize source-filter interaction. While vocal tract adjustments are…

Previously proposed methods for estimating acoustic parameters from reverberant, noisy speech signals exhibit insufficient performance under changing acoustic conditions. A data-centric approach is proposed to overcome the limiting assumption of fixed source-receiver transmission paths. The obtained solution significantly enlarges the scope of potential applications for such estimators. The joint estimation of reverberation time RT60 and clarity index C50 in multiple frequency bands is studied with a focus on dynamic acoustic environments. Three different convolutional recurrent neural network architectures are considered to solve the tasks of single-band, multi-band, and multi-task parameter estimation. A comprehensive performance evaluation is provided that highlights the benefits of the proposed approach.

Gaussian processes (GPs) can capture correlation of the acoustic field at different depths in the ocean. This feature is exploited in this work for pre-processing acoustic data before these are employed for source localization and environmental inversion using matched field inversion (MFI) in an underwater waveguide. Via the application of GPs, the data are denoised and interpolated, generating densely populated acoustic fields at virtual arrays, which are then used as data in MFI. Replicas are also computed at the virtual receivers at which field predictions are made. The correlations among field measurements at distinct spatial points are manifested through the selection of kernel functions. These rely on hyperparameters, that are estimated through a maximum likelihood process for optimal denoising and interpolation. The approach, employing Gaussian and Matérn kernels, is tested on synthetic and real data with both an exhaustive search and genetic algorithms and is found to be superior to conventional beamformer MFI. It is also shown that the Matérn kernel, providing more degrees…

The development of methods to safely rewarm large cryopreserved biological samples remains a barrier to the widespread adoption of cryopreservation. Here, experiments and simulations were performed to demonstrate that ultrasound can increase rewarming rates relative to thermal conduction alone. An ultrasonic rewarming setup based on a custom 444 kHz tubular piezoelectric transducer was designed, characterized, and tested with 2 ml cryovials filled with frozen ground beef. Rewarming rates were characterized in the -20 °C to 5 °C range. Thermal conduction-based rewarming was compared to thermal conduction plus ultrasonic rewarming, demonstrating a tenfold increase in rewarming rate when ultrasound was applied. The maximum recorded rewarming rate with ultrasound was 57° C/min, approximately 2.5 times faster than with thermal conduction alone. Coupled acoustic and thermal simulations were developed and showed good agreement with the heating rates demonstrated experimentally and were also used to demonstrate spatial heating distributions with small (<3° C) temperature differentials…

Recent studies on diffusion adaptation for distributed active noise control (DANC) systems have attracted significant research interest due to their balance between computational burden and stability compared to conventional centralized and decentralized adaptation schemes. The conventional multitask diffusion FxLMS algorithm assumes that the converged solutions of all control filters are consistent to each other, which is unrealistic in practice hence results in inferior performance in noise reduction. An augmented diffusion FxLMS algorithm has been proposed to overcome this problem, which adopts a neighborhood-wide adaptation and node-based combination approach to mitigate the bias in the converged solution of the multitask diffusion algorithms. However, the improvement comes at the expense of a higher computational burden and communication cost. All existing DANC systems, including the multitask and augmented diffusion algorithms, assume one-way communication between nodes. By contrast, this paper proposes a bidirectional communication scheme for the augmented diffusion algorithm…

Substrate-borne communication via mechanical waves is widespread throughout the animal kingdom but has not been intensively studied in fishes. Families such as the salmonids and sculpins have been documented to produce vibratory signals. However, it is likely that fish taxa on or close to the substrate that produce acoustic signals will also have a vibratory component to their signal due to their proximity to substrates and energy transfer between media. Fishes present an intriguing opportunity to study vibrational communication, particularly in the context of signal production and detection, detection range, and how vibratory signals may complement or replace acoustic signals. It is highly likely that the vibrational landscape, the vibroscape, is an important component of their sensory world, which certainly includes and overlaps with the soundscape. With the wide range of anthropogenic activities modifying underwater substrates, vibrational noise presents similar risks as acoustic noise pollution for fishes that depend on vibrational communication. However, in order to understand…

The radiation characteristics of rotor-beam interaction noise are studied experimentally for low Reynolds number small-scale rotors in interaction with beams of different shapes, sizes, and downstream positions. The number of blades ranges from two to four. For the two-bladed rotor, the presence of the beam has no effect on the mean aerodynamic performance. Moreover, the blade passing frequency (BPF) and the high frequency broadband noise (BBN) appear not to be affected by the presence of the beam. On the contrary, the magnitude of the 2×BPF-25×BPF harmonics increases up to 30 dB compared to the case without beam, with an envelope consisting of two humps: one centered around 5×BPF and another around 20×BPF-25×BPF. For the first hump, a dipole-like pattern with minimal amplitude aligned with the beam can be observed, whereas another dipole-like pattern is observed for the higher frequency hump, but with a minimal amplitude over all the rotor disk plane. Compared to the two-bladed rotor, the presence of the beam has an effect on the mean aerodynamic performance of the three- and…

Estimation of modal wavenumbers is important for inference of geoacoustic properties and data-driven matched field processing in shallow water waveguides. This paper introduces a deep neural network called combining physical informed neural network (CPINN) for modal wavenumber estimation using a vertical linear array (VLA). Note that the sound field recorded by a VLA can be expressed as a linear superposition of finite modal depth functions, and the differential equations satisfied by the modal depth functions are related to the corresponding modal wavenumbers. CPINN can estimate the modal wavenumbers by introducing the proxies of the modal depth functions and constraining them to satisfy the corresponding differential equations. The performance of the CPINN is evaluated by simulated data in a noisy shallow water environment. Numerical results show that, when compared with the previous methods, CPINN does not need to know the exact horizontal distance between the sound source and the VLA. Moreover, CPINN can estimate the modal wavenumbers at the VLA position in the case where the…