The 50 most-cited articles in The Journal of the Acoustical Society of America, 2022

This article is a survey of deep learning methods for single and multiple sound source localization, with a focus on sound source localization in indoor environments, where reverberation and diffuse noise are present. We provide an extensive topography of the neural network-based sound source localization literature in this context, organized according to the neural network architecture, the type of input features, the output strategy (classification or regression), the types of data used for model training and evaluation, and the model training strategy. Tables summarizing the literature survey are provided at the end of the paper, allowing a quick search of methods with a given set of target characteristics.

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston operating at 500 kHz), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular spectrum method, pseudospectral method, boundary-element method, and spectral-element…

Categorical perception (CP) is likely the single finding from speech perception with the biggest impact on cognitive science. However, within speech perception, it is widely known to be an artifact of task demands. CP is empirically defined as a relationship between phoneme identification and discrimination. As discrimination tasks do not appear to require categorization, this was thought to support the claim that listeners perceive speech solely in terms of linguistic categories. However, 50 years of work using discrimination tasks, priming, the visual world paradigm, and event related potentials has rejected the strongest forms of CP and provided little strong evidence for any form of it. This paper reviews the origins and impact of this scientific meme and the work challenging it. It discusses work showing that the encoding of auditory input is largely continuous, not categorical, and describes the modern theoretical synthesis in which listeners preserve fine-grained detail to enable more flexible processing. This synthesis is fundamentally inconsistent with CP. This leads to a…

There are substantial knowledge gaps regarding both the bioacoustics and the responses of animals to sounds associated with pre-construction, construction, and operations of offshore wind (OSW) energy development. A workgroup of the 2020 State of the Science Workshop on Wildlife and Offshore Wind Energy identified studies for the next five years to help stakeholders better understand potential cumulative biological impacts of sound and vibration to fishes and aquatic invertebrates as the OSW industry develops. The workgroup identified seven short-term priorities that include a mix of primary research and coordination efforts. Key research needs include the examination of animal displacement and other behavioral responses to sound, as well as hearing sensitivity studies related to particle motion, substrate vibration, and sound pressure. Other needs include: identification of priority taxa on which to focus research; standardization of methods; development of a long-term highly instrumented field site; and examination of sound mitigation options for fishes and aquatic invertebrates.…

In this paper, an acoustic metamaterial, composed of rough neck embedded Helmholtz resonators, is proposed to achieve perfect sound absorption in the low-frequency range. The wall shape of the embedded neck in Helmholtz resonators can be adjusted to improve the low-frequency sound absorption performance of acoustic metamaterials. As a concern, a full-rough neck embedded Helmholtz resonator (FR-NEHR) is designed, which achieves perfect sound absorption (α>0.999) with a deep subwavelength thickness ( λ/44) at 150 Hz. A theoretical model is developed to predict the performance of the FR-NEHR, which is validated against the experimental measurement and numerical simulation. The results show that for the rough embedded neck, when the axial and circumferential roughness of the neck exist, the sound energy dissipation increases not only in the neck but also in the air cavity. As a result, the acoustic absorption peak value of the FR-NEHR increases 20.2%, and the peak position shifts 20.2% to a lower frequency. This work extends Maa's 50-year-old sound absorption theory from smooth channels…

Audiometric testing in research and in clinical settings rarely considers frequencies above 8 kHz. However, the sensitivity of young healthy ears extends to 20 kHz, and there is increasing evidence that testing in the extended high-frequency (EHF) region, above 8 kHz, might provide valuable additional information. Basal (EHF) cochlear regions are especially sensitive to the effects of aging, disease, ototoxic drugs, and possibly noise exposure. Hence, EHF loss may be an early warning of damage, useful for diagnosis and for monitoring hearing health. In certain environments, speech perception may rely on EHF information, and there is evidence for an association between EHF loss and speech perception difficulties, although this may not be causal: EHF loss may instead be a marker for sub-clinical damage at lower frequencies. If there is a causal relation, then amplification in the EHF range may be beneficial if the technical difficulties can be overcome. EHF audiometry in the clinic presents with no particular difficulty, the biggest obstacle being lack of specialist equipment.…

The radiated noise from ships is of great significance to target recognition, and several deep learning methods have been developed for the recognition of underwater acoustic signals. Previous studies have focused on single-target recognition, with relatively few reports on multitarget recognition. This paper proposes a deep learning-based single-channel multitarget underwater acoustic signal recognition method for an unknown number of targets in the specified category. The proposed method allows the two subproblems of recognizing the unique class and duplicate categories of multiple targets to be solved. These two tasks are essentially multilabel binary classification and multilabel multiple value classification, respectively. In this paper, we describe the use of real-valued and complex-valued ResNet and DenseNet convolutional networks to recognize synthetic mixed multitarget signals, which was superimposed from individual target signals. We compare the performance of various features, including the original audio signal, complex-valued short-time Fourier transform (STFT)…

The acoustic black hole (ABH) effect in waveguides is studied using frequency-domain finite element simulations of a cylindrical waveguide with an embedded ABH termination composed of retarding rings. This design is adopted from an experimental study in the literature, which surprisingly showed, contrary to the structural counterpart, that the addition of damping material to the end of the waveguide does not significantly reduce the reflection coefficient any further. To investigate this unexpected behavior, we model different damping mechanisms involved in the attenuation of sound waves in this setup. A sequence of computed pressure distributions indicates occurrences of frequency-dependent resonances in the device. The axial position of the cavity where the resonance occurs can be predicted by a more elaborate wall admittance model than the one that was initially used to study and design ABHs. The results of our simulations show that at higher frequencies, the visco-thermal losses and the damping material added to the end of the setup do not contribute significantly to the…

The aviation sector is rapidly evolving with more electric propulsion systems and a variety of new technologies of vertical take-off and landing manned and unmanned aerial vehicles. Community noise impact is one of the main barriers for the wider adoption of these new vehicles. Within the framework of a perception-driven engineering approach, this paper investigates the relationship between sound quality and first order physical parameters in rotor systems to aid design. Three case studies are considered: (i) contra-rotating versus single rotor systems, (ii) varying blade diameter and thrust in both contra-rotating and single rotor systems, and (iii) varying rotor-rotor axial spacing in contra-rotating systems. The outcomes of a listening experiment, where participants assessed a series of sound stimuli with varying design parameters, allow a better understanding of the annoyance induced by rotor noise. Further to this, a psychoacoustic annoyance model optimised for rotor noise has been formulated. The model includes a novel psychoacoustic function to account for the perceptual…

Structural failure caused by corrosion of the reinforcing steel in concrete structures is quite common. In most cases, corrosion cracks appear on the surface at a late stage, leaving inadequate time for taking any measures. This paper investigates the detection of corrosion damage in reinforced concrete elements by using nonlinear ultrasonic (NLU) techniques. Various linear ultrasonic and NLU techniques were adopted to identify the most sensitive technique and ultrasonic parameters for corrosion induced damage detection at its early stage. It is observed that the linear techniques are not very effective in detecting corrosion induced damage. The sideband peak count-index (or SPC-I), a relatively new and promising technique, has been found to be an excellent indicator for the detection of corrosion induced damage initiation. However, its efficacy for detecting corrosion induced damage has not yet been reported. The present study shows that the SPC-I-based NLU technique outperforms (with the highest sensitivity) all other NLU techniques for detecting the onset of corrosion in steel…

Research on speech categorization and phoneme recognition has relied heavily on tasks in which participants listen to stimuli from a speech continuum and are asked to either classify each stimulus (identification) or discriminate between them (discrimination). Such tasks rest on assumptions about how perception maps onto discrete responses that have not been thoroughly investigated. Here, we identify critical challenges in the link between these tasks and theories of speech categorization. In particular, we show that patterns that have traditionally been linked to categorical perception could arise despite continuous underlying perception and that patterns that run counter to categorical perception could arise despite underlying categorical perception. We describe an alternative measure of speech perception using a visual analog scale that better differentiates between processes at play in speech categorization, and we review some recent findings that show how this task can be used to better inform our theories.

Although it is clear that sighted listeners use both auditory and visual cues during speech perception, the manner in which multisensory information is combined is a matter of debate. One approach to measuring multisensory integration is to use variants of the McGurk illusion, in which discrepant auditory and visual cues produce auditory percepts that differ from those based on unimodal input. Not all listeners show the same degree of susceptibility to the McGurk illusion, and these individual differences are frequently used as a measure of audiovisual integration ability. However, despite their popularity, we join the voices of others in the field to argue that McGurk tasks are ill-suited for studying real-life multisensory speech perception: McGurk stimuli are often based on isolated syllables (which are rare in conversations) and necessarily rely on audiovisual incongruence that does not occur naturally. Furthermore, recent data show that susceptibility to McGurk tasks does not correlate with performance during natural audiovisual speech perception. Although the McGurk effect is…

Underwater acoustic target recognition is an intractable task due to the complex acoustic source characteristics and sound propagation patterns. Limited by insufficient data and narrow information perspective, recognition models based on deep learning seem far from satisfactory in practical underwater scenarios. Although underwater acoustic signals are severely influenced by distance, channel depth, or other factors, annotations of relevant information are often nonuniform, incomplete, and hard to use. In this work, the proposal is to implement underwater acoustic recognition based on templates made up of rich relevant information (UART). The templates are designed to integrate relevant information from different perspectives into descriptive natural language. UART adopts an audio-spectrogram-text trimodal contrastive learning framework, which endows UART with the ability to guide the learning of acoustic representations by descriptive natural language. These experiments reveal that UART has better recognition capability and generalization performance than traditional paradigms.…

Underwater noise transmission in the ocean environment is a complex physical phenomenon involving not only widely varying physical parameters and dynamical scales but also uncertainties in the ocean parameters. It is challenging to construct generalized physical models that can predict transmission loss in a broad range of situations. In this regard, we propose a convolutional recurrent autoencoder network (CRAN) architecture, which is a data-driven deep learning model for learning far-field acoustic propagation. Being data-driven, the CRAN model relies only on the quality of the data and is agnostic to how the data are obtained. The CRAN model can learn a reduced-dimensional representation of physical data and can predict the far-field acoustic signal transmission loss distribution in the ocean environment. We demonstrate the ability of the CRAN model to learn far-field transmission loss distribution in a two-dimensional ocean domain with depth-dependent sources. Results show that the CRAN can learn the essential physical elements of acoustic signal transmission loss generated due…

In 1971, the U.S. National Aeronautics and Space Administration (NASA) published a seminal report-NASA SP-8072-which compiled the results of the early supersonic jet noise studies and provided methods to calculate the noise produced from launch vehicles. Fifty years later and despite known limitations, SP-8072 remains the foundation for much of the launch vehicle noise modeling today. This article reviews what has been learned about the physics of noise generation and radiation from free and impinging rocket plumes since the completion of SP-8072. State-of-the-art methods for the mitigation of launch vehicle noise are also reviewed. A discussion of launch vehicle noise modeling, from empirical to numerical and including reduced-order models of supersonic jets, points to promising approaches that can describe rocket noise characteristics not captured by SP-8072.

Dynamic elastography, whether based on magnetic resonance, ultrasound, or optical modalities, attempts to reconstruct quantitative maps of the viscoelastic properties of biological tissue, properties that are altered by disease and injury, by noninvasively measuring mechanical wave motion in the tissue. Most reconstruction strategies that have been developed neglect boundary conditions, including quasistatic tensile or compressive loading resulting in a nonzero prestress. Significant prestress is inherent to the functional role of some biological tissues currently being studied using elastography, such as skeletal and cardiac muscle, arterial walls, and the cornea. In the present article, we review how prestress alters both bulk mechanical wave motion and wave motion in one- and two-dimensional waveguides. Key findings are linked to studies on skeletal muscle and the human cornea, as one- and two-dimensional waveguide examples. This study highlights the underappreciated combined acoustoelastic and waveguide challenge to elastography. Can elastography truly determine viscoelastic…

An autonomous surface vehicle known as a wave glider, instrumented with a low-power towed hydrophone array and embedded digital signal processor, is demonstrated as a viable low-noise system for the passive acoustic monitoring of marine mammals. Other key design elements include high spatial resolution beamforming on a 32-channel towed hydrophone array, deep array deployment depth, vertical motion isolation, and bandwidth-efficient real-time acoustic data transmission. Using at-sea data collected during a simultaneous deployment of three wave glider-based acoustic detection systems near Stellwagen Bank National Marine Sanctuary in September 2019, the capability of a low-frequency towed hydrophone array to spatially reject noise and to resolve baleen whale vocalizations from anthropogenic acoustic clutter is demonstrated. In particular, mean measured array gain of 15.3 dB at the aperture design frequency results in a post-beamformer signal-to-noise ratio that significantly exceeds that of a single hydrophone. Further, it is shown that with overlapping detections on multiple…

Marine crustaceans produce broadband sounds that have been mostly characterized in tanks. While tank physical impacts on such signals are documented in the acoustic community, they are overlooked in the bioacoustic literature with limited empirical comparisons. Here, we compared broadband sounds produced at 1 m from spiny lobsters (Panulirus argus) in both tank and in situ conditions. We found significant differences in all sound features (temporal, power, and spectral) between tank and in situ recordings, highlighting that broadband sounds, such as those produced by marine crustaceans, cannot be accurately characterized in tanks. We then explained the three main physical impacts that distort broadband sounds in tanks, respectively known as resonant frequencies, sound reverberation, and low frequency attenuation. Tank resonant frequencies strongly distort the spectral shape of broadband sounds. In the high frequency band (above the tank minimum resonant frequency), reverberation increases sound duration. In the low frequency band (below the tank minimum resonant frequency), low…

This work presents a peri-ultrasound theory based on ordinary state-based peridynamics for modeling elastic waves propagating in three-dimensional (3-D) plate structures and interacting with multiple cracks. A recently developed nonlinear ultrasonic technique called sideband peak count-index (or SPC-I) is adopted for monitoring one or more cracks with thickness values equal to 0 mm (crack-free), 1, 2, and 4 mm. Three separate scenarios-one crack, two cracks, and four cracks in 3-D plate structures-are investigated. These cracks can be classified as thin and thick cracks depending on the horizon size, which is mentioned in peri-ultrasound theory. Computed results for all three cases show larger SPC-I values for thin cracks than for thick cracks and the case of no cracks. This observation is in line with the previously reported results in the literature and proves that the state-based peri-ultrasound theory can capture the expected nonlinear response of elastic waves interacting with multiple cracks without changing the cracks' surface locations artificially, and this is always needed…

Acoustics research involving human participants typically takes place in specialized laboratory settings. Listening studies, for example, may present controlled sounds using calibrated transducers in sound-attenuating or anechoic chambers. In contrast, remote testing takes place outside of the laboratory in everyday settings (e.g., participants' homes). Remote testing could provide greater access to participants, larger sample sizes, and opportunities to characterize performance in typical listening environments at the cost of reduced control of environmental conditions, less precise calibration, and inconsistency in attentional state and/or response behaviors from relatively smaller sample sizes and unintuitive experimental tasks. The Acoustical Society of America Technical Committee on Psychological and Physiological Acoustics launched the Task Force on Remote Testing (https://tcppasa.org/remotetesting/) in May 2020 with goals of surveying approaches and platforms available to support remote testing and identifying challenges and considerations for prospective investigators. The…

An interferometric signal processing method for localizing a broadband moving sound source in an oceanic waveguide is proposed and studied theoretically and experimentally. The field of a moving sound source in waveguide creates a stable interference pattern of the intensity distribution (interferogram) I(ω,t) in the frequency-time domain. Sound intensity is accumulated along interference fringes over the observation time. The two-dimensional Fourier transform (2D-FT) is applied to analyze the interferogram I(ω,t). The result of the 2D-FT F(τ,ν) is called the Fourier-hologram (hologram). The mathematical theory of hologram structure F(τ,ν) is developed in the present paper. It is shown that the hologram F(τ,ν) allows the coherent accumulation of sound intensity of the interferogram in a relatively small area focal spots. The presence of these focal spots is the result of interference of acoustic modes with different wave numbers. The main result of this paper is a simple relationship between the focal spots coordinates on the hologram and the source range, velocity, and motion…

This paper proposes an experimental setup for measuring the sound radiation of a quadrotor drone using a hemispherical microphone array. The measured sound field is decomposed into spherical harmonics, which enables the evaluation of the radiation pattern to non-probed positions. Additionally, the measurement setup allows the assessment of noise emission and psychoacoustic metrics at a wide range of angles. The obtained directivity patterns using a third-order spherical harmonic decomposition (SHD) are shown to exhibit low distortion with respect to the original measurements, therefore, validating the SHD as an adequate representation strategy. Furthermore, the noise emissions are evaluated, and the highest noise emission is observed in the 90 ° azimuth direction. The exterior spherical acoustic holography description is employed to evaluate psychoacoustic metrics at arbitrary far-field positions and validated on a reference microphone. The estimated psychoacoustic metrics are closely related to the target metrics, which allows for sound quality analysis at any point external to the…

The mammalian ear embeds a cellular amplifier that boosts sound-induced hydromechanical waves as they propagate along the cochlea. The operation of this amplifier is not fully understood and is difficult to disentangle experimentally. In the prevailing view, cochlear waves are amplified by the piezo-electric action of the outer hair cells (OHCs), whose cycle-by-cycle elongations and contractions inject power into the local motion of the basilar membrane (BM). Concomitant deformations of the opposing (or "top") side of the organ of Corti are assumed to play a minor role and are generally neglected. However, analysis of intracochlear motions obtained using optical coherence tomography calls this prevailing view into question. In particular, the analysis suggests that (i) the net local power transfer from the OHCs to the BM is either negative or highly inefficient; and (ii) vibration of the top side of the organ of Corti plays a primary role in traveling-wave amplification. A phenomenological model derived from these observations manifests realistic cochlear responses and suggests that…

A metamaterial of particular interest for underwater applications is the three-dimensional (3D) anisotropic pentamode (PM), i.e., a structure designed to support a single longitudinal wave with a sound speed that depends on the propagation direction. The present work attempts to experimentally verify anisotropic sound speeds predicted by finite element simulations using additively manufactured anisotropic 3D PM samples made of titanium. The samples were suspended in front of a plane wave source emitting a broadband chirp in a water tank to measure time of flight for wavefronts with and without the PM present. The measurement utilizes a deconvolution method that extracts the band limited impulse response of data gathered by a scanning hydrophone in a plane of constant depth behind the samples. Supporting material takes the form of finite element simulations developed to model the response of a semi-infinite PM medium to an incident normal plane wave. A technique to extract the longitudinal PM wave speed for frequency domain simulations based on Fourier series expansions is given.

Underwater direction-of-arrival (DOA) tracking using a hydrophone array is an important research subject in passive sonar signal processing. In this study, considering that an unknown underwater environment results in uncertain disturbances to the measurements, robust underwater DOA tracking with regard to uncertain environmental disturbances was studied. Because the uniform circular array (UCA) is free from the port and starboard ambiguity problem, a UCA was used to obtain the measurements for a long-time tracking scenario. First, a kinematic model of an underwater target and a measurement model based on the received signal of the UCA were established. Then, a DOA tracking algorithm was derived based on the extended Kalman filter (EKF), whose performance is significantly affected by the accuracy of the measurement noise covariance matrix (MNCM). Finally, considering that uncertain disturbances carry out unstable measurement noise, the modified Sage-Husa algorithm was used to obtain accurate MNCMs during the process of the derived EKF-based DOA tracking algorithm. Thus, a robust DOA…

Underwater source localization by deep neural networks (DNNs) is challenging since training these DNNs generally requires a large amount of experimental data and is computationally expensive. In this paper, label distribution-guided transfer learning (LD-TL) for underwater source localization is proposed, where a one-dimensional convolutional neural network (1D-CNN) is pre-trained with the simulation data generated by an underwater acoustic propagation model and then fine-tuned with a very limited amount of experimental data. In particular, the experimental data for fine-tuning the pre-trained 1D-CNN are labeled with label distribution vectors instead of one-hot encoded vectors. Experimental results show that the performance of underwater source localization with a very limited amount of experimental data is significantly improved by the proposed LD-TL.

Nearfield acoustic holography based on the compressed sensing theory can realize the accurate reconstruction of sound fields with fewer measurement points on the premise that an appropriate sparse basis is obtained. However, for different types of sound sources, the appropriate sparse bases are diverse and should be constructed elaborately. In this paper, a block sparse Bayesian learning (SBL) equivalent source method is proposed for realizing the reconstruction of the sound fields radiated by different types of sources, including the spatially sparse sources, the spatially extended sources, and the mixed ones of the above two, without the elaborate construction of the sparse basis. The proposed method constructs a block sparse equivalent source model and promotes a block sparse solution by imposing a structured prior on the equivalent source model and estimating the posterior of the model by using the SBL, which can achieve the accurate reconstruction of the radiated sound fields of different types of sources simply by adjusting the block size. Numerical simulation and experimental…

Basis function learning is the stepping stone towards effective three-dimensional (3D) sound speed field (SSF) inversion for various acoustic signal processing tasks, including ocean acoustic tomography, underwater target localization/tracking, and underwater communications. Classical basis functions include the empirical orthogonal functions (EOFs), Fourier basis functions, and their combinations. The unsupervised machine learning method, e.g., the K-singular value decomposition (K-SVD) algorithm, has recently tapped into the basis function design, showing better representation performance than the EOFs. However, existing methods do not consider basis function learning approaches that treat 3D SSF data as a third-order tensor, and, thus, cannot fully utilize the 3D interactions/correlations therein. To circumvent such a drawback, basis function learning is linked to tensor decomposition in this paper, which is the primary drive for recent multi-dimensional data mining. In particular, a tensor-based basis function learning framework is proposed, which can include the classical basis…

Automatic algorithms for the detection and classification of sound are essential to the analysis of acoustic datasets with long duration. Metrics are needed to assess the performance characteristics of these algorithms. Four metrics for performance evaluation are discussed here: receiver-operating-characteristic (ROC) curves, detection-error-trade-off (DET) curves, precision-recall (PR) curves, and cost curves. These metrics were applied to the generalized power law detector for blue whale D calls [Helble, Ierley, D'Spain, Roch, and Hildebrand (2012). J. Acoust. Soc. Am. 131(4), 2682-2699] and the click-clustering neural-net algorithm for Cuvier's beaked whale echolocation click detection [Frasier, Roch, Soldevilla, Wiggins, Garrison, and Hildebrand (2017). PLoS Comp. Biol. 13(12), e1005823] using data prepared for the 2015 Detection, Classification, Localization and Density Estimation Workshop. Detection class imbalance, particularly the situation of rare occurrence, is common for long-term passive acoustic monitoring datasets and is a factor in the performance of ROC and DET…

Coral reef soundscapes are increasingly studied for their ecological uses by invertebrates and fishes, for monitoring habitat quality, and to investigate effects of anthropogenic noise pollution. Few examinations of aquatic soundscapes have reported particle motion levels and variability, despite their relevance to invertebrates and fishes. In this study, ambient particle acceleration was quantified from orthogonal hydrophone arrays over several months at four coral reef sites, which varied in benthic habitat and fish communities. Time-averaged particle acceleration magnitudes were similar across axes, within 3 dB. Temporal trends of particle acceleration corresponded with those of sound pressure, and the strength of diel trends in both metrics significantly correlated with percent coral cover. Higher magnitude particle accelerations diverged further from pressure values, potentially representing sounds recorded in the near field. Particle acceleration levels were also reported for boat and example fish sounds. Comparisons with particle acceleration derived audiograms suggest the…

Measurements of the source levels of 9880 passes of 3188 different large commercial ships from the Enhancing Cetacean Habitat and Observation (ECHO) program database were used to investigate the dependencies of vessel underwater noise emissions on several vessel design parameters and operating conditions. Trends in the dataset were analyzed using functional regression analysis, which is an extension of standard regression analysis and represents a response variable (decidecade band source level) as a continuous function of a predictor variable (frequency). The statistical model was applied to source level data for six vessel categories: cruise ships, container ships, bulk carriers, tankers, tugs, and vehicle carriers. Depending on the frequency band and category, the functional regression model explained approximately 25%-50% of the variance in the ECHO dataset. The two main operational parameters, speed through water and actual draft, were the predictors most strongly correlated with source levels in all of the vessel categories. Vessel size (represented via length overall) was the…

This letter introduces a database of Room Impulse Responses (RIRs) measured in seven different rooms for multizone sound field reproduction research in various acoustic environments. A circular array of 60 loudspeakers was installed in each room, with two microphone arrays placed sequentially in five different zones inside the loudspeaker array. A total of 260 400 RIRs were measured to establish the database. As a demonstration application of the database for multizone sound field reproduction, simulations were performed on the pressure matching and acoustic contrast control methods to investigate how a system optimized with the RIRs measured in one room would perform in other rooms.

Airfoil turbulence interaction noise and the flow field up to and over the porous leading edge is experimentally studied. The porous leading edges were of the same base triply periodic minimal surface structure with varying porosity to enable us to understand how the porosity, permeability, and pore size affect the generated turbulence interaction noise. The turbulent flow was generated by means of a passive turbulence grid that does not affect the normal background noise of the wind tunnel. Far-field noise results were obtained from a polar microphone array to assess the directivity of the sound as well as the narrowband frequency contributions. Far-field noise results demonstrate that increasing porosity reduces the turbulence interaction noise over low-to-mid frequencies, with a penalty of a high frequency noise increase. Flow measurement results indicate hydrodynamic penetration of the flow into the porous structure at the leading edge. Furthermore, the two-point correlation analysis of the velocity fluctuations approaching the leading edge shows that the turbulent structures…

When confronted with unfamiliar or novel forms of speech, listeners' word recognition performance is known to improve with exposure, but data are lacking on the fine-grained time course of adaptation. The current study aims to fill this gap by investigating the time course of adaptation to several different types of distorted speech. Keyword scores as a function of sentence position in a block of 30 sentences were measured in response to eight forms of distorted speech. Listeners recognised twice as many words in the final sentence compared to the initial sentence with around half of the gain appearing in the first three sentences, followed by gradual gains over the rest of the block. Rapid adaptation was apparent for most of the eight distortion types tested with differences mainly in the gradual phase. Adaptation to sine-wave speech improved if listeners had heard other types of distortion prior to exposure, but no similar facilitation occurred for the other types of distortion. Rapid adaptation is unlikely to be due to procedural learning since listeners had been familiarised…

The long baseline (LBL) underwater navigation paradigm relies on the conversion of travel times into pseudoranges to trilaterate position. For real-time autonomous underwater vehicle (AUV) operations, this conversion assumes an isovelocity sound speed. For re-navigation, computationally and/or labor-intensive acoustic modeling may be employed to reduce uncertainty. This work demonstrates a real-time ray-based prediction of the effective sound speed along a path from source to receiver. This method was implemented for an AUV-LBL system in the Beaufort Sea in an ice-covered and a double-ducted propagation environment. Given the lack of Global Navigation Satellite Systems (GNSS) data throughout the vehicle's mission, the pseudorange performance is first evaluated on acoustic transmissions between GNSS-linked beacons. The mean real-time absolute range error between beacons is roughly 11 m at distances up to 3 km. A consistent overestimation in the real-time method provides insights for improved eigenray filtering by the number of bounces. An operationally equivalent pipeline is used to…

Bragg scattering in periodic media generates bandgaps, frequency bands where waves attenuate rather than propagate. Yet, a finite periodic structure may exhibit resonance frequencies within these bandgaps. This is caused by boundary effects introduced by the truncation of the nominal infinite medium. Previous studies of discrete systems determined existence conditions for bandgap resonances, although the focus has been limited to mainly periodic chains with free-free boundaries. In this paper, we present closed-form existence conditions for bandgap resonances in discrete diatomic chains with general boundary conditions (free-free, free-fixed, fixed-free, or fixed-fixed), odd or even chain parity (contrasting or identical masses at the ends), and the possibility of attaching a unique component (mass and/or spring) at one or both ends. The derived conditions are consistent with those theoretically presented or experimentally observed in prior studies of structures that can be modeled as linear discrete diatomic chains with free-free boundary conditions. An intriguing case is a…

Personal sound zones (PSZ) systems use an array of loudspeakers to render independent audio signals to multiple listeners within a room. The performance of a PSZ system, designed using weighted pressure matching, depends on the selected target responses for the bright zone. In reverberant environments, the target responses are generally chosen to be the room impulse responses from one of the loudspeakers to the control points in the selected bright zone. This approach synthesizes the direct propagation component and all the reverberant components in the bright zone, while minimizing the energy in the dark zone. We present a theoretical analysis to show that high energy differences cannot be achieved for the diffuse reverberant components in the bright and dark zones, and so trying to synthesize these components in the bright zone does not lead to the best performance. It is then shown that the performance can be improved by using windowed versions of these measured impulse responses as target signals, in order to control which reverberant components are synthesized in the bright…

Of the many available reverberation time prediction formulas, Sabine's and Eyring's equations are still widely used. The assumptions of homogeneity and isotropy of sound energy during the decay associated with those models are usually recognized as a reason for lack of agreement between predictions and measurements. At the same time, the inaccuracy in the estimation of the sound-absorption coefficient adds to the uncertainty of calculations. This paper shows that the error of incorrectly assumed sound absorption is more detrimental to the prediction precision than the inherent error in the formulas themselves. The proposed absorption calibration procedure reduces the differences between the measured and predicted reverberation time values, showing that an accuracy within ±10% from the target reverberation time values can be achieved regardless of the absorption distribution in a room. The paper also discusses the oft neglected air absorption of sound, which may introduce considerable bias to the measurement results. The need for an air-absorption compensation procedure is…

The amplitude of the speech signal varies over time, and the speech envelope is an attempt to characterise this variation in the form of an acoustic feature. Although tacitly assumed, the similarity between the speech envelope-derived time series and that of phonetic objects (e.g., vowels) remains empirically unestablished. The current paper, therefore, evaluates several speech envelope extraction techniques, such as the Hilbert transform, by comparing different acoustic landmarks (e.g., peaks in the speech envelope) with manual phonetic annotation in a naturalistic and diverse dataset. Joint speech tasks are also introduced to determine which acoustic landmarks are most closely coordinated when voices are aligned. Finally, the acoustic landmarks are evaluated as predictors for the temporal characterisation of speaking style using classification tasks. The landmark that performed most closely to annotated vowel onsets was peaks in the first derivative of a human audition-informed envelope, consistent with converging evidence from neural and behavioural data. However, differences…

This paper describes the design process of a low-frequency sound absorptive panel composed of differently tuned Helmholtz resonators (HRs), considering size and fabrication constraints relevant for applications in the building sector. The paper focuses on cylindrical and spiral resonators with embedded necks that are thin and can achieve high absorption. the mutual interaction between the resonators was modeled based on the radiation impedance method and it plays a key component in enhancing the absorption performance of the array. The differential evolution search algorithm was used to design the resonators and modify their mutual interaction to derive the absorption performance of multiple HR arrays for comparison. Optimizations to the resonator configuration and the neck resistance were implemented to produce a unit panel that has a broadband absorption performance with emphasis on the low to mid frequencies and is thin and light in weight. Unit panels with dimensions of 20 cm×20 cm, consisting of 29 cylindrical HRs designed to absorb in the 25-900 Hz frequency range, were…

Leaky waves are an important class of waves, particularly for guiding waves along structures embedded within another medium; a mismatch in wavespeeds often leads to leakage of energy from the waveguide, or interface, into the medium, which consequently attenuates the guided wave. The accurate and efficient identification of theoretical solutions for leaky waves is a key requirement for the choices of modes and frequencies required for non-destructive evaluation inspection techniques. We choose a typical situation to study: an elastic waveguide with a fluid on either side. Historically, leaky waves are identified via root-finding methods that have issues with conditioning, or numerical methods that struggle with the exponential growth of solutions at infinity. By building upon a spectral collocation method, we show how it can be adjusted to find exponentially growing solutions, i.e., leaky waves, leading to an accurate, fast, and efficient identification of their dispersion properties. The key concept required is a mapping, in the fluid region, that allows for exponential growth of…

This paper presents gridless sparse processing for direction-of-arrival (DOA) estimation. The method solves a gridless version of sparse covariance-based estimation using alternating projections. Gridless sparse DOA estimation is represented by the reconstruction of Toeplitz-structured low-rank matrices, which our method recovers by alternatively projecting a solution matrix. Compared to the existing gridless sparse methods, our method improves speed and accuracy and considers non-uniformly configured linear arrays. High-resolution and reliable DOA estimation are achieved even with single-snapshot data, coherent sources, and non-uniform arrays. Simulation results demonstrate performance improvements compared to the existing DOA estimators, including gridless sparse methods. The method is illustrated using experimental data from a real ocean experiment.

The flexible vibrational sensor (FVS) has the potential to become a popular wearable communication device because of its natural noise shielding characteristics and soft materials. However, FVS speech faces a severe loss of frequency components. To improve speech quality, a time-domain neural network model based on the dual-path transformer combined with equalization-generation components prediction (DPT-EGNet) is proposed. More specifically, the DPT-EGNet consists of five modules, namely the pre-processing module, dual-path transformer module, equalization module, generation module, and post-processing module. The dual-path transformer module is leveraged to extract the local and global contextual relationship of long-term speech sequences, which is extremely beneficial for inferring the missing components. The equalization and generation modules are designed according to the characteristics of FVS speech, which further improve the speech quality by simulating the inversion process of the speech distortion. The experimental results demonstrate that the proposed model effectively…

Music listening experiences can be enhanced with tactile vibrations. However, it is not known which parameters of the tactile vibration must be congruent with the music to enhance it. Devices that aim to enhance music with tactile vibrations often require coding an acoustic signal into a congruent vibrotactile signal. Therefore, understanding which of these audio-tactile congruences are important is crucial. Participants were presented with a simple sine wave melody through supra-aural headphones and a haptic actuator held between the thumb and forefinger. Incongruent versions of the stimuli were made by randomizing physical parameters of the tactile stimulus independently of the auditory stimulus. Participants were instructed to rate the stimuli against the incongruent stimuli based on preference. It was found making the intensity of the tactile stimulus incongruent with the intensity of the auditory stimulus, as well as misaligning the two modalities in time, had the biggest negative effect on ratings for the melody used. Future vibrotactile music enhancement devices can use time…

The measure H1-H2, the difference in amplitude between the first and second harmonics, is frequently used to distinguish phonation types and to characterize differences across voices and genders. While H1-H2 can differentiate voices and is used by listeners to perceive changes in voice quality, its relation to voice articulation is less straightforward. Its calculation also involves practical issues with error propagation. This paper highlights some developments in the use of H1-H2 and proposes a new measure that we call "residual H1." In residual H1, the amplitude of the first harmonic is normalized against the overall sound energy (as measured by root mean square energy) instead of against H2. Residual H1 may mitigate some of the issues with using H1-H2. The current study tests the correlation between residual H1 and electroglottographic contact quotient (CQ) and compares the ability of residual H1 vs H1-H2 to differentiate statistically across phonation types in !Xóõ and utterance-level changes in phonatory quality in Mandarin. The results show that residual H1 has a stronger…

Resonant ultrasound spectroscopy is used to nondestructively measure the elastic resonances of small solids to elucidate the material's elastic properties or other qualities like size, shape, or composition. Here, we introduce the software RUScal for the purpose of determining elastic properties by analyzing the eigenfrequencies of solid specimens with common shapes, such as rectangular parallelepipeds, cylinders (solid and hollow tube), ellipsoids, and octahedrons, as well as irregularly shaped ellipsoids that can be described analytically. All symmetry classes are supported, from isotropic to triclinic, along with the option to add or remove up to three orthogonal mirror planes as well as the ability to reorient the crystal axes with respect the sample edges via Euler angles. Additional features include tools to help find initial sets of elastic constants, including grid exploration and Monte Carlo methods, a tool to analyze frequencies as a function of sample length or crystal orientation, an error analysis tool to assess fit quality, and formatting of the input and output files…

A multi-range vertical array data processing (MRP) method based on a convolutional neural network (CNN) is proposed to estimate geoacoustic parameters in shallow water. The network input is the normalized sample covariance matrices of the broadband multi-range data received by a vertical line array. Since the geoacoustic parameters (e.g., bottom sound speed, density, and attenuation) have different scales, the multi-task learning is used to estimate these parameters simultaneously. To reduce the influence of the uncertainty of the source position, the training and validation data are composed of the simulation data of different source depths. Simulation results demonstrate that compared with the conventional matched-field inversion (MFI), the CNN with MRP alleviates the coupling between the geoacoustic parameters and is more robust to different source depths in the shallow water environment. Based on the inversion results, better localization performance is achieved when the range-dependent environment is assumed to be a range-independent model. Real data from the East China Sea…

Optical coherence tomography (OCT) has become a powerful tool for measuring vibrations within the organ of Corti complex (OCC) in cochlear mechanics experiments. However, the one-dimensional nature of OCT measurements, combined with experimental and anatomical constraints, make these data ambiguous: Both the relative positions of measured structures and their orientation relative to the direction of measured vibrations are not known a priori. We present a method by which these measurement features can be determined via the use of a volumetric OCT scan to determine the relationship between the imaging/measurement axes and the canonical anatomical axes. We provide evidence that the method is functional by replicating previously measured radial vibration patterns of the basilar membrane (BM). We used the method to compare outer hair cell and BM vibration phase in the same anatomical cross section (but different optical cross sections), and found that outer hair cell region vibrations lead those of the BM across the entire measured frequency range. In contrast, a phase lead is only…

Bearded seals vocalizations are often analyzed manually or by using automatic detections that are manually validated. In this work, an automatic detection and classification system (DCS) based on convolutional neural networks (CNNs) is proposed. Bearded seal sounds were year-round recorded by four spatially separated receivers on the Chukchi Continental Slope in Alaska in 2016-2017. The DCS is divided in two sections. First, regions of interest (ROI) containing possible bearded seal vocalizations are found by using the two-dimensional normalized cross correlation of the measured spectrogram and a representative template of two main calls of interest. Second, CNNs are used to validate and classify the ROIs among several possible classes. The CNNs are trained on 80% of the ROIs manually labeled from one of the four spatially separated recorders. When validating on the remaining 20%, the CNNs show an accuracy above 95.5%. To assess the generalization performance of the networks, the CNNs are tested on the remaining recorders, located at different positions, with a precision above 89.2%…

Aging, noise exposure, and ototoxic medications lead to cochlear synapse loss in animal models. As cochlear function is highly conserved across mammalian species, synaptopathy likely occurs in humans as well. Synaptopathy is predicted to result in perceptual deficits including tinnitus, hyperacusis, and difficulty understanding speech-in-noise. The lack of a method for diagnosing synaptopathy in living humans hinders studies designed to determine if noise-induced synaptopathy occurs in humans, identify the perceptual consequences of synaptopathy, or test potential drug treatments. Several physiological measures are sensitive to synaptopathy in animal models including auditory brainstem response (ABR) wave I amplitude. However, it is unclear how to translate these measures to synaptopathy diagnosis in humans. This work demonstrates how a human computational model of the auditory periphery, which can predict ABR waveforms and distortion product otoacoustic emissions (DPOAEs), can be used to predict synaptic loss in individual human participants based on their measured DPOAE levels and…