The 50 most-cited articles in The Journal of the Acoustical Society of America, 2018

This paper considers the importance of particle motion to fishes and invertebrates and the steps that need to be taken to improve knowledge of its effects. It is aimed at scientists investigating the impacts of sounds on fishes and invertebrates but it is also relevant to regulators, those preparing environmental impact assessments, and to industries creating underwater sounds. The overall aim of this paper is to ensure that proper attention is paid to particle motion as a stimulus when evaluating the effects of sound upon aquatic life. Directions are suggested for future research and planning that, if implemented, will provide a better scientific basis for dealing with the impact of underwater sounds on marine ecosystems and for regulating those human activities that generate such sounds. The paper includes background material on underwater acoustics, focusing on particle motion; the importance of particle motion to fishes and invertebrates; and sound propagation through both water and the substrate. Consideration is then given to the data gaps that must be filled in order to…

Composite honeycomb sandwich panels have been adopted in a wide range of applications owing to their excellent mechanical properties. This paper demonstrates a design of a composite honeycomb metasurface panel that can achieve 90% sound absorption from 600 to 1000 Hz with a thickness less than 30 mm. The panel is comprised of periodically and horizontally arranged honeycomb "supercells" which consist of unit cells of different geometric parameters (pore size). Two different analytical models (Helmholtz resonator model and micro-perforated panel model) are used to calculate the sound absorption of the panel, and they are further validated by a numerical model. The relatively broadband sound absorption is found to be attributed to the coupling between unit cells, which is illustrated by both the complex frequency plane theory and the calculated sound intensity field.

Thermoacoustic engines convert heat energy into high amplitude acoustic waves and subsequently into electric power. This article provides a review of the four main methods to convert the (thermo)acoustic power into electricity. First, loudspeakers and linear alternators are discussed in a section on electromagnetic devices. This is followed by sections on piezoelectric transducers, magnetohydrodynamic generators, and bidirectional turbines. Each segment provides a literature review of the given technology for the field of thermoacoustics, focusing on possible configurations, operating characteristics, output performance, and analytical and numerical methods to study the devices. This information is used as an input to discuss the performance and feasibility of each method, and to identify challenges that should be overcome for a more successful implementation in thermoacoustic engines. The work is concluded by a comparison of the four technologies, concentrating on the possible areas of application, the conversion efficiency, maximum electrical power output and more generally the…

Deep neural networks (DNNs) are advantageous for representing complex nonlinear relationships. This paper applies DNNs to source localization in a shallow water environment. Two methods are proposed to estimate the range and depth of a broadband source through different neural network architectures. The first adopts the classical two-stage scheme, in which feature extraction and DNN analysis are independent steps. The eigenvectors associated with the modal signal space are extracted as the input feature. Then, the time delay neural network is exploited to model the long term feature representation and constructs the regression model. The second concerns a convolutional neural network-feed-forward neural network (CNN-FNN) architecture, which trains the network directly by taking the raw multi-channel waveforms as input. The CNNs are expected to perform spatial filtering for multi-channel signals, in an operation analogous to time domain filters. The outputs of CNNs are summed as the input to FNN. Several experiments are conducted on the simulated and experimental data to evaluate the…

In this paper, machine learning is introduced to source localization in underwater ocean waveguides. Source localization is regarded as a supervised learning regression problem and is solved by generalized regression neural network (GRNN). As a feed-forward network, GRNN is built using training data with fixed structure and configuration. The normalized sample covariance matrix (SCM) formed over a number of snapshots, and the corresponding source position are used as the input and output for GRNN. The source position can be estimated directly from the normalized SCM with GRNN; the proposed approach is thus in theory data driven. In addition, there is only one parameter, the spread factor, to be learned for GRNN. The optimal spread factor is determined using cross-validation. The regression method of GRNN is compared with the classification method of feed-forward neural network (FNN), as well as the classical method of matched field processing (MFP) for vertical array data from the SWellEx-96 experiment. The results show that GRNN achieves a satisfactory localization performance that…

Speech perception requires multiple acoustic cues. Cue weighting may differ across individuals but be systematic within individuals. The current study compared individuals' cue weights within and across contrasts. Forty-two listeners performed a two-alternative forced choice task for four out of five sets of minimal pairs, each varying orthogonally in two dimensions. Individuals' cue weights within a contrast were positively correlated for bet-bat, Luce-lose, and sock-shock, but not for bog-dog and dear-tear. Importantly, individuals' cue weights were also positively correlated across contrasts. This indicates that some individuals are better able to extract and use phonetic information across different dimensions.

Compressive sensing (CS) in acoustics has received significant attention in the last decade, and thus motivates this special issue. CS emerged from the signal processing and applied math community and has since generated compelling results in acoustics. This special issue primarily addresses the acoustics CS topics of compressive beamforming and holography. For a sound field observed on a sensor array, CS reconstructs the direction of arrival of multiple sources using a sparsity constraint. Similarly, in holography a sparsity constraint gives improved sound field reconstruction over conventional ℓ2-regularization. Other topics in this issue include sparse array configurations (as co-arrays) and sparse sensing in acoustic communication.

Capturing the impulse or frequency response functions within extended regions of a room requires an unfeasible number of measurements. In this study, a method to reconstruct the response at arbitrary points based on compressive sensing (CS) is examined. The sound field is expanded into plane waves and their amplitudes are estimated via CS, obtaining a spatially sparse representation of the sound field. The validity of the CS assumptions are discussed, namely, the assumption of the wave field spatial sparsity (which depends strongly on the properties of the specific room), and the coherence of the sensing matrix due to different spatial sampling schemes. An experimental study is presented in order to analyze the accuracy of the reconstruction. Measurements with a scanning robotic arm make it possible to circumvent uncertainty due to positioning and transducer mismatch, and examine the accuracy of the reconstruction over extended regions of space. The results indicate that near perfect reconstructions are possible at low frequencies, even from a limited set of measurements. In…

A model and method to accurately estimate the local speed of sound in tissue from pulse-echo ultrasound data is presented. The model relates the local speeds of sound along a wave propagation path to the average speed of sound over the path, and allows one to avoid bias in the sound-speed estimates that can result from overlying layers of subcutaneous fat and muscle tissue. Herein, the average speed of sound using the approach by Anderson and Trahey is measured, and then the authors solve the proposed model for the local sound-speed via gradient descent. The sound-speed estimator was tested in a series of simulation and ex vivo phantom experiments using two-layer media as a simple model of abdominal tissue. The bias of the local sound-speed estimates from the bottom layers is less than 6.2 m/s, while the bias of the matched Anderson's estimates is as high as 66 m/s. The local speed-of-sound estimates have higher standard deviation than the Anderson's estimates. When the mean local estimate is computed over a 5-by-5 mm region of interest, its standard deviation is reduced to less…

This paper presents a bi-view (front and side) audiovisual Lombard speech corpus, which is freely available for download. It contains 5400 utterances (2700 Lombard and 2700 plain reference utterances), produced by 54 talkers, with each utterance in the dataset following the same sentence format as the audiovisual "Grid" corpus [Cooke, Barker, Cunningham, and Shao (2006). J. Acoust. Soc. Am. 120(5), 2421-2424]. Analysis of this dataset confirms previous research, showing prominent acoustic, phonetic, and articulatory speech modifications in Lombard speech. In addition, gender differences are observed in the size of Lombard effect. Specifically, female talkers exhibit a greater increase in estimated vowel duration and a greater reduction in F2 frequency.

Speech localization and enhancement involves sound source mapping and reconstruction from noisy recordings of speech mixtures with microphone arrays. Conventional beamforming methods suffer from low resolution, especially with a limited number of microphones. In practice, there are only a few sources compared to the possible directions-of-arrival (DOA). Hence, DOA estimation is formulated as a sparse signal reconstruction problem and solved with sparse Bayesian learning (SBL). SBL uses a hierarchical two-level Bayesian inference to reconstruct sparse estimates from a small set of observations. The first level derives the posterior probability of the complex source amplitudes from the data likelihood and the prior. The second level tunes the prior towards sparse solutions with hyperparameters which maximize the evidence, i.e., the data probability. The adaptive learning of the hyperparameters from the data auto-regularizes the inference problem towards sparse robust estimates. Simulations and experimental data demonstrate that SBL beamforming provides high-resolution DOA maps…

Binaural rendering of Ambisonic signals is of great interest in the fields of virtual reality, immersive media, and virtual acoustics. Typically, the spatial order of head-related impulse responses (HRIRs) is considerably higher than the order of the Ambisonic signals. The resulting order reduction of the HRIRs has a detrimental effect on the binaurally rendered signals, and perceptual evaluations indicate limited externalization, localization accuracy, and altered timbre. In this contribution, a binaural renderer, which is computed using a frequency-dependent time alignment of HRIRs followed by a minimization of the squared error subject to a diffuse-field covariance matrix constraint, is presented. The frequency-dependent time alignment retains the interaural time difference (at low frequencies) and results in a HRIR set with lower spatial complexity, while the constrained optimization controls the diffuse-field behavior. Technical evaluations in terms of sound coloration, interaural level differences, diffuse-field response, and interaural coherence, as well as findings from…

The acoustic fields and streaming in a confined fluid depend strongly on the viscous boundary layer forming near the wall. The width of this layer is typically much smaller than the bulk length scale set by the geometry or the acoustic wavelength, which makes direct numerical simulations challenging. Based on this separation in length scales, the classical theory of pressure acoustics is extended by deriving a boundary condition for the acoustic pressure that takes viscous boundary-layer effects fully into account. Using the same length-scale separation for the steady second-order streaming, and combining it with time-averaged short-range products of first-order fields, the usual limiting-velocity theory is replaced with an analytical slip-velocity condition on the long-range streaming field at the wall. The derived boundary conditions are valid for oscillating cavities of arbitrary shape and wall motion, as long as both the wall curvature and displacement amplitude are sufficiently small. Finally, the theory is validated by comparison with direct numerical simulation in two…

Network-based sound monitoring systems are deployed in various cities over the world and mobile applications allowing participatory sensing are now common. Nevertheless, the sparseness of the collected measurements, either in space or in time, complicates the production of sound maps. This paper describes the results of a measurement campaign that has been conducted in order to test different spatial interpolation strategies for producing sound maps. Mobile measurements have been performed while walking multiple times in every street of the XIIIth district of Paris. By adaptively constructing a noise map on the basis of these measurements, the role of the density of observations and the performance of four different interpolation strategies is investigated. Ordinary and universal Kriging methods are assessed, as well as the effect of using an alternative definition of the distance between observation locations, which takes the topology of the road network into account. The results show that a high density of observation points is necessary to obtain an interpolated sound map close…

The influence of a polycrystals' grain structure on elastic wave scattering is studied with analytical and numerical methods in a broad frequency range. A semi-analytical attenuation model, based on an established scattering theory, is presented. This technique accurately accounts for the grain morphology without prior assumptions on grain statistics. This is achieved by incorporating a samples' exact spatial two-point correlation function into the theory. The approach is verified by using a finite element method (FEM) to simulate P-wave propagation in 3D Voronoi crystals with equal mean grain diameter, but different grain shape uniformity. Aluminum and Inconel serve as representatives for weak and strong scattering cubic class materials for simulations and analytical calculations. It was found that the shape of the grains has a strong influence on the attenuation curve progression in the Rayleigh-stochastic transition region, which was attributed to mode conversion scattering. Comparisons between simulations and theory show excellent agreement for both materials. This demonstrates…

Directional hearing may enable fishes to seek out prey, avoid predators, find mates, and detect important spatial cues. Early sound localization experiments gave negative results, and it was thought unlikely that fishes utilized the same direction-finding mechanisms as terrestrial vertebrates. However, fishes swim towards underwater sound sources, and some can discriminate between sounds from different directions and distances. The otolith organs of the inner ear detect the particle motion components of sound, acting as vector detectors through the presence of sensory hair cells with differing orientation. However, many questions remain on inner ear functioning. There are problems in understanding the actual mechanisms involved in determining sound direction and distance. Moreover, very little is still known about the ability of fishes to locate sound sources in three-dimensional space. Do fishes swim directly towards a source, or instead "sample" sound levels while moving towards the source? To what extent do fishes utilize other senses and especially vision in locating the source?…

Excessive vocal effort is a common clinical voice symptom, yet the acoustical manifestation of vocal effort and how that is perceived by speakers and listeners has not been fully elucidated. Here, 26 vocally healthy adults increased vocal effort during the production of the utterance /ifi/, followed by self-ratings of effort on a 100 mm visual analog scale. Twenty inexperienced listeners assessed the speakers' vocal effort using the visual sort-and-rate method. Previously proposed acoustical correlates of vocal effort were calculated, including: mean sound pressure level (SPL), mean fundamental frequency (fo), relative fundamental frequency (RFF) offset cycle 10 and onset cycle 1, harmonics-to-noise ratio (HNR), cepstral peak prominence and its standard deviation (SD), and low-to-high (L/H) spectral ratio and its SD. Two separate mixed-effects regression models yielded mean SPL, L/H ratio, and HNR as significant predictors of both speaker and listener ratings of vocal effort. RFF offset cycle 10 and mean fo were significant predictors of listener ratings only. Therefore, speakers…

In this paper, the effectiveness of deep learning for automatic classification of grouper species by their vocalizations has been investigated. In the proposed approach, wavelet denoising is used to reduce ambient ocean noise, and a deep neural network is then used to classify sounds generated by different species of groupers. Experimental results for four species of groupers show that the proposed approach achieves a classification accuracy of around 90% or above in all of the tested cases, a result that is significantly better than the one obtained by a previously reported method for automatic classification of grouper calls.

Sparse linear arrays such as co-prime and nested arrays can resolve more sources than the number of sensors. In contrast, uniform linear arrays (ULA) cannot resolve more sources than the number of sensors. This paper demonstrates this using Sparse Bayesian learning (SBL) and co-array MUSIC for single frequency beamforming. For approximately the same number of sensors, co-prime and nested arrays are shown to outperform ULA in root mean squared error. This paper shows that multi-frequency SBL can significantly reduce spatial aliasing. The effects of different sparse sub-arrays on SBL performance are compared qualitatively using the Noise Correlation 2009 experimental data set.

During the past decade, several publications have described the use of compressive sensing principles to extend the frequency range supported by a given irregular microphone array for near-field acoustic holography. The applied numerical source model has typically been of the type used for the equivalent source method, i.e., a mesh of point sources, and a one-norm regularized inverse problem has been solved using a very stable, but slow interior-point optimization algorithm. A few publications have investigated the use of simpler and faster iterative algorithms. The present paper gives a brief description of five such iterative algorithms, and it compares their performances with that of the interior-point algorithm based on a set of simulated measurements. A particular focus is on the suitability for industrial applications. Finally, an optimal choice of methodology is discussed based on the presented limited set of simulated tests.

The work presented in this paper focuses on the use of acoustic systems for passive acoustic monitoring of ocean vitality for fish populations. Specifically, it focuses on the use of acoustic systems for passive acoustic monitoring of ocean vitality for fish populations. To this end, various indicators can be used to monitor marine areas such as both the geographical and temporal evolution of fish populations. A discriminative model is built using supervised machine learning (random-forest and support-vector machines). Each acquisition is represented in a feature space, in which the patterns belonging to different semantic classes are as separable as possible. The set of features proposed for describing the acquisitions come from an extensive state of the art in various domains in which classification of acoustic signals is performed, including speech, music, and environmental acoustics. Furthermore, this study proposes to extract features from three representations of the data (time, frequency, and cepstral domains). The proposed classification scheme is tested on real fish sounds…

The feasibility of data based machine learning applied to ultrasound tomography is studied to estimate water-saturated porous material parameters. In this work, the data to train the neural networks is simulated by solving wave propagation in coupled poroviscoelastic-viscoelastic-acoustic media. As the forward model, a high-order discontinuous Galerkin method is considered, while deep convolutional neural networks are used to solve the parameter estimation problem. In the numerical experiment, the material porosity and tortuosity is estimated, while the remaining parameters which are of less interest are successfully marginalized in the neural networks-based inversion. Computational examples confirm the feasibility and accuracy of this approach.

Grouper, a family of marine fishes, produce distinct vocalizations associated with their reproductive behavior during spawning aggregation. These low frequencies sounds (50-350 Hz) consist of a series of pulses repeated at a variable rate. In this paper, an approach is presented for automatic classification of grouper vocalizations from ambient sounds recorded in situ with fixed hydrophones based on weighted features and sparse classifier. Group sounds were labeled initially by humans for training and testing various feature extraction and classification methods. In the feature extraction phase, four types of features were used to extract features of sounds produced by groupers. Once the sound features were extracted, three types of representative classifiers were applied to categorize the species that produced these sounds. Experimental results showed that the overall percentage of identification using the best combination of the selected feature extractor weighted mel frequency cepstral coefficients and sparse classifier achieved 82.7% accuracy. The proposed algorithm has been…

A Green's function solution is derived for calculating the acoustic field generated by phased array transducers of arbitrary shape when driven by a single frequency continuous wave excitation with spatially varying amplitude and phase. The solution is based on the Green's function for the homogeneous wave equation expressed in the spatial frequency domain or k-space. The temporal convolution integral is solved analytically, and the remaining integrals are expressed in the form of the spatial Fourier transform. This allows the acoustic pressure for all spatial positions to be calculated in a single step using two fast Fourier transforms. The model is demonstrated through several numerical examples, including single element rectangular and spherically focused bowl transducers, and multi-element linear and hemispherical arrays.

Acoustoelastic techniques have been recently used to characterize the state of prestress in structures such as plates. The velocity of guided wave modes propagating through plates is sensitive to the magnitude and orientation of the initial state of stress. Dispersion curves for phase velocities of plate guided waves can be computed using the superposition of partial bulk waves (SPBW) method. Here, a semi-analytical finite element (SAFE) method is formulated for the acoustoelastic problem of guided waves in weakly nonlinear elastic plates. The SAFE formulation is shown to provide phase velocity dispersion curve results identical with those provided by the SPBW method for the problem of a plate under a uniaxial and uniform tensile stress. Analytical phase and group velocity dispersion curves are also obtained for a plate with an initial prestress gradient through its thickness using the SAFE method. The magnitude of the prestress gradient is shown to have a significant effect on phase and group velocities of the fundamental and first order Lamb modes, only in certain…

A method to recover the elastic properties, thickness, or orientation of the principal symmetry axes of anisotropic plates is presented. This method relies on the measurements of multimode guided waves, which are launched and detected in arbitrary directions along the plate using a multi-element linear transducer array driven by a programmable electronic device. A model-based inverse problem solution is proposed to optimally recover the properties of interest. The main contribution consists in defining an objective function built from the dispersion equation, which allows accounting for higher-order modes without the need to pair each experimental data point to a specific guided mode. This avoids the numerical calculation of the dispersion curves and errors in the mode identification. Compared to standard root-finding algorithms, the computational gain of the procedure is estimated to be on the order of 200. The objective function is optimized using genetic algorithms, which allow identifying from a single out-of-symmetry axis measurement the full set of anisotropic elastic…

This study proposes an experimental method for evaluating isotropy in enclosures, based on an analysis of the wavenumber spectrum in the spherical harmonics domain. The wavenumber spectrum, which results from expanding an arbitrary sound field into a plane-wave basis, is used to characterize the spatial properties of the observed sound field. Subsequently, the obtained wavenumber spectrum is expanded into a series of spherical harmonics, and the moments from this spherical expansion are used to characterize the isotropy of the wave field. The analytical framework is presented. The method is examined numerically and experimentally, based on array measurements in four chambers: two anechoic chambers (one with a single source and another with an array of 52 sources), a reverberation chamber, and the same reverberation chamber with a sample of absorbing material on the floor. The results indicate that the proposed methodology is suitable for assessing the isotropy of a sound field.

A structure for an underwater sound absorber with subwavelength thickness and a quasi-perfect absorption property at multiple frequency bands is reported. This absorber consists of a viscoelastic coating layer embedded with periodically distributed plate scatterers (PSs). The embedded PSs cannot only slow sound waves in the coating, leading to a down-shifted resonance frequency where the absorption is maximized, but also introduce multiple local bending modes and local longitudinal modes in the coating. Via proper selection of the parameters of the PSs and the PS array, multiple local resonance modes of different types in a coating unit can be excited, resulting in quasi-perfect absorption of incident sound at multiple frequencies whose wavelengths are much longer than the thickness of the coating layer. For example, absorption (89%) of underwater sound at 462.9 Hz is achieved by such a layer with a thickness of 6 cm, which is 1.9% of the wavelength of the incident sound. Broadband quasi-perfect absorption can also be realized by coupling of those multiple local resonant modes. This…

This paper presents single receiver geoacoustic inversion of a combustive sound source signal, recorded during the 2017 Seabed Characterization Experiment on the New England Mud Patch, in an area where water depth is around 70 m. There are two important features in this study. First, it is shown that high-order modes can be resolved and estimated using warping (up to mode number 18 over the frequency band 20-440 Hz). However, it is not possible to determine mode numbers from the data, so that classical inversion methods that require mode identification cannot be applied. To solve this issue, an inversion algorithm that jointly estimates geoacoustic properties and identifies mode number is proposed. It is successfully applied on a range-dependent track, and provides a reliable range-average estimation of geoacoustic properties of the mud layer, an important feature of the seabed on the experimental area.

How fast can listeners adapt to unfamiliar foreign accents? Clarke and Garrett [J. Acoust. Soc. Am. 116, 3647-3658 (2004)] (CG04) reported that native-English listeners adapted to foreign-accented English within a minute, demonstrating improved processing of spoken words. In two web-based experiments that closely follow the design of CG04, the effects of rapid accent adaptation are examined and its generalization is explored across talkers. Experiment 1 replicated the core finding of CG04 that initial perceptual difficulty with foreign-accented speech can be attenuated rapidly by a brief period of exposure to an accented talker. Importantly, listeners showed both faster (replicating CG04) and more accurate (extending CG04) comprehension of this talker. Experiment 2 revealed evidence that such adaptation transferred to a different talker of a same accent. These results highlight the rapidity of short-term accent adaptation and raise new questions about the underlying mechanism. It is suggested that the web-based paradigm provides a useful tool for investigations in speech adaptation.

In this paper, an impedance matching underwater acoustic bend with pentamode microstructure is designed. The proposed bend is assembled by pentamode lattice. The effective density and compressive modulus of each unit cell can be tuned simultaneously, which are modulated to guarantee both the bending effect and high transmission. The standard deviations (SDs) of transmitted phase are calculated to quantitatively evaluate the degree of the distortion of the transmitted wavefront, while the transmission is calculated to appraise the degree of acoustic impedance matching. The low SDs and high transmission indicate that the designed bend has a nice broadband bending effect and is impedance-matched to water. This design has potential applications in underwater communication and underwater detection.

Researchers investigating the vowel systems of languages or dialects frequently employ normalization methods to minimize between-speaker variability in formant patterns while preserving between-phoneme separation and (socio-)dialectal variation. Here two methods are considered: log-mean and Lobanov normalization. Although both of these methods express formants in a speaker-dependent space, the methods differ in their complexity and in their implied models of human vowel-perception. Typical implementations of these methods rely on balanced data across speakers so that researchers may have to reduce the data available in the analyses in missing-data situations. Here, an alternative method is proposed for the normalization of vowels using the log-mean method in a linear-regression framework. The performance of the traditional approaches to log-mean and Lobanov normalization against the regression approach to the log-mean method using naturalistic, simulated vowel-data was investigated. The results indicate that the Lobanov method likely removes legitimate linguistic variation from…

The elastodynamic behavior of polycrystalline cubic materials is studied through the fundamental propagation properties, the attenuation and wave speed, of a longitudinal wave. Predictions made by different analytical models are compared to both numerical and experimental results. The numerical model is based on a three-dimensional Finite Element (FE) simulation which provides a full-physics solution to the scattering problem. The three main analytical models include the Far-Field Approximation (FFA), the Self-Consistent Approximation (SCA) to the reference medium, and the herein derived Second Order Approximation (SOA). The classic Stanke and Kino model is also included, which by comparison to the SOA, reveals the importance of the distribution of length-scales described in terms of the two-point correlation function in determining scattering behavior. Further comparison with the FE model demonstrates that the FFA provides a simple but satisfactory approximation, whereas the SOA shows all-around excellent agreement. The experimental wave velocity data evaluated against the SOA and…

Research shows that the sight of trees and the sound of moving water improve the soundscape quality of outdoor spaces exposed to road traffic noise. Effects are attributed to non-energetic masking, visual attentional distortion, and congruence between sight and hearing. However, there is no literature on such effects for aircraft noise. Aircraft noise varies from other traffic sources, i.e., in terms temporal variability, duration, and spectral composition, complicating the application of findings without further research. In a virtual reality experiment reported in this article, participants were asked to rate scenarios with different sound levels of flyovers, urban typologies, vegetation, and/ or water features. The results showed a significant improvement of the soundscape quality when (1) vegetation and (2) moving water were present, and especially when (3) vegetation and moving water were presented simultaneously, especially for residential areas in terms of the relative change. Moving water also reduced the saliency of aircraft flyovers significantly, changing the…

A striation-based method with a vertical line array is proposed for source depth estimation. Broadband striation structures of direct and surface-reflected arrivals after propagating to receivers near the ocean bottom are applied. A tracking algorithm for the striation structures is proposed based on the extended Kalman filter. A cost function for source depth estimation is presented by matching the traces of the measured striations with a library of model-based traces under different source depths. The method is demonstrated on array data collected during an acoustic research experiment in the South China Sea in 2016.

Wideband direction of arrival (DOA) estimation using a sensor array plays a fundamental role in passive sonar signal processing. Although sparsity-based DOA estimation methods can attain high resolution in the condition of few snapshots and low signal-to-noise ratio, the localization accuracy is seriously affected by strong interferences. In this paper, a matrix filter with nulling (MFN) is used to pass weak targets in sector-of-interest (passband) while attenuating the out-of-sector (stopband) interferences by forming deep nulls toward the directions of interferences adaptively. Then, a method based on sparse spectrum fitting (SpSF) and MFN is proposed to localize closely spaced wideband signals in a strong interference environment. In comparison with the minimum variance distortionless response and SpSF, the proposed method achieves higher localization accuracy, which is verified by simulation and experimental results.

Compressive sensing (CS) based estimation technique utilizes a sparsity promoting constraint and solves the direction-of-arrival (DOA) estimation problem efficiently with high resolution. In this paper a grid free CS based DOA estimation technique is proposed, which uses sequential multiple snapshot data. Conventional CS technique suffers from a basis mismatch issue, while grid free CS technique is relieved of basis mismatch problem. Moreover, when the DOAs are stationary, multiple snapshot processing provides stable estimates over fluctuating single snapshot processing results. For multiple snapshot processing, the generalized version of total variation norm (group total variation norm) is implemented to impose a common sparsity pattern of multiple snapshot solution vectors in a continuous angular domain. Furthermore, an extended version is proposed using the singular value decomposition technique to mitigate computational complexity resulting from a large number of multiple snapshots. Data from SWellEx-96 are used to examine the proposed method. From the experimental data, it was…

Various adverse symptoms resulting from exposure to very high-frequency sound (VHFS) and ultrasound (US) have previously been reported. This study aimed to establish whether these symptoms are experienced under controlled laboratory conditions and are specific to VHFS/US. To do this, participants were exposed to VHFS/US (at frequencies between 13.5 and 20 kHz and sound pressure levels between 82 and 92 dB) and to a 1 kHz reference stimulus, both at 25 dB above their hearing threshold. The VHFS/US and reference stimuli were presented 4 times, each time for 3 min, during which participants performed a sustained attention task, rated their symptom severity, and had their galvanic skin response (GSR) measured to assess their level of anxiety. Prior to exposure, participants were assigned either to a symptomatic or an asymptomatic group, based on their prior history of symptoms that they attributed to VHFS/US. In both groups, overall discomfort ratings were higher in the VHFS/US condition than the reference condition. In the symptomatic group only, difficulty concentrating and annoyance…

The need of tuning into speech in noisy and reverberant classrooms is a challenge for good speech communication and literacy development at school. Reading development can be compromised if children are exposed to inadequate acoustics, especially those with poor neural processing in speech discrimination. This work reports preliminary results on the influence of classroom acoustics on the reading speed of 94 Italian second-graders. Speech clarity (C50) was found to be significantly correlated with all the investigated reading tasks, while no significant correlations were found with reverberation time.

This letter deals with the problem of differential beamforming with microphone arrays of arbitrary planar geometry. By approximating the beampattern with the Jacobi-Anger expansion, it develops an algorithm that can form any specified frequency-invariant beampattern with a microphone array of any planar geometry as long as the sensors' coordinates are given and the spacing between neighboring sensors is smaller than the smallest wavelength. This method is rather general and it can be used to design differential beamformers with linear, circular, and concentric circular differential microphone arrays as well as differential arrays of arbitrary planar geometry where sensors are placed in any specified positions.

The Waveguide Invariant (WI) theory has been introduced to quantify the orientation of the intensity interference patterns in a range-frequency domain. When the sound speed is constant over the water column, the WI is a scalar with the canonical value of 1. But, when considering shallow waters with a stratified sound speed profile, the WI ceases to be constant and is more appropriately described by a distribution, which is mainly sensitive to source/receiver depths. Such configurations have been widely investigated, with practical applications including passive source localization. However, in deep waters, the interference pattern is much more complex and variable. In fact the observed WI varies with source/receiver depth but it also varies very quickly with source-array range. In this paper, the authors investigate two phenomena responsible for this variability, namely the dominance of the acoustic field by groups of modes and the frequency dependence of the eigenmodes. Using a ray-mode approach, these two features are integrated in a WI distribution derivation. Their importance in…

, 547-557] showed that speech reception thresholds (SRTs) in noise, obtained with normal-hearing listeners, were significantly higher with hearing aids (HAs) than without. Some listeners reported a change in their spatial perception of the stimuli due to the HA processing, with auditory images often being broader and closer to the head or even internalized. The current study investigated whether worse speech intelligibility with HAs might be explained by distorted spatial perception and the resulting reduced ability to spatially segregate the target speech from the interferers. SRTs were measured in normal-hearing listeners with or without HAs in the presence of three interfering talkers or speech-shaped noises. Furthermore, listeners were asked to sketch their spatial perception of the acoustic scene. Consistent with the previous study, SRTs increased with HAs. Spatial release from masking was lower with HAs than without. The effects were similar for noise and speech maskers and appeared to be accounted for by changes to energetic masking. This interpretation was supported by…

Evaluation of the performance of computer-based algorithms to automatically detect mammalian vocalizations often relies on comparisons between detector outputs and a reference data set, generally obtained by manual annotation of acoustic recordings. To explore the reproducibility of these annotations, inter- and intra-analyst variability in manually annotated Antarctic blue whale (ABW) Z-calls are investigated by two analysts in acoustic data from two ocean basins representing different scenarios in terms of call abundance and background noise. Manual annotations exhibit strong inter- and intra-analyst variability, with less than 50% agreement between analysts. This variability is mainly caused by the difficulty of reliably and reproducibly distinguishing single calls in an ABW chorus made of overlaying distant calls. Furthermore, the performance of two automated detectors, based on spectrogram correlation or subspace-detection strategy, is evaluated by comparing detector output to a "conservative" manually annotated reference data set, which comprises only analysts' matching…

Although many fish are soniferous, few of their sounds have been identified, making passive acoustic monitoring (PAM) ineffective. To start addressing this issue, a portable 6-hydrophone array combined with a video camera was assembled to catalog fish sounds in the wild. Sounds are detected automatically in the acoustic recordings and localized in three dimensions using time-difference of arrivals and linearized inversion. Localizations are then combined with the video to identify the species producing the sounds. Uncertainty analyses show that fish are localized near the array with uncertainties < 50 cm. The proposed system was deployed off Cape Cod, MA and used to identify sounds produced by tautog (Tautoga onitis), demonstrating that the methodology can be used to build up a catalog of fish sounds that could be used for PAM and fisheries management.

Guided waves are used for the non-destructive evaluation in automotive and aerospace industries. There is a trend leaning away from isotropic materials to the manufacturing based on composites. However, the elastic wave dynamics in such materials is considerably more complicated. Much effort has been committed to the calculation of guided waves' dispersion curves in composites. Lots of methods and tools are available, but it becomes difficult when there are more than one hundred layers. In this paper the calculation of dispersion diagrams and mode shapes using the stiffness matrix method is demonstrated. Boundary conditions are implemented into the stiffness matrix method that allow for the separate tracing of the various mode families. Shear horizontal modes are modeled with the transfer matrix method without facing any numerical instability. It is elucidated just how the occurrence of the mode families depends on the system's symmetry and wave propagation direction. As a result, the robustness and reliability of guided wave modeling by using the stiffness method is improved, and…

Clinical tests of cochlear implant (CI) outcomes in sentence recognition cannot fully reflect CI users' self-reported quality of life (QoL). Here, vocal emotion recognition scores, speech reception thresholds (SRTs), and demographic factors were tested as predictors of QoL scores assessed with the Nijmegen Cochlear Implant Questionnaire in postlingually deafened adult CI users. After correction for multiple comparisons, vocal emotion recognition scores were significantly correlated with QoL scores in all subdomains (social interaction, self-esteem, etc.), while SRTs and duration of CI use were not. Vocal emotion recognition may thus be used in clinic to accurately and broadly predict QoL with CIs.

This study investigates the hypothesis that speakers make active use of the visual modality in production to improve their speech intelligibility in noisy conditions. Six native speakers of Canadian French produced speech in quiet conditions and in 85 dB of babble noise, in three situations: interacting face-to-face with the experimenter (AV), using the auditory modality only (AO), or reading aloud (NI, no interaction). The audio signal was recorded with the three-dimensional movements of their lips and tongue, using electromagnetic articulography. All the speakers reacted similarly to the presence vs absence of communicative interaction, showing significant speech modifications with noise exposure in both interactive and non-interactive conditions, not only for parameters directly related to voice intensity or for lip movements (very visible) but also for tongue movements (less visible); greater adaptation was observed in interactive conditions, though. However, speakers reacted differently to the availability or unavailability of visual information: only four speakers enhanced…

Sparse reconstruction methods, such as Compressive Sensing, are powerful methods in acoustic array processing, as they make wideband reconstruction possible. However, when addressing sound fields that are not necessarily sparse (e.g., in acoustic near-fields, reflective environments, extended sources, etc.), the methods can lead to a poor reconstruction of the sound field. This study examines the use of sparse analysis priors to promote block-sparse solutions. In particular, a Fused Total Generalized Variation (F-TGV) method is developed, to analyze the sound field in the near-field of acoustic sources. The method promotes sparsity both on the spatial derivatives of the solution and on the solution itself, thus seeking solutions where the non-zero coefficients are grouped together. The performance of the method is examined numerically and experimentally, and compared with established methods. The results indicate that the F-TGV method is suitable to examine both compact and spatially extended sources. The method is promising for its generality, robustness to noise, and the…

Recently, deep learning based speech segregation has been shown to improve human speech intelligibility in noisy environments. However, one important factor not yet considered is room reverberation, which characterizes typical daily environments. The combination of reverberation and background noise can severely degrade speech intelligibility for hearing-impaired (HI) listeners. In the current study, a deep learning based time-frequency masking algorithm was proposed to address both room reverberation and background noise. Specifically, a deep neural network was trained to estimate the ideal ratio mask, where anechoic-clean speech was considered as the desired signal. Intelligibility testing was conducted under reverberant-noisy conditions with reverberation time T60 = 0.6 s, plus speech-shaped noise or babble noise at various signal-to-noise ratios. The experiments demonstrated that substantial speech intelligibility improvements were obtained for HI listeners. The algorithm was also somewhat beneficial for normal-hearing (NH) listeners. In addition, sentence intelligibility scores…

Research on vocal alignment, the tendency for language users to match another individual's speech productions, suggests that multiple factors contribute to this behavior. Social and motivational goals, aspects of cognitive architecture, and linguistic flexibility may all affect the extent to which vocal alignment occurs, suggesting complex underlying mechanisms. The present study capitalized on the social and linguistic characteristics of Spanish-accented English to examine the relationship among these contributors to vocal alignment. American English-speaking adults participated in a shadowing task. Degree of vocal alignment was assessed by both acoustic measures and independent raters' judgments. Participants aligned to both native English and Spanish-accented productions, despite differences in attitudes to and intelligibility of the different accents. Individual differences in shadowers' vowel dispersion were also related to extent of vocal alignment, with greater dispersion associated with greater alignment. Acoustic measures were related to perceptual assessments of alignment…