The 50 most-cited articles in The Journal of the Acoustical Society of America, 2020

Face masks muffle speech and make communication more difficult, especially for people with hearing loss. This study examines the acoustic attenuation caused by different face masks, including medical, cloth, and transparent masks, using a head-shaped loudspeaker and a live human talker. The results suggest that all masks attenuate frequencies above 1 kHz, that attenuation is greatest in front of the talker, and that there is substantial variation between mask types, especially cloth masks with different materials and weaves. Transparent masks have poor acoustic performance compared to both medical and cloth masks. Most masks have little effect on lapel microphones, suggesting that existing sound reinforcement and assistive listening systems may be effective for verbal communication with masks.

Wearing face masks (alongside physical distancing) provides some protection against infection from COVID-19. Face masks can also change how people communicate and subsequently affect speech signal quality. This study investigated how three common face mask types (N95, surgical, and cloth) affected acoustic analysis of speech and perceived intelligibility in healthy subjects. Acoustic measures of timing, frequency, perturbation, and power spectral density were measured. Speech intelligibility and word and sentence accuracy were also examined using the Assessment of Intelligibility of Dysarthric Speech. Mask type impacted the power distribution in frequencies above 3 kHz for the N95 mask, and above 5 kHz in surgical and cloth masks. Measures of timing and spectral tilt mainly differed with N95 mask use. Cepstral and harmonics to noise ratios remained unchanged across mask type. No differences were observed across conditions for word or sentence intelligibility measures; however, accuracy of word and sentence translations were affected by all masks. Data presented in this study show…

This paper examines the relationship between conventional beamforming and linear supervised learning, then develops a nonlinear deep feed-forward neural network (FNN) for direction-of-arrival (DOA) estimation. First, conventional beamforming is reformulated as a real-valued, linear inverse problem in the weight space, which is compared to a support vector machine and a linear FNN model. In the linear formulation, DOA is quickly and accurately estimated for a realistic array calibration example. Then, a nonlinear FNN is developed for two-source DOA and for K-source DOA, where K is unknown. Two training methodologies are used: exhaustive training for controlled accuracy and random training for flexibility. The number of FNN model hidden layers, hidden nodes, and activation functions are selected using a hyperparameter search. In plane wave simulations, the 2-source FNN resolved incoherent sources with 1° resolution using a single snapshot, similar to Sparse Bayesian Learning (SBL). With multiple snapshots, K-source FNN achieved resolution and accuracy similar to Multiple Signal…

Offshore wind turbines are increasingly abundant sources of underwater low frequency noise. This increase raises concern for the cumulative contribution of wind farms to the underwater soundscape and possible impact on marine ecosystems. Here, available measurements of underwater noise from different wind turbines during operation are reviewed to show that source levels are at least 10-20 dB lower than ship noise in the same frequency range. The most important factor explaining the measured sound pressure levels from wind turbines is distance to the turbines with smaller effects of wind speed and turbine size. A simple multi-turbine model demonstrates that cumulative noise levels could be elevated up to a few kilometres from a wind farm under very low ambient noise conditions. In contrast, the noise is well below ambient levels unless it is very close to the individual turbines in locations with high ambient noise from shipping or high wind speeds. The rapid increase in the number and size of offshore wind farms means that the cumulative contribution from the many turbines may be…

The lockdown that Madrid has suffered during the months of March to June 2020 to try to control and minimize the spread of COVID-19 has significantly altered the acoustic environment of the city. The absence of vehicles and people on the streets has led to a noise reduction captured by the monitoring network of the City of Madrid. In this article, an analysis has been carried out to describe the reduction in noise pollution that has occurred and to analyze the changes in the temporal patterns of noise, which are strongly correlated with the adaptation of the population's activity and behavior to the new circumstances. The reduction in the sound level ranged from 4 to 6 dBA for the indicators Ld, Le, and Ln, and this is connected to a significant variation in the daily time patterns, especially during weekends, when the activity started earlier in the morning and lasted longer at midday, decreasing significantly in the afternoon.

This study explored the effects of wearing face masks on classroom communication. The effects of three different types of face masks (fabric, surgical, and N95 masks) on speech intelligibility (SI) presented to college students in auralized classrooms were evaluated. To simulate realistic classroom conditions, speech stimuli were presented in the presence of speech-shaped noise with a signal-to-noise ratio of +3 dB under two different reverberation times (0.4 s and 3.1 s). The use of fabric masks yielded a significantly greater reduction in SI compared to the other masks. Therefore, surgical masks or N95 masks are recommended in teaching environments.

Over a decade after the Cook Inlet beluga (Delphinapterus leucas) was listed as endangered in 2008, the population has shown no sign of recovery. Lack of ecological knowledge limits the understanding of, and ability to manage, potential threats impeding recovery of this declining population. National Oceanic and Atmospheric Administration Fisheries, in partnership with the Alaska Department of Fish and Game, initiated a passive acoustics monitoring program in 2017 to investigate beluga seasonal occurrence by deploying a series of passive acoustic moorings. Data have been processed with semi-automated tonal detectors followed by time intensive manual validation. To reduce this labor intensive and time-consuming process, in addition to increasing the accuracy of classification results, the authors constructed an ensembled deep learning convolutional neural network model to classify beluga detections as true or false. Using a 0.5 threshold, the final model achieves 96.57% precision and 92.26% recall on testing dataset. This methodology proves to be successful at classifying beluga…

In the Northern Horpa (NH) language of Sichuan, vowels are divided between plain and pharyngealized sets, with the latter pronounced with auxiliary articulatory gestures involving more constriction in the vocal tract. The current study examines how the NH vocalic contrast is manifested in line with the process of pharyngealization both acoustically and articulatorily, based on freshly gathered data from two varieties of the language (i.e., Rtsangkhog and Yunasche). Along with formant analyses, ultrasound imaging was employed to capture the tongue postures and positions during vowel production. The results show that in contrast with plain vowels, pharyngealized vowels generally feature lower F2 values and higher F1 and F3 values. Mixed results for F2 and F3 suggest that the quality contrasts are vowel-dependent. Ultrasound images, on the other hand, reveal that the vocalic distinction is affected by different types of tongue movements, including retraction, backing, and double bunching, depending on the inherent tongue positions for each vowel. The two NH varieties investigated are…

Classical ocean acoustic experiments involve the use of synchronized arrays of sensors. However, the need to cover large areas and/or the use of small robotic platforms has evoked interest in single-hydrophone processing methods for localizing a source or characterizing the propagation environment. One such processing method is "warping," a non-linear, physics-based signal processing tool dedicated to decomposing multipath features of low-frequency transient signals (frequency f < 500 Hz), after their propagation through shallow water (depth D < 200 m) and their reception on a distant single hydrophone (range r > 1 km). Since its introduction to the underwater acoustics community in 2010, warping has been adopted in the ocean acoustics literature, mostly as a pre-processing method for single receiver geoacoustic inversion. Warping also has potential applications in other specialties, including bioacoustics; however, the technique can be daunting to many potential users unfamiliar with its intricacies. Consequently, this tutorial article covers basic warping theory, presents…

A multi-task learning (MTL) method with adaptively weighted losses applied to a convolutional neural network (CNN) is proposed to estimate the range and depth of an acoustic source in deep ocean. The network input is the normalized sample covariance matrices of the broadband data received by a vertical line array. To handle the environmental uncertainty, both the training and validation data are generated by an acoustic propagation model based on multiple possible sets of environmental parameters. The sensitivity analysis is investigated to examine the effect of mismatched environmental parameters on the localization performance in the South China Sea environment. Among the environmental parameters, the array tilt is found to be the most important factor on the localization. Simulation results demonstrate that, compared with the conventional matched field processing (MFP), the CNN with MTL performs better and is more robust to array tilt in the deep-ocean environment. Tests on real data from the South China Sea also validate the method. In the specific ranges where the MFP fails,…

This paper proposes a strategy to broaden the sound absorption region of porous materials by embedding ribs. The theoretical solution and the numerical simulations of the optimization model show that the composite metastructure exhibits ultra-wide high absorption characteristics and an average sound absorption coefficient of 0.937 in the 0-10 kHz range upon its teaching-learning-based optimization. High sound pressures are present only among the embedded ribs. A significant slowing down of the sound takes place inside the metastructure. The impedance tube test confirms the design of the broadband sound absorption region in agreement with the teaching-learning-based optimization method.

In this paper, a deep-learning-based method for sound field reconstruction is proposed. The possibility to reconstruct the magnitude of the sound pressure in the frequency band 30-300 Hz for an entire room by using a very low number of irregularly distributed microphones arbitrarily arranged is shown. Moreover, the approach is agnostic to the location of the measurements in the Euclidean space. In particular, the presented approach uses a limited number of arbitrary discrete measurements of the magnitude of the sound field pressure in order to extrapolate this field to a higher-resolution grid of discrete points in space with a low computational complexity. The method is based on a U-net-like neural network with partial convolutions trained solely on simulated data, which itself is constructed from numerical simulations of Green's function across thousands of common rectangular rooms. Although extensible to three dimensions and different room shapes, the method focuses on reconstructing the two-dimensional plane of a rectangular room from measurements of the three-dimensional sound…

A slowdown in global trade activity due to COVID-19 has led to a reduction in commercial shipping traffic into the Port of Vancouver. The Ocean Networks Canada observatory system provides researchers real-time access to oceanographic data from a wide range of instruments including hydrophones located along the offshore and inshore approaches to Vancouver. Measurements of power spectral density at 100 Hz from four of these bottom mounted hydrophones are presented, along with AIS data and shipping and trade statistics to assess to what extent the economic impact of COVID-19 can be observed acoustically and in near real-time. The quarterly trend in median weekly noise power in the shipping band of frequencies shows that a reduction in noise commensurate with the economic slowdown has been observed at three of the four hydrophone stations.

Noise mitigation of stage machinery can be quite demanding and requires innovative solutions. In this work, an acoustic metamaterial capsule is proposed to reduce the noise emission of several stage machinery drive trains, while still allowing the ventilation required for cooling. The metamaterial capsule consists of c-shape meta-atoms, which have a simple structure that facilitates manufacturing. Two different metamaterial capsules are designed, simulated, manufactured, and experimentally validated that utilize an ultra-sparse and air-permeable reflective meta-grating. Both designs demonstrate transmission loss peaks that effectively suppress gear mesh noise or other narrow band noise sources. The ventilation by natural convection was numerically verified, and was shown to give adequate cooling, whereas a conventional sound capsule would lead to overheating. The noise spectra of three common stage machinery drive trains are numerically modelled, enabling one to design meta-gratings and determine their noise suppression performance. The results fulfill the stringent stage machinery…

The present study investigates to what extent acoustic cues to word stress facilitate both offline and online word processing in Papuan Malay. Previous production research has shown acoustic evidence for word-stress patterns in this language, counter to earlier predictions. A discussion of the literature on word stress perception and word stress in Papuan Malay is provided and complemented with reports of three word recognition tasks. The first two presented sequences of acoustically manipulated syllable dyads to native listeners in an offline word recognition task. This was done in order to investigate the individual contribution of each of the acoustic cues (F0, duration, intensity, spectral tilt) to the perception of word stress. F0 appeared a relevant cue when stimuli were embedded in a phrase, not in isolation. A follow-up reaction time experiment (online processing) investigated to what extent word recognition was facilitated when either an acoustically weak or an acoustically strong syllable was the cue to identify a word. Reaction times were shorter for strong syllables than…

Passive acoustics provides a powerful tool for monitoring the endangered North Atlantic right whale (Eubalaena glacialis), but robust detection algorithms are needed to handle diverse and variable acoustic conditions and differences in recording techniques and equipment. This paper investigates the potential of deep neural networks (DNNs) for addressing this need. ResNet, an architecture commonly used for image recognition, was trained to recognize the time-frequency representation of the characteristic North Atlantic right whale upcall. The network was trained on several thousand examples recorded at various locations in the Gulf of St. Lawrence in 2018 and 2019, using different equipment and deployment techniques. Used as a detection algorithm on fifty 30-min recordings from the years 2015-2017 containing over one thousand upcalls, the network achieved recalls up to 80% while maintaining a precision of 90%. Importantly, the performance of the network improved as more variance was introduced into the training dataset, whereas the opposite trend was observed using a conventional…

Phrase-level prosody serves two essential functions in many languages of the world: chunking information into units (demarcating) and marking important information (highlighting). Recent work suggests that prosody has a mainly demarcating function in the Trade Malay language family. That is, the use of pitch accents in these languages is limited or absent, as the main prosodic events occur on the final two syllables in a phrase. The current study investigates the extent to which Papuan Malay phrase prosody is used for demarcating and highlighting, taking into account the potential influence of word stress. This is done by means of acoustic analyses on a corpus of spontaneous speech. Both the form (F0 movement) and the possible functions (demarcating and highlighting) of the final two syllables in Papuan Malay phrases are investigated. Although most results favor the demarcating function of Papuan Malay phrase prosody, a highlighting function cannot be ruled out. The results suggest that Papuan Malay might hold an exceptional position in the typology of prosodic prominence.

Unfamiliar second-language (L2) accents present a common challenge to speech understanding. However, the extent to which accurately recognized unfamiliar L2-accented speech imposes a greater cognitive load than native speech remains unclear. The current study used pupillometry to assess cognitive load for native English listeners during the perception of intelligible Mandarin Chinese-accented English and American-accented English. Results showed greater pupil response (indicating greater cognitive load) for the unfamiliar L2-accented speech. These findings indicate that the mismatches between unfamiliar L2-accented speech and native listeners' linguistic representations impose greater cognitive load even when recognition accuracy is at ceiling.

With the COVID-19 pandemic, the wearing of face masks covering mouth and nose has become ubiquitous all around the world. This study investigates the impact of typical face masks on voice radiation. To analyze the transmission loss caused by masks and the influence of masks on directivity, this study measured the full-spherical voice directivity of a dummy head with a mouth simulator covered with six masks of different types, i.e., medical masks, filtering facepiece respirator masks, and cloth face coverings. The results show a significant frequency-dependent transmission loss, which varies depending on the mask, especially above 2 kHz. Furthermore, the two facepiece respirator masks also significantly affect speech directivity, as determined by the directivity index (DI). Compared to the measurements without a mask, the DI deviates by up to 7 dB at frequencies above 3 kHz. For all other masks, the deviations are below 2 dB in all third-octave frequency bands.

The identification of acoustic sources in a three-dimensional (3D) domain based on measurements with an array of microphones is a challenging problem: it entails the estimation of the angular position of the sources (direction of arrival), distance relative to the array (range), and the quantification of the source amplitudes. A 3D source localization model using a rigid spherical microphone array with spherical wave propagation is proposed. In this study, sparse Bayesian learning is used to perform localization in 3D space and examine the use of principal component analysis to denoise the measurement data. The performance of the proposed method is examined numerically and experimentally, which is tested both in a free-field and in a reverberant environment. The numerical and experimental investigations demonstrate that the approach offers accurate localization in a 3D domain, resolving closely spaced sources and making it possible to identify sources located at different ranges.

In this work, model-based methods are employed, along with machine learning techniques, to classify sediments in oceanic environments based on the geoacoustic properties of a two-layer seabed. Two different scenarios are investigated. First, a simple low-frequency case is set up, in which the acoustic field is modeled with normal modes. Four different hypotheses are made for seafloor sediment possibilities, and these are explored using both various machine learning techniques and a simple matched-field approach. For most noise levels, the latter has an inferior performance to the machine learning methods. Second, the high-frequency model of the scattering from a rough, two-layer seafloor is considered. Again, four different sediment possibilities are classified with machine learning. For higher accuracy, one-dimensional convolutional neural networks are employed. In both cases, the machine learning methods, both in simple and more complex formulations, lead to effective sediment characterization. The results assess the robustness to noise and model misspecification of different…

One way music is thought to convey emotion is by mimicking acoustic features of affective human vocalizations [Juslin and Laukka (2003). Psychol. Bull. 129(5), 770-814]. Regarding fear, it has been informally noted that music for scary scenes in films frequently exhibits a "scream-like" character. Here, this proposition is formally tested. This paper reports acoustic analyses for four categories of audio stimuli: screams, non-screaming vocalizations, scream-like music, and non-scream-like music. Valence and arousal ratings were also collected. Results support the hypothesis that a key feature of human screams (roughness) is imitated by scream-like music and could potentially signal danger through both music and the voice.

Underwater sounds from human sources can have detrimental effects upon aquatic animals, including fishes. Thus, it is important to establish sound exposure criteria for fishes, setting out those levels of sound from different sources that have detrimental effects upon them, in order to support current and future protective regulations. This paper considers the gaps in information that must be resolved in order to establish reasonable sound exposure criteria for fishes. The vulnerability of fishes is affected by the characteristics of underwater sounds, which must be taken into account when evaluating effects. The effects that need to be considered include death and injuries, physiological effects, and changes in behavior. Strong emphasis in assessing the effects of sounds has been placed upon the hearing abilities of fishes. However, although hearing has to be taken into account, other actual effects also have to be considered. This paper considers the information gaps that must be filled for the development of future guidelines and criteria.

Voice onset time (VOT) is an acoustic property of stop consonants that is commonly manipulated in studies of phonetic perception. This paper contains a thorough description of the "progressive cutback and replacement" method of VOT manipulation, and comparison with other VOT manipulation techniques. Other acoustic properties that covary with VOT-such as fundamental frequency and formant transitions-are also discussed, along with considerations for testing VOT perception and its relationship to various other measures of auditory temporal or spectral processing. An implementation of the progressive cutback and replacement method in the Praat scripting language is presented, which is suitable for modifying natural speech for perceptual experiments involving VOT and/or related covarying F0 and intensity cues. Justifications are provided for the stimulus design choices and constraints implemented in the script.

The clinical relevance of lung ultrasonography (LUS) has been rapidly growing since the 1990s. However, LUS is mainly based on the evaluation of visual artifacts (also called B-lines), leading to subjective and qualitative diagnoses. The formation of B-lines remains unknown and, hence, researchers need to study their origin to allow clinicians to quantitatively evaluate the state of lungs. This paper investigates an ambiguity about the formation of B-lines, leading to the formulation of two main hypotheses. The first hypothesis states that the visualization of these artifacts is linked only to the dimension of the emitted beam, whereas the second associates their appearance to specific resonance phenomena. To verify these hypotheses, the frequency spectrum of B-lines was studied by using dedicated lung-phantoms. A research programmable platform connected to an LA533 linear array probe was exploited both to implement a multifrequency approach and to acquire raw radio frequency data. The strength of each artifact was measured as a function of frequency, focal point, and transmitting…

The open porosity of air-saturated acoustical porous materials is estimated from the low-frequency or high-frequency asymptotes of the real part of the dynamic bulk modulus. Combining this technique with the estimation of the static air-flow resistivity from the low-frequency asymptote of the imaginary part of the dynamic mass density and the analytical inversions of the remaining parameters from the dynamic mass density and bulk modulus [methods introduced by Panneton and Olny, J. Acoust. Soc. Am. 119(4), 2027-2040 (2006) and Olny and Panneton 123(2), 814-824 (2008)], this work estimates all six parameters of a Johnson-Champoux-Allard-Lafarge model from impedance tube measurements. A classical two-microphone impedance tube, as well as three- or four-microphone tubes, can be used for these measurements and estimations. Examples of applications and limits of the method are presented and a tool to estimate the open porosity and the static air-flow resistivity is made available online.

In ocean acoustics, many types of optimizations have been employed to locate acoustic sources and estimate the properties of the seabed. How these tasks can take advantage of recent advances in deep learning remains as open questions, especially due to the lack of labeled field data. In this work, a Convolutional Neural Network (CNN) is used to find seabed type and source range simultaneously from 1 s pressure time series from impulsive sounds. Simulated data are used to train the CNN before application to signals from a single hydrophone signal during the 2017 Seabed Characterization Experiment. The training data includes four seabeds representing deep mud, mud over sand, sandy silt, and sand, and a wide range of source parameters. When applied to measured data, the trained CNN predicts expected seabed types and obtains ranges within 0.5 km when the source-receiver range is greater than 5 km, showing the potential for such algorithms to address these problems.

In deep-sea source localization, some of the existing methods only estimate the source range, while the others produce large errors in distance estimation when estimating both the range and depth. Here, a convolutional neural network-based method with high accuracy is introduced, in which the source localization problem is solved as a regression problem. The proposed neural network is trained by a normalized acoustic matrix and used to predict the source position. Experimental data from the western Pacific indicate that this method performs satisfactorily: the mean absolute percentage error of the range is 2.10%, while that of the depth is 3.08%.

An experimental campaign was undertaken to identify the effects posed by flow recirculation on the dynamic performance and acoustic emissions of an isolated rotor, operating in hover in a sealed anechoic chamber. It is shown that flow recirculation is an artifact of testing rotary-wing systems in an enclosed environment, and results in a significant amplification of tonal and broadband noise components. The acoustic emissions produced while the recirculated flow is ingested into the rotor disk vary from those emitted by similar rotors operating in clean inflow conditions. A variety of turbulence suppression screens were employed to impede the propagation of the rotor wake, in an effort to delay the onset of recirculation. This mitigation strategy proved to be effective for one treatment configuration and significantly extended the duration available to acquire clean measurements. The presence of this treatment is thought to alter the coherent structures comprising the recirculated flow and thus the noise emissions following the onset of flow recirculation.

Lung ultrasound imaging is a fast-evolving field of application for ultrasound technologies. However, most diagnoses are currently performed with imaging protocols that assume a quasi-homogeneous speed of sound in the volume of interest. When applied to the lung, due to the presence of air, this assumption is unrealistic. Consequently, diagnoses are often based on imaging artifacts and thus qualitative and subjective. In this paper, we present an image formation protocol that is capable of capturing the frequency dependence of well-known artifacts (B-lines) and visualizing it in real time, ultimately providing a quantitative assessment of the signals received from the lung. Previous in vitro studies have shown the potential of B-lines native-frequency for the characterization of bubbly medium, but this paper presents the first results on clinical data. The image formation process has been designed to work on lung tissue, and ultrasound images generated with four orthogonal bands centered at 3, 4, 5 and 6 MHz can be acquired and displayed in real time. Results show that B-lines can…

Over 500 000 automated and manual acoustic localizations, measured over seven years between 2008 and 2014, were used to examine how natural wind-driven noise and anthropogenic seismic airgun survey noise influence bowhead whale call densities (calls/km2/min) and source levels during their fall migration in the Alaskan Beaufort Sea. Noise masking effects, which confound measurements of behavioral changes, were removed using a modified point transect theory. The authors found that mean call densities generally rose with increasing continuous wind-driven noise levels. The occurrence of weak airgun pulse sounds also prompted an increase in call density equivalent to a 10–15 dB change in natural noise level, but call density then dropped substantially with increasing cumulative sound exposure level (cSEL) from received airgun pulses. At low in-band noise levels the mean source level of the acoustically-active population changed to nearly perfectly compensate for noise increases, but as noise levels increased further the mean source level failed to keep pace, reducing the population's…

Better understanding of elastic wave propagation in polycrystals has interest for applications in seismology and nondestructive material characterization. In this study, a second-order wave propagation (SOA) model that considers forward multiple scattering events is developed for macroscopically isotropic polycrystals with equiaxed grains of arbitrary anisotropy (triclinic). It predicts scattering-induced wave attenuation and dispersion of phase velocity. The SOA model implements the generalized two-point correlation (TPC) function, which relates to the actual numeric TPC of simulated microstructure. The analytical Rayleigh and stochastic asymptotes for both attenuation and phase velocity are derived for triclinic symmetry grains, which elucidate the effects of the elastic scattering factors and the generalized TPC in different frequency regimes. Also, the computationally efficient far field approximation attenuation model is obtained for this case; it shows good agreement with the SOA model in all frequency ranges. To assess the analytical models, a three-dimensional (3D) finite…

Three-dimensional finite element (FE) modelling, with representation of materials at grain scale in realistic sample volumes, is capable of accurately describing elastic wave propagation and scattering within polycrystals. A broader and better future use of this FE method requires several important topics to be fully understood, and this work presents studies addressing this aim. The first topic concerns the determination of effective media parameters, namely, scattering induced attenuation and phase velocity, from measured coherent waves. This work evaluates two determination approaches, through-transmission and fitting, and it is found that these approaches are practically equivalent and can thus be used interchangeably. For the second topic of estimating modelling errors and uncertainties, this work performs thorough analytical and numerical studies to estimate those caused by both FE approximations and statistical considerations. It is demonstrated that the errors and uncertainties can be well suppressed by using a proper combination of modelling parameters. For the last topic…

Many animals increase the intensity of their vocalizations in increased noise. This response is known as the Lombard effect. While some previous studies about cetaceans report a 1 dB increase in the source level (SL) for every dB increase in the background noise level (NL), more recent data have not supported this compensation ability. The purpose of this study was to calculate the SLs of humpback whale song units recorded off Hawaii and test for a relationship between these SLs and background NLs. Opportunistic recordings during 2012-2017 were used to detect and track 524 humpback whale encounters comprised of 83 974 units on the U.S. Navy's Pacific Missile Range Facility hydrophones. Received levels were added to their estimated transmission losses to calculate SLs. Humpback whale song units had a median SL of 173 dB re 1 μPa at 1 m, and SLs increased by 0.53 dB/1 dB increase in background NLs. These changes occurred in real time on hourly and daily time scales. Increases in ambient noise could reduce male humpback whale communication space in the important breeding area off…

Multiple approaches for depth estimation in deep-ocean environments are discussed. First, a multispectral transformation for depth estimation (MSTDE) method based on the low-spatial-frequency interference in a constant sound speed is derived to estimate the source depth directly. To overcome the limitation of real sound-speed profiles and source bandwidths on the accuracy of MSTDE, a method based on a convolution neural network (CNN) and conventional beamforming (CBF) preprocessing is proposed. Further, transfer learning is adapted to tackle the effect of noise on the estimation result. At-sea data are used to test the performance of these methods, and results suggest that (1) the MSTDE can estimate the depth; however, the error increases with distance; (2) MSTDE error can be moderately compensated through a calculated factor; (3) the performance of deep-learning approach using CBF preprocessing is much better than those of MSTDE and traditional CNN.

Strict lockdown strategies to stop the spread of COVID-19 have caused a decrease in environmental noise levels and introduced new noise conditions in dwellings. The present study has investigated the impact of the forced lockdown in Turkey on noise annoyances due to traffic, neighbors, and personal dwellings, as well as the concern of being heard by neighbors, and overall dwelling satisfaction in an online questionnaire. The stress and anxiety levels of respondents were also investigated. The survey obtained 1053 respondents. Additionally, environmental noise levels were measured over 24-h at two locations and compared with results before the pandemic. The results clearly exhibit that environmental noise levels and annoyance due to the noise levels dropped significantly. The annoyance drop was larger in previously noisier environments than previously tranquil locations. Noise annoyance due to neighbor noise did not change significantly; however, noise annoyance due to one's own dwelling increased. The results also confirmed an overall increase in dwelling satisfactions indicating a…

This study aims to determine the degree to which Portable Automated Rapid Testing (PART), a freely available program running on a tablet computer, is capable of reproducing standard laboratory results. Undergraduate students were assigned to one of three within-subject conditions that examined repeatability of performance on a battery of psychoacoustical tests of temporal fine structure processing, spectro-temporal amplitude modulation, and targets in competition. The repeatability condition examined test/retest with the same system, the headphones condition examined the effects of varying headphones (passive and active noise-attenuating), and the noise condition examined repeatability in the presence of recorded cafeteria noise. In general, performance on the test battery showed high repeatability, even across manipulated conditions, and was similar to that reported in the literature. These data serve as validation that suprathreshold psychoacoustical tests can be made accessible to run on consumer-grade hardware and perform in less controlled settings. This dataset also provides a…

Regulations for underwater anthropogenic noise are typically formulated in terms of peak sound pressure, root-mean-square sound pressure, and (weighted or unweighted) sound exposure. Sound effect studies on humans and other terrestrial mammals suggest that in addition to these metrics, the impulsiveness of sound (often quantified by its kurtosis β) is also related to the risk of hearing impairment. Kurtosis is often used to distinguish between ambient noise and transients, such as echolocation clicks and dolphin whistles. A lack of standardization of the integration interval leads to ambiguous kurtosis values, especially for transient signals. In the current research, kurtosis is applied to transient signals typical for high-power underwater noise. For integration time (t2−t1), the quantity (t2−t1)/β is shown to be a robust measure of signal duration, closely related to the effective signal duration, τeff for sounds from airguns, pile driving, and explosions. This research provides practical formulas for kurtosis of impulsive sounds and compares kurtosis between measurements of…

New Orleans English (NOE) has always stood out amongst Southern Englishes, since NOE speakers do not participate in the Southern vowel shift, and instead display features more commonly associated with New York City English. While these traditional features of NOE are on the decline, this study establishes the adoption of a new feature in the dialect that is similarly distinctive within the Gulf South: the pre-voiceless raising of the nucleus of /au/. Based on statistical analyses and consideration of the social context in post-Katrina New Orleans, this paper argues that this feature is a change in progress which appears to pre-date the demographic shifts following Hurricane Katrina, and which arose independently rather than due to contact with /au/-raising speakers. The social and phonetic findings in this paper converge to support arguments for the naturalness of raising in pre-voiceless environments, and for the likelihood of this feature being more widely adopted within the region. Moreover, the presence of Canadian raising of /au/ in NOE represents an additional way that the…

A full-wave model for nonlinear ultrasound propagation through a heterogeneous and absorbing medium in an axisymmetric coordinate system is developed. The model equations are solved using a nonstandard or k-space pseudospectral time domain method. Spatial gradients in the axial direction are calculated using the Fourier collocation spectral method, and spatial gradients in the radial direction are calculated using discrete trigonometric transforms. Time integration is performed using a k-space corrected finite difference scheme. This scheme is exact for plane waves propagating linearly in the axial direction in a homogeneous and lossless medium and significantly reduces numerical dispersion in the more general case. The implementation of the model is described, and performance benchmarks are given for a range of grid sizes. The model is validated by comparison with several analytical solutions. This includes one-dimensional absorption and nonlinearity, the pressure field generated by plane-piston and bowl transducers, and the scattering of a plane wave by a sphere. The general…

The horizontal wavenumbers and modal depth functions are estimated by block sparse Bayesian learning (BSBL) for broadband signals received by a vertical line array in shallow-water waveguides. The dictionary matrix consists of multi-frequency modal depth functions derived from shooting methods given a large set of hypothetical horizontal wavenumbers. The dispersion relation for multi-frequency horizontal wavenumbers is also taken into account to generate the dictionary. In this dictionary, only a few of the entries are used to describe the pressure field. These entries represent the modal depth functions and associated wavenumbers. With the constraint of block sparsity, the BSBL approach is shown to retrieve the horizontal wavenumbers and corresponding modal depth functions with high precision, while a priori knowledge of sea bottom, moving source, and source locations is not needed. The performance is demonstrated by simulations and experimental data.

Large aperture towed arrays are widely used underwater to detect weak targets. During maneuvering, the beamformer performance degrades significantly if a wrong array configuration is assumed. Currently, engineering sensors and/or (augmented) acoustic sources are used to estimate the array element positions. The results are often inadequate depending on the number of measurements available. In this paper, an adaptive bow (AB) sparse Bayesian learning (SBL) algorithm is proposed, called ABSBL. Assuming the towed array follows a parabola shape during slow turns and treating the array bow as a hyperparameter in SBL, the bow and directions of arrival (DOAs) of the signals can be jointly estimated from the received acoustic data. Simulations show that ABSBL yields accurate estimates of the bow and target DOAs if the turning direction is known. ABSBL is applied to the MAPEX2000 data. The estimated array bow and DOA agrees with that estimated from relative time delays measured from acoustic pings and SBL, better than that estimated from the GPS data using the water-pulley model. The method…

A multiple constraint method (MCM) specifically designed to accommodate the uncertainty of array tilt is developed for matched field processing (MFP). Combining the MCM with the white noise gain constraint method results in a processor that is tolerant to both array tilt and environmental mismatch. Experimental results verify the robustness of the proposed MFP to localize and track a surface ship radiating broadband noise (200-500 Hz), using a 56-m long vertical array with tilt in approximately 100-m deep shallow water.

Expressive moments in communicative hand gestures often align with emphatic stress in speech. It has recently been found that acoustic markers of emphatic stress arise naturally during steady-state phonation when upper-limb movements impart physical impulses on the body, most likely affecting acoustics via respiratory activity. In this confirmatory study, participants (N = 29) repeatedly uttered consonant-vowel (/pa/) mono-syllables while moving in particular phase relations with speech, or not moving the upper limbs. This study shows that respiration-related activity is affected by (especially high-impulse) gesturing when vocalizations occur near peaks in physical impulse. This study further shows that gesture-induced moments of bodily impulses increase the amplitude envelope of speech, while not similarly affecting the Fundamental Frequency (F0). Finally, tight relations between respiration-related activity and vocalization were observed, even in the absence of movement, but even more so when upper-limb movement is present. The current findings expand a developing line of research…

In recent years, the current technological improvements of unmanned aerial vehicles (UAV) have made drones more difficult to locate using optical or radio-based systems. However, the sound emitted by UAV motorization and the aerodynamic whistling of the UAVs can be exploited using a microphone array and an adequate real time signal processing algorithm. The proposed method takes advantage of the characteristics of the sound emitted by the UAV. The intrinsic harmonic structure of the emitted sound is exploited by a pitch detection algorithm coupled with zero-phase selective bandpass filtering to detect the fundamental of the signal and to extract its specific harmonics. Although three-dimensional position errors are less when signals are filtered within the antenna bandwidth, experimental measurements show that accurate estimates with only a few selected harmonics in the signal can be obtained with the localization process. Kalman filtering is used to smooth the estimates.

This study investigated the effects of cochlear implant (CI) electrode array type and scalar location on the number of channels available to CI recipients for maximum speech understanding and sound quality. Eighteen post-lingually deafened adult CI recipients participated, including 11 recipients with straight electrode arrays entirely in scala tympani and 7 recipients with translocated precurved electrode arrays. Computerized tomography was used to determine electrode placement and scalar location. In each condition, the number of channels varied from 4 to 22 with equal spatial distribution across the array. Speech recognition (monosyllables, sentences in quiet and in noise), subjective speech sound quality, and closed-set auditory tasks (vowels, consonants, and spectral modulation detection) were measured acutely. Recipients with well-placed straight electrode arrays and translocated precurved electrode arrays performed similarly, demonstrating asymptotic speech recognition scores with 8-10 channels, consistent with the classic literature. This finding contrasts with recent work…

Explosions from activities such as construction, demolition, and military activities are increasingly encountered in the underwater soundscape. However, there are few scientifically rigorous data on the effects of underwater explosions on aquatic animals, including fishes. Thus, there is a need for data on potential effects on fishes collected simultaneously with data on the received signal characteristics that result in those effects. To better understand potential physical effects on fishes, Pacific sardines (Sardinops sagax) were placed in cages at mid-depth at distances of 18 to 246 m from a single mid-depth detonation of C4 explosive (4.66 kg net explosive weight). The experimental site was located in the coastal ocean with a consistent depth of approximately 19.5 m. Following exposure, potential correlations between blast acoustics and observed physical effects were examined. Acoustic metrics were calculated as a function of range, including peak pressure, sound exposure level, and integrated pressure over time. Primary effects related to exposure were damage to the swim…

To suppress the noise interference in underwater acoustic signals for recognition, a practical denoising representation and recognition method is proposed. This algorithm first generates the multi-images between marine noise and target signal by correlation and "dropout" processing, adaptively. Second, a convolutional denoising autoencoder is designed to train the segmented multi-images in parallel to acquire denoising features. Finally, to improve the classification accuracy of random forest (RF), the weight fusion is exploited to initialize parallel RF classifier. Numerical experiments are shown that demonstrate superiority to three other methods in feature denoising and classification under underwater acoustic scenes.

This paper presents an equivalent fluid model (EFM) formulation in a three-dimensional time-domain discontinuous Galerkin finite element method framework for room acoustic simulations. Using the EFM allows for the modeling of the extended-reaction (ER) behavior of porous sound absorbers. The EFM is formulated in the numerical framework by using the method of auxiliary differential equations to account for the frequency dependent dissipation of the porous material. The formulation is validated analytically and an excellent agreement with the theory is found. Experimental validation for a single reflection case is also conducted, and it is shown that using the EFM improves the simulation accuracy when modeling a porous material backed by an air cavity as compared to using the local-reaction (LR) approximation. Last, a comparative study of different rooms with different porous absorbers is presented, using different boundary modeling techniques, namely, a LR approximation, a field-incidence (FI) approximation, or modeling the full ER behavior with the EFM. It is shown that using a LR…

Lung ultrasound (LUS) is a rapidly evolving field of application for ultrasound technologies. Especially during the current pandemic, many clinicians around the world have employed LUS to assess the condition of the lung for patients suspected and/or affected by COVID-19. However, LUS is currently performed with standard ultrasound imaging, which is not designed to cope with the high air content present in lung tissues. Nowadays LUS lacks standardization and suffers from the absence of quantitative approaches. To elevate LUS to the level of other ultrasound imaging applications, several aspects deserve attention from the technical and clinical world. This overview piece tries to provide the reader with a forward-looking view on the future for LUS.