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Evaluating sound similarity is a fundamental building block in acoustic perception and computational analysis. Traditional data-driven analyses of perceptual similarity are based on heuristics or simplified linear models, and are thus limited. Deep learning embeddings, often using triplet networks, have been useful in many fields. However, such networks are usually trained using large class-labelled datasets. Such labels are not always feasible to acquire. We explore data-driven neural embeddings for sound event representation when class labels are absent, instead utilising proxies of perceptual similarity judgements. Ultimately, our target is to create a perceptual embedding space that reflects animals' perception of sound. We create deep perceptual embeddings for bird sounds using triplet models. In order to deal with the challenging nature of triplet loss training with the lack of class-labelled data, we utilise multidimensional scaling (MDS) pretraining, attention pooling, and a triplet mining scheme. We also evaluate the advantage of triplet learning compared to learning a neural embedding from a model trained on MDS alone. Using computational proxies of similarity judgements, we demonstrate the feasibility of the method to develop perceptual models for a wide range of data based on behavioural judgements, helping us understand how animals perceive sounds.The energy dissipated during vocal fold (VF) contact is a predictor of phonotrauma. Difficulty measuring contact pressure has forced prior energy dissipation estimates to rely upon generalized approximations of the contact dynamics. To address this shortcoming, contact pressure was measured in a self-oscillating synthetic VF model with high spatiotemporal resolution using a hemilaryngeal configuration. The approach yields a temporal resolution of less than 0.26 ms and a spatial resolution of 0.254 mm in the inferior-superior direction. The average contact pressure was found to be 32% of the peak contact pressure, 60% higher than the ratio estimated in prior studies. It was found that 52% of the total power was dissipated due to collision. The power dissipated during contact was an order of magnitude higher than the power dissipated due to internal friction during the non-contact phase of oscillation. Both the contact pressure magnitude and dissipated power were found to be maximums at the mid anterior-posterior position, supporting the idea that collision is responsible for the formation of benign lesions, which normally appear at the middle third of the VF.Most studies of speech perception employ highly controlled stimuli. It is not always clear how such results extend to the processing of natural speech. In a series of experiments, we progressively explored the role of voice onset time (VOT) and potential secondary cues in adult labeling of stressed syllable-initial /b d p t/ produced by typically developing two-year-old learners of American English. this website Taken together, the results show the following (a) Adult listeners show phoneme boundaries in labeling functions comparable to what have been established for adult speech. (b) Adult listeners can be sensitive to distributional properties of the stimulus set, even in a study that employs highly varied naturalistic productions from multiple speakers. (c) Secondary cues are available in the speech of two-year-olds, and these may influence listener judgments. Cues may differ across places of articulation and the VOT continuum. These results can lend insight into how clinicians judge child speech during assessment and also have implications for our understanding of the role of primary and secondary acoustic cues in adult perception of child speech.This paper presents a semi-analytical method of suppressing acoustic scattering using reinforcement learning (RL) algorithms. We give a RL agent control over design parameters of a planar configuration of cylindrical scatterers in water. These design parameters control the position and radius of the scatterers. As these cylinders encounter an incident acoustic wave, the scattering pattern is described by a function called total scattering cross section (TSCS). Through evaluating the gradients of TSCS and other information about the state of the configuration, the RL agent perturbatively adjusts design parameters, considering multiple scattering between the scatterers. As each adjustment is made, the RL agent receives a reward negatively proportional to the root mean square of the TSCS across a range of wavenumbers. Through maximizing its reward per episode, the agent discovers designs with low scattering. Specifically, the double deep Q-learning network and the deep deterministic policy gradient algorithms are employed in our models. Designs discovered by the RL algorithms performed well when compared to a state-of-the-art optimization algorithm using fmincon.The hooded seal is a migratory species inhabiting the North Atlantic. Passive acoustic monitoring (PAM) conducted over spatial scales consistent with their known and potential habitat could provide insight into seasonal and spatial occurrence patterns of this species. Hooded seal airborne and underwater acoustic signals were recorded during the breeding season on the pack ice in the Gulf of St. Lawrence in March 2018 to better characterize their acoustic repertoire (notably underwater calls). In-air and underwater signals were classified into 12 and 22 types, respectively. Signals produced by males through the inflation and deflation of the proboscis and septum were the predominant sounds heard on the ice surface. Five of the 22 underwater signals were proboscis and septum noises. The remaining underwater signals (17) were categorized as voiced calls and further analyzed using two classification methods. Agreement with the initial subjective classification of voiced calls was high (77% for classification tree analysis and 88% for random forest analysis), showing that 12-13 call types separated well. The hooded seal's underwater acoustic repertoire is larger and more diverse than has been previously described. This study provides important baseline information necessary to monitor hooded seals using PAM.The Reflections series takes a look back on historical articles from The Journal of the Acoustical Society of America that have had a significant impact on the science and practice of acoustics.Fine-scale mixing noise (FSMN) and broadband shock-associated noise (BBSAN) are the dominant components of supersonic jet noise in the sideline and upstream directions. We use the previously developed statistical FSMN and BBSAN models to compare the noise radiated from three different nozzles, i.e., a method of characteristics nozzle, a bi-conic nozzle, and a faceted nozzle at different operating conditions. link2 A numerical sensitivity analysis is performed using the models by perturbing various model parameters and conditions such as nozzle pressure ratio (NPR), total temperature ratio, area ratio, and boundary layer thickness. We observed that FSMN is most sensitive to NPR and BBSAN is most sensitive to area ratio. We also examine the changes in source statistics and corresponding correlations of the radiated noise using the fluidic injection noise reduction technique. Noise reduction predictions relative to the baseline cases are compared at different operating conditions and similar reduction as the experimental measurements were obtained at over-expanded conditions. Finally, we analyze the noise source locations for both components of jet noise in the sideline direction. The trends predicted in this study increase understanding of the changes in source statistics and radiated noise for different nozzles over a range of operating conditions.We simulated the effect of several automatic gain control (AGC) and AGC-like systems and head movement on the output levels, and resulting interaural level differences (ILDs) produced by bilateral cochlear-implant (CI) processors. The simulated AGC systems included unlinked AGCs with a range of parameter settings, linked AGCs, and two proprietary multi-channel systems used in contemporary CIs. The results show that over the range of values used clinically, the parameters that most strongly affect dynamic ILDs are the release time and compression ratio. Linking AGCs preserves ILDs at the expense of monaural level changes and, possibly, comfortable listening level. Multichannel AGCs can whiten output spectra, and/or distort the dynamic changes in ILD that occur during and after head movement. We propose that an unlinked compressor with a ratio of approximately 31 and a release time of 300-500 ms can preserve the shape of dynamic ILDs, without causing large spectral distortions or sacrificing listening comfort.We developed a piezoelectric micromachined cantilever acoustic vector (PEMCAV) sensor. We modeled the device using a "lumped" approach that considers fluid-structure interaction, the piezoelectric effect, and the mechanical impedance of the cantilever. Due to the high flexibility, the influence of the medium is significant, so fluid-structure interaction must be considered in theoretical modeling. We compared the model data to experimental results. The design parameters optimized using the derived analytical open-circuit sensitivity equation are presented, and the physical characteristics of the sensor are discussed. We used a micromachining technique to fabricate the sensor, added a preamplifier, and tested it using a reference hydrophone under a frequency range of 100 Hz-1 kHz. The analytical predictions and experimental results were in good agreement with respect to frequency response and the directivity of the sensor. Even when the sensor was much smaller than the wavelength ( ka≪1), the proposed sensor exhibited a typical cosine directivity pattern, and the measured sensitivity at 100 Hz was -194 dBV/μPa.Quantitative ultrasound methods based on the backscatter coefficient (BSC) and envelope statistics have been used to quantify disease in a wide variety of tissues, such as prostate, lymph nodes, breast, and thyroid. However, to date, these methods have not been investigated in the lung. link3 In this study, lung properties were quantified by BSC and envelope statistical parameters in normal, fibrotic, and edematous rat lungs in vivo. The average and standard deviation of each parameter were calculated for each lung as well as the evolution of each parameter with acoustic propagation time within the lung. The transport mean free path and backscattered frequency shift, two parameters that have been successfully used to assess pulmonary fibrosis and edema in prior work, were evaluated in combination with the BSC and envelope statistical parameters. Multiple BSC and envelope statistical parameters were found to provide contrast between control and diseased lungs. BSC and envelope statistical parameters were also significantly correlated with fibrosis severity using the modified Ashcroft fibrosis score as the histological gold standard. These results demonstrate the potential for BSC and envelope statistical parameters to improve the diagnosis of pulmonary fibrosis and edema as well as monitor pulmonary fibrosis.Noise-interference suppression and data-processing acceleration are crucial to aeroacoustic measurements with phased array in wind tunnels. In this paper, we develop a "multi-window" beamforming algorithm that recursively processes data based on an array-acquisition model. This spatial filtering algorithm is derived from the Kalman filter theory for signal processing. The simulated results show that by using recursive operations, accurate signal estimation is acquired with incoherent and coherent background noise removed in the presence of both channel noise and phase noise. The convergence rate of this recursive algorithm is faster than the existing algorithms. As a result, considerable storage space and computational resources are saved, while testing defects in wind tunnel measurement are revealed and corrected immediately on-site. It has a great potential for real-time localization of sound sources in a noisy environment.