Several simple experiments involving room acoustics of an empty rectangular room are described, including observation of flutter echoes, identification of standing wave room modes, measurements of reverberation time, and measurements of sound pressure level as a function of distance from a source to observe the transition from free-field to reverberant field and the critical distance.

While analogs between electrical, mechanical, and acoustical systems are well known, especially for the analysis of transducers, students encountering analogous acoustical and mechanical systems in different settings often do not recognize the similarities between the systems and their solutions. This paper explores two homework problems that are direct analogs of each other. One problem involves a cylindrical Helmholtz resonator, and the other involves a longitudinal oscillation of a fixed, mass-loaded rod. A detailed analysis of both problems, including lumped-element approximate solutions and more accurate solutions utilizing impedance and boundary conditions, illustrates that these two systems represent essentially the same problem.

Matched-field processing is highly sensitive to environmental mismatch, yet most robust formulations emphasize static uncertainties more than time-evolving environmental forcing. This study examines a representative low-frequency shallow-water scenario in which wind-driven mixed-layer deepening reshapes the upper-ocean sound-speed profile and perturbs modal horizontal wavenumbers, producing accumulated phase errors, ambiguity-surface distortion, and systematic range bias. To organize these effects beyond a single operating point, a conditional modal phase-spread analysis is introduced to show how wind-driven degradation depends jointly on wind state, propagation range, frequency, and source depth relative to the mixed layer. A physics-coupled particle filter (PC-PF) is then proposed, in which wind speed is treated as a dynamic hidden state and estimated jointly with source range through an embedded reduced-order environmental model. Broadband numerical experiments are used to assess mechanism and tracking performances. For the representative storm-evolution scenario considered here, a conventional static-model broadband Bartlett processor develops kilometer-scale range errors, whereas the proposed PC-PF substantially reduces the root mean square error and preserves track continuity. The formulation is intended as a reduced-order, acoustically informed framework for dynamic environmental adaptation in time-varying conditions.

Improving the understanding and control of tip leakage noise is increasingly important for meeting future aviation noise-reductions targets. This study experimentally investigates porous tip treatments on a single stationary aerofoil, focusing on their effect on the two tip leakage noise sources, vortex-shedding and shear layer roll-up, both arising from the tip flow separation at the pressure side tip. Porous tip effectively reduces the roll-up noise source, with even a thin treatment of 1.6 mm providing reductions of almost 10 dB, whereas vortex-shedding noise radiation shifts toward lower frequencies and achieves almost full suppression for the thickness treatment of 10 mm. Localising the porous section to the mid-chord yields comparable noise reductions to full-chord treatments. Aerodynamic measurements indicate a modest lift reduction with the porous treatment compared to the hard-wall case, whereas drag remains largely unaffected for larger gaps.

Distributed Acoustic Sensing (DAS) on submarine cables is an untapped resource for monitoring marine mammals. The high spatial coverage and resolution of DAS data require specialized automated methods. In November 2021, the Ocean Observatories Initiative (OOI) Regional Cabled Array (RCA) collected DAS data including fin whale calls from an experiment offshore of central Oregon using two nearshore cable sections (65 and 95 km long) with sampling rates up to 1 kHz. This study presents an automated method for associating and localizing fin whale call detections of the OOI RCA. The method employs a grid search approach to associate acoustic arrival times between cables and multiple calling individuals, utilizing data from one or both cables depending on detection availability. Noisy call associations are enhanced through Gabor filtering of detections and spatial windowing on the farthest cable sections. Localization is performed using a weighted least squares inversion. Five ten-minute subsets of detection data were manually annotated to compute precision, recall, and F1-scores. The method enhanced with a far spatial window achieves recall values of 0.92-0.94 with low precision (0.3), which can be mitigated by subsequent track formation. These findings highlight the potential of submarine cable DAS for continuous, large-scale marine mammal monitoring.

This study characterises articulatory-kinematic strategies to differentiate the sibilants /s/ and /ʃ/ in individuals before and after tongue cancer surgery. We further evaluate whether successful differentiation can be predicted by auditory and somatosensory motor learning abilities. Acoustic and electromagnetic articulography data were collected longitudinally (pre-surgery, and 6, 12, and 18 months post-surgery) from Dutch individuals treated for T1-T3 tongue tumours (n = 12). Sex- and age-matched typical speakers (n = 11) were tested once. We analysed the Euclidean distance (ED) between the tongue's position for /s/ and /ʃ/, alongside the centre of gravity. Altered formant feedback and bite-block experiments assessed motor learning from auditory and somatosensory input. Speakers showed a reduced ED between sibilants at the tongue tip (TT) six months post-surgery compared to pre-surgery. While performance improved over time, pre-surgery levels were not regained. ED reductions were associated with changes in lip aperture and jaw positioning. No differences were found between patients and typical speakers in acoustic or kinematic measures at any time point. No robust association was found between auditory/somatosensory motor learning ability and sibilant differentiation. Together, while TT control was reduced following tongue cancer surgery, speakers compensated using the lips and jaw to preserve the sibilant contrast.

Monitoring whale vocalization is of scientific importance and has practical value for marine ecology, hydroacoustics, and geophysics. Conventional monitoring approaches, including hydrophone arrays, ocean-bottom seismometers, and satellite tagging, are limited by sparse spatial coverage, potential biological disturbance, and high cost. Distributed acoustic sensing (DAS) is an emerging method that uses submarine optical cables as dense acoustic arrays, potentially enabling large-scale, high-resolution monitoring of whale vocalization. We investigated the features of the wavefields of fin whale vocalization by integrating DAS observations with numerical modeling. Three distinct features-insensitive response segments (IRSs), high-frequency component loss, and acoustic notches-were identified in the observed wavefields. DAS response modeling based on ray theory indicates that the length of the IRS is correlated positively with the vertical distance between the source and cable, and the gauge length is responsible for the high-frequency loss in whale calls. Furthermore, wavefield modeling using the spectral-element method demonstrates that the notches represent transitions between transmission zones of waterborne multipath waves entering the seafloor and are sensitive to the seafloor P-wave velocity, water depth, and bathymetry. These findings not only improve our understanding of DAS-observed wavefields but also highlight the potential of DAS for ocean environmental parameter estimation and three-dimensional whale localization.

Sound localization performance was measured for ambisonic panning over a circular array of loudspeakers with various orders of ambisonics. Absolute sound localization was measured by recording physical orientation to the perceived sound source using a head tracker. The frequency of front/back errors was elevated using first-order ambisonics. After front/back correction, first- and second-order ambisonics still produced distortions in perceptual space compared to higher orders. For orders three to eight, the further performance improvements were not statistically significant; accuracy was comparable with that for point sources and replicated the perceptual biases listeners have shown for the azimuth of sound sources. Precision of absolute sound localization was also poorer for first- and second-order ambisonics. To estimate precision without contamination from motor responses, the minimum audible angle (MAA) was measured at a range of azimuths for 1st-, 3rd-, and 8th-order ambisonics. MAAs were smaller for 3rd- and 8th-order ambisonics than for 1st-order ambisonics. At the higher orders, the MAA was comparable to that observed with point sources in previous studies when the source was close to the midline. Otherwise, ambisonic MAAs were poorer than reported for dicrete sound sources, but replicated reports of relatively elevated MAAs in the rear hemifield.

Auditory localization depends on the integration of binaural and spectral cues, yet their relative contributions to localization judgments remain difficult to quantify within a unified computational framework. This study introduces a Bayesian model of static auditory localization with an explicit cue-weighting (ECW) mechanism that estimates cue-specific weighting parameters by fitting behavioral responses. By embedding ECW into the likelihood function, the model provides a probabilistic framework for characterizing how weighted acoustic cues, spatial priors, and motor noise jointly shape localization responses. The estimated weighting patterns were broadly consistent with classic psychoacoustic findings, showing stronger weighting of binaural cues together with selective high-frequency weighting of spectral cues. The model further accounted for major behavioral trends across broadband stimulation and several challenging acoustic conditions, including non-individualized head-related transfer functions and reduced spectral resolution via vocoders. Together, these results indicate that the proposed ECW model extends Bayesian models of auditory localization by making the relative contributions of established binaural and spectral cues behaviorally estimable while providing competitive predictive performance.

Ultrasonic echoes provide critical cues for object perception, yet their millisecond duration and frequency-specific structure violate assumptions of conventional spectrogram-based convolutional models. Existing biomimetic front-end systems, including auditory spectrograms, cortical wavelets, and the biomimetic BioNet, either under-utilize model capacity on brief echoes or impose frequency shift-invariance suited to vocalizations but detrimental for echo discrimination. This study introduces BioNet5-A, a biomimetic encoder optimized for ultrasonic echoes. BioNet5-A is derived from an autoencoder pretrained on bat vocalizations and incorporates three architectural innovations: (1) spectrotemporal attention to concentrate capacity on the ∼2 ms echo segment and relax frequency-axis invariance; (2) multi-sized convolution/transposed-convolution modules that capture echo structure across multiple scales; and (3) a symmetric, weight-tied encoder-decoder to stabilize training and regularize the biomimetic code. Using a controlled ultrasonic dataset spanning multiple objects and noise conditions, BioNet5-A consistently outperforms auditory spectrogram, cortical wavelet, and the conventional BioNet, and shows improved clustering, discrimination, and robustness. Additionally, representations by the model remain compact and interpretable, aligning with bat midbrain physiology. These results position BioNet5-A as a practical front end for biosonar-inspired sensing and ultrasonic applications.