Journal of the Acoustical Society of America最新文献

Anthropogenic noise may pose a threat to Kemp's ridley sea turtles in nearshore and offshore waters of the western North Atlantic and Gulf of America, where shipping and energy industries are widespread. Understanding hearing sensitivity is necessary for the development of effective noise impact mitigation strategies. However, data gaps currently exist. Therefore, in this study, we measured auditory evoked potentials (AEP) to determine the underwater hearing sensitivities of 13 juvenile Kemp's ridley sea turtles using hearing test frequencies ranging from 50 to 1600 Hz. We detected AEPs for hearing test signals between 50 and 800 Hz. Peak hearing sensitivity occurred between 200 and 300 Hz, followed by a decline in sensitivity above 400 Hz. The lowest hearing threshold averaged across all test subjects was 100 dB re 1 μPa at 300 Hz. No responses were detected at 1200 Hz (max received level = 143 dB re 1 μPa) and 1600 Hz (max received level = 143-165 dB re 1 μPa). Our results averaged across multiple individuals at 100 Hz (n = 9), 200 Hz (n = 8), 300 Hz (n = 5), and 400 Hz (n = 8) reveal lower hearing thresholds (greater sensitivity) than those reported in a previous study of two Kemp's ridley sea turtles at these frequencies. The results presented here should be considered a conservative estimate of hearing sensitivity, as perceptual hearing thresholds are likely lower than what can be determined with AEPs.

To address the dual demands of high static load capacity and low resonance frequency in underwater electrodynamic transducers, this study introduces a nonlinear supporting mechanism based on a tension spring-roller-cam quasi-zero stiffness (QZS) structure. The mechanism effectively reduces the equivalent stiffness while maintaining high static load capacity, achieving lower resonance frequency and enhanced ultra-low-frequency vibration performance. A nonlinear dynamic model of the transducer is developed, and displacement and sound pressure level responses are analyzed using the harmonic balance method. Numerical simulations reveal the influence of mechanical damping and excitation amplitude on the system's vibration characteristics. Comparative analysis shows that the QZS-supported system exhibits a significantly lower resonance frequency and improved low-frequency vibration behavior than the conventional linear system. Experimental validation using impact hammer testing confirms a significant reduction in resonance frequency and enhanced acceleration response in the ultra-low-frequency range. These findings validate the capability of the proposed QZS suspension mechanism to achieve ultra-low resonance frequency, suggesting its potential for application in underwater ultra-low-frequency electrodynamic transducers.

A formulation to introduce acoustic waves from a control surface using volumetric source terms is proposed for numerical simulations. A general expression of the source terms is derived from the non-linear Euler equations. The method is validated through three academic configurations: the injection of oblique plane waves and the radiation of a monopole source in two and three dimensions, in uniform flow. The governing equations are solved in a Cartesian grid using a low-dispersion and low-dissipation high order finite-difference numerical scheme. However, the control surface has an arbitrary shape, as demonstrated here with the use of a cylindrical surface. Numerical results show good agreement with analytical solutions in both phase and amplitude. The method is then applied to an open-fan aircraft engine configuration. The source terms are computed from a cylindrical control surface enclosing the rotor, based on data extracted from a previous fluid mechanics simulation. The radiated acoustic field is compared with the one obtained using the Ffowcs Williams-Hawkings integral formulation. The two solutions are again found in good agreement for this more realistic configuration.

Clear speech, a speaking style used to communicate with individuals with hearing loss and other communication difficulties, has been shown to sound "angry" more often than conversational speech [Morgan and Ferguson (2017). J. Speech. Lang. Hear. Res. 60, 2271-2280]. In this study, acoustic analyses of emotionally neutral sentences from a database of 41 talkers spoken both clearly and conversationally were analyzed in tandem with judgments of emotions for the same sentences to assess potential acoustic correlates of judgments of anger in clear speech. Principal component analyses were conducted to guide the selection of acoustic measures for statistical models. Decreases in speaking rate and increases in temporal fluctuations in amplitude centered at 1 Hz, both of which are prominent features of clear speech, were both associated with increases in judgments of anger. Increases in fundamental frequency variability, another common feature of clear speech, were associated with increases in judgments of any amount of anger but only in conversational speech. Finally, after controlling for speaking style and fundamental frequency variability, women were judged to sound angry more often than men. The results suggest that speaking rate, amount of word or phrase-level amplitude modulation, and fundamental frequency variability could possibly be manipulated to decrease judgments of anger in clear speech.

In underwater mobile spread spectrum communications, time-varying Doppler effects cause severe carrier phase jumps, significantly degrading spreading gain. Addressing the limitations of conventional compensation techniques under high relative velocities, this study investigates the correlation cost factor (CCF) during de-spreading in M-ary spread spectrum systems. Theoretical analysis reveals that CCF serves as an effective loss function for frequency offset compensation. Leveraging this, a high-resolution Doppler estimation method (HCCF-MSS) is proposed. HCCF-MSS employs the adaptive learning rate of the Adam optimizer to update step sizes, enabling rapid, high-precision convergence of the CCF loss function to the accurate frequency offset. To mitigate convergence to local minima in highly dynamic environments, the Multi-starting Point Parallel Gradient Search (MPGS) algorithm is introduced. MPGS initiates concurrent gradient searches from diverse starting points and selects the optimal solution by comparing CCF values across convergent paths. Numerical simulations and sea trials demonstrate that HCCF-MSS-9 (9 iterations) achieves performance comparable to CCF-MSS-0.02 (±6 Hz range, 0.02 Hz precision) with superior computational efficiency. Under accelerations up to 3 m/s2, HCCF-MSS-9+MPGS-6 (6 starting points) attains a Doppler estimation mean squared error of approximately -3.3 dB, outperforming other algorithms by 0.5-1.5 dB, demonstrating its effectiveness for precise frequency offset estimation under complex variable-motion conditions.

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.

Acoustic signals with a center frequency of 35 Hz and a full bandwidth of about 4 Hz were transmitted over various ranges along a path extending from north of Svalbard to north of Alaska during the 2019-2020 US-Norwegian Coordinated Arctic Acoustic Thermometry Experiment (CAATEX). Three moorings were installed in the Canada Basin and three in the Nansen Basin, with one mooring in each basin hosting a source. All moorings had vertical receiving arrays, enabling spatial separation of the low-order acoustic normal modes. The modal group delays varied significantly over the year but were roughly consistent with predictions for the decade 2015-2022 based on the World Ocean Atlas 2023. The CAATEX signals traversed nearly the same trans-Arctic acoustic path as the 19.6-Hz signals in the 1994 Transarctic Acoustic Propagation (TAP) experiment. The TAP and CAATEX group delays cannot be directly compared because of the differing carrier frequencies. Thus, an indirect method using the group delays computed using WOA 2023 as a convenient standard was employed, but the large TAP mode-2 travel-time uncertainty precluded definitive comparisons. Nonetheless, CAATEX demonstrated that long-range acoustic transmissions provide precise, year-round measurements of large-scale ocean sound-speed (temperature) variability under the ice.

The primary goal of this study is to investigate and refine the two-cavity impedance tube method for acoustic characterization of bulk porous materials, specifically addressing previously unexplained inaccuracies in the prediction of surface impedance and absorption coefficients. Unlike the conventional two-thickness approach, the two-cavity method requires only one sample thickness and involves conducting measurements at various air cavity depths behind the sample. The initial analyses revealed previously unidentified numerical instabilities, resulting in anomalous predictions of sound absorption at specific frequencies. Through systematic investigation and use of calculated data, the numerical origins of these anomalies are uncovered and a practical solution, involving the careful selection of cavity depths, is presented. This approach significantly improves predictive accuracy, validating the two-cavity impedance tube method as a robust and effective tool for the acoustic characterization of a wide variety of porous materials, including metallic and nonmetallic open-cell foams and additively manufactured lattice structures.

Spatial audio systems are typically evaluated in comparative listening tests using the same source signal for each condition {such as ABX: ITU-R BS.1116-3 [(2015a) Methods for the Subjective Assessment of Small Impairments in Audio Systems (International Telecommunication Union, Geneva, Switzerland)] and multiple stimulus with hidden reference and anchor ITU-R BS.1534-3 [(2015b) Methods for the Subjective Assessment of Intermediate Quality Level of Audio Systems (International Telecommunication Union, Geneva, Switzerland)]}. However, in augmented reality (AR) scenarios, it is infeasible that the same sound source would exist at the same position in space, both real and virtual; instead, each sound source will emit a different signal. To investigate this discrepancy, a perceptual study is conducted on the effect of source signal similarity when distinguishing different room acoustics conditions. Specifically, these conditions are binaural room impulse responses measured at different distances from the source, modified to all use the same direct sound. Three classes of source signal are investigated in a three-alternative forced choice paradigm: the same speech signal for all conditions, the same speaker but a different sentence for each condition, and a different speaker and a different sentence for each condition. Results show that using different speech recordings significantly reduces the ability to identify differences in room acoustics. This suggests that spatial audio system fidelity requirements could vary depending on the source signals used in the target application; AR audio evaluation should use different signals for comparisons.

The prediction of ocean sound speed fields (SSFs) is critical for underwater communication, marine resource exploration, and environmental monitoring. Due to the powerful generalization ability, deep learning technology has demonstrated its advantages in SSF prediction. However, limited by the processing capabilities of high-dimensional data, current research can only realize the three-dimensional characteristic extraction, without capturing the complete spatiotemporal information of SSF. In this work, we propose the Swin Transformer-UNet model (ST-UNet), which combines the convolutional networks U-Net and Swin Transformer networks, to approach the four-dimensional prediction of SSF. In this model, Swin Transformer network is applied to extract spatiotemporal characteristics through the multi-head self-attention mechanism, while U-Net enhances spatial details via the convolutional feature recovery. The availability and accuracy of the model are demonstrated by the real-life dataset from the South China Sea. It achieves a root mean square error of 0.783 m/s for 24-h SSF prediction based on 7-day historical data, outperforming baseline architectures by 33%-72%.