JASA express letters最新文献

Ultrasonic inspection plays a critical role in nondestructive material characterization. Contact-based methods have been used in industry and field inspections for decades due to their portability. Although immersion testing provides improved spatial resolution, its adoption has been limited to commercial or research facilities due to its cost and footprint. Here, we present a frugal design for a custom immersion system based on a repurposed three-dimensional printer and show that ultrasonic wave speed measurements collected with the custom system and a commercial system are in statistical agreement. This work enables broader adoption of immersion ultrasonics for industry, education, and workforce development.

Merged productions of /ɪ/ and /ɛ/ before nasal consonants is well documented in Southern U.S. English, but perception studies on this merger are limited. A two-alternative forced-choice perception task asked U.S. listeners from inside and outside the South to respond to stimuli on continua from bid to bed and bin to Ben. Vowel nasality and coda nasality were fully crossed in the stimuli. The results confirm that Southern speakers are to some degree merged in perception, and that the presence of a nasal coda, and not vowel nasality, conditions merger in perception.

The health of the auditory nerve is a key factor for hearing outcomes in cochlear-implant patients. Many electrophysiological markers of auditory-neural health have been proposed, with varying predictive power and independence from non-neural factors. The "Failure Index" (FI), the ratio between stimulation current level and response magnitude of the electrically-evoked compound action potential (eCAP) was compared to the Panoramic eCAP method. Both methods predicted localized areas of reduced neural responsiveness in a group of human cochlear-implant users, but the FI showed a greater dependence on a non-neural factor, namely, the distances between the cochlear-implant electrodes and the auditory nerves.

This article introduces an analytical framework for modeling head-related transfer functions (HRTFs) from a listener-centered perspective. The distinction between strong (or general) HRTFs, aiming for idealized physical acoustic fidelity, and weak (or narrow) HRTFs, prioritizing perceptual adequacy in task-specific contexts, frames the contrast in multiple contrasting definitions and scientific methodologies by drawing inspiration from the debate in artificial intelligence. The proposed formalism adopts a Bayesian structure that models HRTFs through a state-space formulation capturing anatomical, contextual, experiential, and task-related factors: the eHRTF. The "e" emphasizes the egocentric perspective, transforming HRTFs from static measurements into mutable auditory representations continuously updated through the listener's feedback. Satisfaction regions are defined in probabilistic terms and characterize how different classes of HRTFs, i.e., individual, generic, super, and personalized, meet perceptual requirements under varying tasks and their complexity.

This study examined the effects of age and sentence context on perceiving speech temporal cues in noise. Adults 18 to 81 yrs of age with self-reported normal hearing performed a phonemic categorization task using the dent/tent contrast with varied voice-onset times (VOTs). Target words were embedded in sentences that biased perception toward "dent," "tent," or provided no bias, presented in speech-shaped noise at a 0 dB signal-to-noise ratio. Results showed reduced VOT processing with increasing age in neutral and dent-biasing contexts but not in tent-biasing contexts. Findings suggest that contextual influences can shape age-related changes in temporal processing in challenging listening conditions.

With the aim of achieving strong absorption over a wide range of frequencies and angles of incidence, the reflection of an acoustic wave by a rigidly-backed periodic layer of inclined ultrathin resistive sheet is studied theoretically and numerically. It appears that the structure exhibits either almost omnidirectional large absorption over a subwavelength frequency band for large resistivity of the wiremesh or large absorption over a broad frequency band for medium resistivity. Both optimal values are obtained for large inclination angles. These findings provide promising perspectives for the design of broadband omnidirectional subwavelength sound-absorbing devices.

Marine vessels are mandated or requested to reduce speed to meet operational, economic, and conservation goals. Vessel speed reduction (VSR) is a key strategy in global efforts to reduce ocean noise. Many regional VSR programs incorporate underwater acoustic monitoring to assess reductions in underwater radiated noise (URN) from vessels. Drawing from North American VSR programs, approaches to measuring URN reduction are assessed and progress toward robust metrics, scalable methods, and integrative measures are documented. Improved alignment across programs is recommended across programs to achieve measurement comparability to advance VSR evaluation and contribute to global underwater noise reduction and sustainable shipping goals.

Model-based deep learning approaches provide an alternative scheme to address the problem of the shortage of training data. However, performance degradation caused by sound speed profile (SSP) mismatch remains a critical challenge, particularly in shallow-water environments influenced by internal waves. In this paper, a simple range-dependent SSP model is integrated into the deep learning approach for source localization. The network trained on simulated data generated with the range-dependent SSP model performs well on validation data and generalizes to experimental test data after transfer learning with limited experimental samples.

The presence of unavoidable background noise limits the signal-to-noise ratio in measured room impulse responses (RIRs). A common solution is to crop the RIR to the time interval where the signal dominates the background noise, but finding the correct onset and truncation points is challenging. It usually requires estimating the sound decay rate and noise floor, which is burdened with uncertainty. In this study, we propose an RIR cropping method based on the covariance between two repeated RIRs and its inherent monotonicity. Evaluation on measured RIRs shows the proposed method is highly robust in different scenarios and outperforms state-of-the-art algorithms.