JASA express letters最新文献

The control of speech can be modeled as a dynamical system in which articulators are driven toward target positions. These models are typically evaluated using fleshpoint data, such as electromagnetic articulography (EMA), but recent methodological advances make ultrasound imaging a promising alternative. We evaluate whether the parameters of a linear harmonic oscillator can be reliably estimated from ultrasound tongue kinematics and compare these with parameters estimated from simultaneously recorded EMA data. We find that ultrasound and EMA yield comparable dynamical parameters, while mandibular short tendon tracking also adequately captures jaw motion. This supports using ultrasound kinematics to evaluate dynamical articulatory models.

The frequency following response (FFR) reflects the brain's neural encoding of pitch through the fundamental frequency (F0). While autocorrelation has long been the standard method for estimating F0 in FFRs, few alternatives have been explored. We propose a harmonic-structure-based approach that leverages knowledge of the stimulus F0 to guide a selective filterbank, extracting harmonic energy while suppressing noise. F0 is then tracked by identifying the most prominent spectral peak. Applied to FFRs recorded from 16 listeners in response to natural speech stimuli, the method reduced F0 tracking error by 8.8% to 47.4% compared to autocorrelation, offering a more accurate approach.

Currently, diagnosis of voice disorders is often made when patients visit the clinic, by which time speakers already experience vocal difficulties. The goal of this study was to develop a voice inversion system that predicts how speakers modulate vocal physiology from the produced voice, toward early detection of unhealthy vocal behavior. Two neural networks, a Bayesian neural network and a deep ensemble of neural networks, were developed that predict changes in vocal physiological parameters and their confidence intervals. Comparison to human data showed that both networks were able to predict meaningful differences in vocal behavior across subjects, demonstrating their potential toward ambulatory monitoring of vocal behavior at the physiological level.

Physics-informed neural networks (PINNs) have emerged as a promising tool for simulating various phenomena. However, their application in underwater acoustics remains challenging, primarily due to the need to sample large computational domains and to convergence to trivial solutions. This study presents a strategy to address these issues by combining adaptive domain sampling with absorbing boundary conditions. The adaptive sampler dynamically focuses computational effort on regions where the acoustic energy is localized, while the absorbing boundaries perform training stabilization. Numerical experiments show that our method improves the stability and convergence of PINN training, leading to more accurate and reliable wave propagation simulations.

This study characterizes the statistical dependence of low-frequency ambient sound on wind speed using 8 years of Ocean Observatories Initiative hydrophone data. Data from two bottom-mounted hydrophones, sampled at 200 Hz, are compared to a National Oceanic and Atmospheric Administration surface winds model. One hydrophone is on the continental slope and one is in open ocean. Wind dependence on ambient sound levels is reported for both locations across all studied frequencies (0.1-90 Hz). A piecewise, log-linear model is fit to ambient sound and wind speed, and different regions of wind dependence are discussed. Directional surface wave spectra from a nearby buoy are compared with acoustic measurements below 1.2 Hz. Time-frequency characteristics in acoustic data are largely explained by local surface spectra.

In this Letter, a simplified expression of the vertical dimension narrowband interference pattern in deep water direct arrival zone is theoretically derived. The correlation between the vertical dimension interference pattern and source depth is analyzed, and the depth span corresponding to a complete interference cycle (interference period) is derived theoretically. A source depth estimation method is proposed based on matching the vertical interference pattern calculated from the data with theoretical predictions. The effectiveness of the theoretical approach in predicting the vertical interference pattern and effectiveness of the proposed depth estimation method are verified by experimental data.

Spatiotemporal modulation (STM) has recently been used to improve diffusion from finite apertures of conventional acoustic diffuser profiles by introducing STM of the termination impedance of the diffuser wells and to scatter acoustic energy at frequencies that are up- and down-shifted from the incident wave frequency by integer multiples of the modulation frequencies. The present work employs a semi-analytical model of acoustic scattering from an STM acoustic metasurface to investigate the tunability of scattering from a flat metasurface with STM admittance by demonstrating nonreciprocal and diffuse scattering of sound via a parametric study on the modulation frequency and admittance amplitude. The results provide insight into the use of STM of input admittance to control acoustic scattering from acoustic metasurfaces.

Shadle [(2023). J. Acoust. Soc. Am. 153, 1412-1426] proposed that the spectral peak in mid-frequency (FM) is a superior measure of place of articulation of sibilant fricatives to the most commonly used measure, the first spectral moment (M1). It is examined as to whether FM predicts adult listener's ratings of the place of articulation of 2.5-3.5-year-old children's word-initial /s/ and /ʃ/ when compared to M1. Regression models reveal that FM in 3-9 kHz range best predicts listener's ratings of children's fricatives. These results provide additional validation for FM as a measure of fricatives' place of articulation, including in children's speech.

This Letter presents an analysis of near-field acoustic data collected on Space Launch System's Mobile Launcher tower during the Artemis I mission. Twelve pressure sensors located two and four effective nozzle diameters (De) from the vehicle centerline recorded maximum overall sound pressure levels ranging from ∼ 162 dB to more than 170 dB, originating ∼ 10 De downstream of the nozzle exit plane. Frequency-dependent characteristics are also discussed. The peak noise is radiated over a broader frequency range than in the far field. Low-frequency noise locations match other rockets, but high-frequency locations diverge, falling between prior measurements of undeflected and deflected plumes.

Spatial release from masking for an individual is dependent on the spatial separation between the target and the maskers, age, auditory capabilities, and working memory capacity. In this paper, a task is presented that estimates an individual's working memory capacity using a divided-attention version of the classic spatial release from masking task. Speech identification thresholds, temporal overlap thresholds, and working memory were measured for younger and older adults. The results showed younger listeners had better thresholds than older listeners across all the tests. Overall, this test can simultaneously estimate an individual's working memory and spatial processing capabilities.