JASA express letters最新文献

Underwater acoustic communication signals suffer from time dispersion due to time-varying multipath propagation in the ocean. This leads to intersymbol interference, which in turn degrades the performance of the communication system. Typically, the channel correlation functions are employed to describe these characteristics. In this paper, a metric called the channel average correlation coefficient (CACC) is proposed from the correlation function to quantify the time-varying characteristics. It has a theoretical negative relationship with communication performance. Comparative analysis involving simulations and experimental data processing highlights the superior effectiveness of CACC over the traditional metric, the channel coherence time.

Recently researchers often normalize the radiation force on spheres in standing waves in inviscid fluids using an acoustic contrast factor (typically denoted by Φ) that is independent of kR where k is the wave number and R is the sphere radius. An alternative normalization uses a function Ys that depends on kR. Here, standard results for Φ are extended as a power series in kR using prior Ys results. Also, new terms are found for fluid spheres and applied to the kR dependence of Φ for strongly responsive and weakly responsive examples. Partial-wave phase shifts are used in the derivation.

Although the telephone band (0.3-3 kHz) provides sufficient information for speech recognition, the contribution of the non-telephone band (<0.3 and >3 kHz) is unclear. To investigate its contribution, speech intelligibility and talker identification were evaluated using consonants, vowels, and sentences. The non-telephone band produced relatively good intelligibility for consonants (76.0%) and sentences (77.4%), but not vowels (11.5%). The non-telephone band supported good talker identification only with sentences (74.5%), but not vowels (45.8%) or consonants (10.8%). Furthermore, the non-telephone band cannot produce satisfactory speech intelligibility in noise at the sentence level, suggesting the importance of full-band access in realistic listening.

The peaked cochlear tonotopic response does not show the typical phenomenology of a resonant system. Simulations of a 2 D viscous model show that the position of the peak is determined by the competition between a sharp pressure boost due to the increase in the real part of the wavenumber as the forward wave enters the short-wave region, and a sudden increase in the viscous losses, partly counteracted by the input power provided by the outer hair cells. This viewpoint also explains the peculiar experimental behavior of the cochlear admittance (broadly tuned and almost level-independent) in the peak region.

The model manifold, an information geometry tool, is a geometric representation of a model that can quantify the expected information content of modeling parameters. For a normal-mode sound propagation model in a shallow ocean environment, transmission loss (TL) is calculated for a vertical line array and model manifolds are constructed for both absolute and relative TL. For the example presented in this paper, relative TL yields more compact model manifolds with seabed environments that are less statistically distinguishable than manifolds of absolute TL. This example illustrates how model manifolds can be used to improve experimental design for inverse problems.

Elastic periodic lattices act as mechanical filters of incident vibrations. By and large, they forbid wave propagation within bandgaps and resonate outside them. However, they often encounter "truncation resonances" (TRs) inside bandgaps when certain conditions are met. In this study, we show that the extent of unit cell asymmetry, its mass and stiffness contrasts, and the boundary conditions all play a role in the TR location and wave profile. The work is experimentally supported via two examples that validate the methodology, and a set of design charts is provided as a blueprint for selective TR placement in diatomic lattices.

Age-related changes in auditory processing may reduce physiological coding of acoustic cues, contributing to older adults' difficulty perceiving speech in background noise. This study investigated whether older adults differed from young adults in patterns of acoustic cue weighting for categorizing vowels in quiet and in noise. All participants relied primarily on spectral quality to categorize /ɛ/ and /æ/ sounds under both listening conditions. However, relative to young adults, older adults exhibited greater reliance on duration and less reliance on spectral quality. These results suggest that aging alters patterns of perceptual cue weights that may influence speech recognition abilities.

Singing is socially important but constrains voice acoustics, potentially masking certain aspects of vocal identity. Little is known about how well listeners extract talker details from sung speech or identify talkers across the sung and spoken modalities. Here, listeners (n = 149) were trained to recognize sung or spoken voices and then tested on their identification of these voices in both modalities. Learning vocal identities was initially easier through speech than song. At test, cross-modality voice recognition was above chance, but weaker than within-modality recognition. We conclude that talker information is accessible in sung speech, despite acoustic constraints in song.

This study investigated the acoustic cue weighting of the Korean stop contrast in the perception and production of speakers who moved from a nonstandard dialect region to the standard dialect region, Seoul. Through comparing these mobile speakers with data from nonmobile speakers in Seoul and their home region, it was found that the speakers shifted their cue weighting in perception and production to some degree, but also retained some subphonemic features of their home dialect in production. The implications of these results for the role of dialect prestige and awareness in second dialect acquisition are discussed.

The automatic classification of phonation types in singing voice is essential for tasks such as identification of singing style. In this study, it is proposed to use wavelet scattering network (WSN)-based features for classification of phonation types in singing voice. WSN, which has a close similarity with auditory physiological models, generates acoustic features that greatly characterize the information related to pitch, formants, and timbre. Hence, the WSN-based features can effectively capture the discriminative information across phonation types in singing voice. The experimental results show that the proposed WSN-based features improved phonation classification accuracy by at least 9% compared to state-of-the-art features.