Tim Sonnemann, Jan Dettmer, Charles W Holland, Stan E Dosso
{"title":"Range-dependent meso-scale geoacoustic seabed quantification.","authors":"Tim Sonnemann, Jan Dettmer, Charles W Holland, Stan E Dosso","doi":"10.1121/10.0036835","DOIUrl":"https://doi.org/10.1121/10.0036835","url":null,"abstract":"<p><p>This study presents a probabilistic one-step two-dimensional (2D) inversion method of spherical-wave reflection coefficient data to estimate the range-dependent structure and geoacoustic parameters along a track. The approach of inverting such datasets independently as one-dimensional (1D) layered models and merging them to a 2D section is feasible but computationally expensive. This study demonstrates a more parsimonious 2D parametrization for active source data recorded on a towed hydrophone array. The comparison of data variance reduction for 1D- and 2D-based results clearly favors the 2D parametrization described here.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144201002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Parallel tempering in trans-dimensional Bayesian geoacoustic inversion for high-information-content data and multi-parameter models.","authors":"Stan E Dosso","doi":"10.1121/10.0036948","DOIUrl":"https://doi.org/10.1121/10.0036948","url":null,"abstract":"<p><p>Trans-dimensional (trans-D) Bayesian inversion is a powerful approach to estimate seabed geoacoustic models from ocean-acoustic data, combining quantitative model selection and uncertainty estimation. Trans-D inversion samples probabilistically over the number of seabed layers and the geoacoustic parameters for each layer, with layers added and removed in sampling, changing the dimension of the model. However, the probability of accepting dimension changes can approach zero for problems involving highly informative data or large numbers of parameters per layer. This Letter examines the use of parallel tempering, which employs a sequence of interacting Markov chains with successively relaxed likelihoods, to address these challenging cases.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kristian Kvist, Sergey V Sorokin, Jan Balle Larsen
{"title":"Approximating radiated acoustic power by spherical harmonic decomposition.","authors":"Kristian Kvist, Sergey V Sorokin, Jan Balle Larsen","doi":"10.1121/10.0036786","DOIUrl":"https://doi.org/10.1121/10.0036786","url":null,"abstract":"<p><p>This study enhances the approximation \"radiation efficiency varying equivalent radiated power.\" This is done through introducing a new method for estimating radiation efficiencies, based on spherical harmonic decomposition. The proposed improvements eliminate the need for computationally expensive surface integrals and results in solution times comparable with the classical equivalent radiated power approximation. This is achieved while significantly outperforming classical equivalent radiated power in terms of accuracy when compared with full numerical solutions to Helmholtz equation. This is shown both quantitively and qualitatively through numerical acoustic models of two systems of industrial complexity. The proposed improvements make the method robust for non-convex geometries across varying mesh densities, making the method highly suitable for iterative acoustic analysis in industrial applications.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144201000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Examining variability and generalization in dimension-based statistical learning for speech: The case of place of articulation.","authors":"Jeremy Steffman, Minxuan He, Seb Segger-Staveley","doi":"10.1121/10.0036895","DOIUrl":"https://doi.org/10.1121/10.0036895","url":null,"abstract":"<p><p>In this study, the question of generalization for dimension-based statistical learning in speech perception is revisited. Learning for F0 and voice-onset-time as cues to stop voicing has been suggested to be fairly specific to a particular contrast, which was previously shown not to generalize between two places of articulation. The present study seeks to replicate generalization for the same place of articulation, using more varied stimuli and a different design. Then, it is tested if increased evidence for a distributional pattern, i.e., two places of articulation showing that pattern, leads to generalization to a third place of articulation. Same place of articulation learning is replicated, and no generalization across place of articulation is found, reaffirming that learning appears to be quite specific.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144318877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ultrasound measurement of relative tongue size and its correlation with tongue mobility for healthy individuals.","authors":"Jing Sun, Tatsuya Kitamura, Yukiko Nota, Noriko Yamane, Ryoko Hayashi","doi":"10.1121/10.0036838","DOIUrl":"https://doi.org/10.1121/10.0036838","url":null,"abstract":"<p><p>The size of an individual's tongue relative to the oral cavity is associated with articulation speed [Feng, Lu, Zheng, Chi, and Honda, in Proceedings of the 10th Biennial Asia Pacific Conference on Speech, Language, and Hearing (2017), pp. 17-19)] and may affect speech clarity. This study introduces an ultrasound-based method for measuring relative tongue size, termed ultrasound-based relative tongue size (uRTS), as a cost-effective alternative to the magnetic resonance imaging (MRI) based method. Using deep learning to extract the tongue contour, uRTS was calculated from tongue and oropharyngeal cavity sizes in the midsagittal plane. Results from ten speakers showed a strong correlation between uRTS and MRI-based measurements (r = 0.87) and a negative correlation with tongue movement speed (r = -0.73), indicating uRTS is a useful index for assessing tongue size.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144236110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Occlusion and height estimation using the coherence of multi-static synthetic aperture sonar images.","authors":"Thomas E Blanford","doi":"10.1121/10.0036836","DOIUrl":"https://doi.org/10.1121/10.0036836","url":null,"abstract":"<p><p>Objects in synthetic aperture sonar imagery that lie proud above an interface will occlude a portion of the background behind it. This occlusion may appear as a shadow in the imagery whose dimensions can be used to infer the height of the object. Volume scattering from beneath the object, however, may prevent such shadows from being visible in imagery. Regions of occlusion can be detected using the coherence between two images collected from different horizontal baselines. Using controlled laboratory experimentation, this approach is shown to detect occluded regions for accurate estimation of the height of an object.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144201001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Three-dimensional sound field reconstruction from optical projections using physics-informed neural networks.","authors":"Rikuto Ito, Kenji Ishikawa, Risako Tanigawa, Yasuhiro Oikawa","doi":"10.1121/10.0036816","DOIUrl":"https://doi.org/10.1121/10.0036816","url":null,"abstract":"<p><p>The implicit representation by physics-informed neural networks (PINNs) serves as an effective solution for a key challenge faced by optical sound measurements. Since optical sound measurements observe line integral of the sound pressure along the optical path, reconstruction is necessary to determine the sound pressure at each point in the three-dimensional field. In this paper, we expand the PINNs-based reconstruction method into three-dimensional reconstruction and demonstrate its effectiveness for optically measured sound fields. Furthermore, we propose a reconstruction approach which can estimate solutions well outside the bounds of the data used for training.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144201003","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Blind weak signal detection via dictionary learning in time-spreading distortion channels using vector sensors.","authors":"Rami Rashid, Ali Abdi, Zoi-Heleni Michalopoulou","doi":"10.1121/10.0036919","DOIUrl":"10.1121/10.0036919","url":null,"abstract":"<p><p>This paper presents a blind passive signal detection method for underwater sparse time-spreading distortion (TSD) channels, employing a dictionary learning (DL) algorithm. This approach estimates and separates the unknown signal from the unknown channel impulse response. A log-likelihood ratio detector is derived and utilized for sparse TSD channels. Simulations and underwater experiments with a vector sensor are conducted to evaluate the performance of the proposed DL-based blind passive method and compare it with other approaches. The improved detection probabilities achieved by this blind method demonstrate its effectiveness in the detection of unknown signals within TSD channels.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Adaptive physics-informed neural networks for underwater acoustic field predictiona).","authors":"Zhengyi Li, Ting Zhang, Lei Cheng","doi":"10.1121/10.0036834","DOIUrl":"https://doi.org/10.1121/10.0036834","url":null,"abstract":"<p><p>This paper introduces an adaptive physics-informed neural network for predicting underwater pressure fields. A gradient-based adaptive weighting method is proposed to address the imbalance between physics-constrained and data-fidelity terms, effectively capturing complex field structures and preserving important modal features. The origin of this imbalance is also analyzed, providing insight into the limitations of fixed-weight approaches. Validated through simulations and experimental data, this method demonstrates accurate predictions across pressure fields with varying structures and frequencies, including complex multimodal patterns. The results highlight the robustness and effectiveness of this adaptive approach, making it a promising solution for practical underwater acoustic field reconstruction.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effects of reference sound speed on underwater acoustic direction-of-arrival estimation with horizontal plane array.","authors":"Feitong Chen, Lianghao Guo, Yuhan Liu, Jianjun Liu, Weiyu Zhang, Jiapeng Song, Ge Dong","doi":"10.1121/10.0036837","DOIUrl":"https://doi.org/10.1121/10.0036837","url":null,"abstract":"<p><p>Direction-of-arrival (DOA) estimation of an underwater acoustic target is usually dependent on the selection of reference sound speed. For a horizontal line array, severe error of DOA estimation is induced when reference sound speed diverges from phase velocity. For a horizontal plane array, this work investigates the effects of reference sound speed on DOA estimation based on normal-mode theory, finding an independence between estimated azimuth and reference sound speed. Simulated and experimental results demonstrate that azimuth can be unbiasedly estimated and is irrelevant to reference sound speed below an upper bound in environments with various sound speed profiles.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"5 6","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}