{"title":"The QuickGIN: Development of a rapid gap detection test for clinical temporal processing assessment.","authors":"Douglas Brungart, Alyssa Davidson, Gregory Ellis","doi":"10.1121/10.0046855","DOIUrl":"https://doi.org/10.1121/10.0046855","url":null,"abstract":"<p><p>Auditory gap detection thresholds are an important tool for evaluating temporal processing deficits in human listeners, but current tests are too cumbersome for widespread clinical use. This letter describes the development and validation of a rapid 18-trial test for assessing gap detection based on an earlier binaural tone-in-noise paradigm. Results from 616 normal-hearing listeners show psychometric properties similar to the clinical gaps-in-noise test and provide normative values that support preliminary use as a screener for temporal processing deficits in clinical populations.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149186667","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":"Acoustic field prediction in Pekeris waveguides using a learnable effective depth.","authors":"Zeyu Wang, Yongxian Wang, Yanqun Wu, Zhao Sun, Yunxiang Zhang, Houwang Tu","doi":"10.1121/10.0046924","DOIUrl":"https://doi.org/10.1121/10.0046924","url":null,"abstract":"<p><p>Predicting acoustic fields from sparse measurements using physics-informed neural networks (PINNs) is challenging under uncertain bottom geoacoustic parameters. This paper proposes a framework incorporating a learnable effective-depth bottom boundary and two-stage training strategy, called LED-PINN. For 1 km range extrapolation beyond a 3 km measurement interval (ratio 1/3), LED-PINN reduces the mean absolute error from 7.42 dB for OceanPINN, a PINN-based model for ocean acoustic field prediction, to 2.41 dB, while improving depth extrapolation and keeping the effective-depth inversion error below 0.6 m. These results demonstrate improved acoustic field extrapolation under uncertain bottom parameters.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221110","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}
Megan S Ballard, Ying-Tsong Lin, Julien Bonnel, David P Knobles, Andrew R McNeese, Preston S Wilson
{"title":"Estimating deep sediment sound speed from head waves at the New England shelf break.","authors":"Megan S Ballard, Ying-Tsong Lin, Julien Bonnel, David P Knobles, Andrew R McNeese, Preston S Wilson","doi":"10.1121/10.0046865","DOIUrl":"https://doi.org/10.1121/10.0046865","url":null,"abstract":"<p><p>Head-wave arrivals generated by explosive sources and recorded on a vertical line array were analyzed to estimate deep sediment sound-speed structure at the New England shelf break. Arrival times associated with two subsurface interfaces were identified using beamformed elevation angles and fit with a linear travel-time model. The resulting geoacoustic model includes layers with sound speeds of 1728 ± 14 and 2324 ± 55 m/s located 137 ± 36 and 410 ± 53 m below the seafloor, respectively. Predicted head-wave arrival times derived from the model are consistent with corresponding arrivals observed on an independently deployed seabed recorder.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149221140","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}
Erik Jorgensen, Megan Werner, Autumn Grove, Afton Noll
{"title":"Matching laboratory and real-world listening environments with ecological momentary assessment improves prediction of speech perception.","authors":"Erik Jorgensen, Megan Werner, Autumn Grove, Afton Noll","doi":"10.1121/10.0046844","DOIUrl":"10.1121/10.0046844","url":null,"abstract":"<p><p>Laboratory speech-in-noise measures fail to predict real-world listening performance. This study tested whether matching laboratory to real-world environments using self-reported noise sources from ecological momentary assessment (EMA) improves predictions. Speech intelligibility and listening effort were measured in virtual acoustic environments in 51 normal-hearing adults, who then self-rated both via EMA for 1 week. Laboratory intelligibility predicted real-world intelligibility only when laboratory and real-world environments were matched. Effort results were not significant. Findings suggest that environment-specific laboratory testing improves ecological validity of intelligibility measures, though environment matching explained only 1.1% of variance in real-world ratings, with individual differences accounting for substantially more.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13670081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149186589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jyrki Alakuijala, Martin Bruse, Sami Boukortt, Jozef Marus Coldenhoff, Milos Cernak
{"title":"Zimtohrli: An efficient psychoacoustic audio similarity metric.","authors":"Jyrki Alakuijala, Martin Bruse, Sami Boukortt, Jozef Marus Coldenhoff, Milos Cernak","doi":"10.1121/10.0046909","DOIUrl":"https://doi.org/10.1121/10.0046909","url":null,"abstract":"<p><p>This paper introduces Zimtohrli, an efficient full-reference audio similarity metric. Existing metrics are standardised but require a licensed implementation [Perceptual Objective Listening Quality Assessment (POLQA)], are speech-calibrated [Perceptual Evaluation of Speech Quality, Virtual Speech Quality Objective Listener (ViSQOL)], or-like the audio-domain Perceptual Evaluation of Audio Quality (PEAQ) standard (ITU-R BS.1387)-are tuned to the near-transparent range of BS.1116 tests, leaving a gap for an open metric spanning speech and full-band audio across a wide quality range. Zimtohrli pairs a 128-channel equivalent rectangular bandwidth-spaced gammatone front-end with a non-linear resonator, comparing perceptually-mapped spectrograms via modified dynamic time warping and a neurogram similarity index, optimized against human ratings. It outperforms ViSQOL and Advanced PEAQ, trails POLQA by ∼7% yet surpasses it on full-band music, running 5× faster.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278180","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}
Kay L Gemba, Nicholas C Durofchalk, Bruce Allen, Demetrius Bush, Geoffrey F Edelmann
{"title":"Basin-scale ocean acoustic telemetry: Digital waveforms for transmitting oceanographic corrections.","authors":"Kay L Gemba, Nicholas C Durofchalk, Bruce Allen, Demetrius Bush, Geoffrey F Edelmann","doi":"10.1121/10.0046923","DOIUrl":"https://doi.org/10.1121/10.0046923","url":null,"abstract":"<p><p>Basin-scale acoustic positioning, navigation, and timing are affected by ocean variability, which introduces uncertainty in acoustic travel time and position. Here, a cyclic code-shift keying (CCSK) direct-sequence spread-spectrum waveform is demonstrated for transmitting compact digital information over a 3500 km acoustic path. Information is encoded in cyclic shifts of a maximum-length sequence while retaining matched-filter compression and processing gain. Analysis of 42 transmissions at a 75-Hz center frequency shows symbol error rates of 4.8% or less for the first six symbols, with later-symbol performance degrading, consistent with finite channel coherence. A conceptual method for quantizing effective travel-time corrections and mapping them to the CCSK symbol alphabet is presented, providing a pathway toward integrated basin-scale navigation and ocean observation.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278150","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":"Acoustic analyses on German vowels in read speech, recited speech, and singing.","authors":"Franka Zebe-Sheng, Anna Immerz","doi":"10.1121/10.0046810","DOIUrl":"https://doi.org/10.1121/10.0046810","url":null,"abstract":"<p><p>On the continuum of hyper- and hypoarticulation, speech production is adjusted based on the environment and the listener to ensure intelligibility with minimal articulatory effort. The current study examines 13 German vowels produced by 16 professional female singers in read speech, recited speech, and singing. Stimuli consisted of ten original extracts from German classical art songs. The vowels' first two formants were analyzed, comparing across the three conditions. Furthermore, Euclidean distances were calculated for all vowels. Results generally indicate more hyperarticulation in recited speech and more centralization in singing. Several exceptions to this trend highlight the necessity for future research.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119541","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}
Jiarui Yin, Ran Cao, Jingwei Yin, Li Li, Dewen Li, Linjun Tan
{"title":"Block sparse Bayesian learning for broadband bearing estimation in shallow-water waveguides.","authors":"Jiarui Yin, Ran Cao, Jingwei Yin, Li Li, Dewen Li, Linjun Tan","doi":"10.1121/10.0047058","DOIUrl":"https://doi.org/10.1121/10.0047058","url":null,"abstract":"<p><p>For horizontal arrays in shallow-water waveguides, methods based on the plane wave assumption often produce biased bearing estimates because of multimode propagation. Although subspace-intersection methods reduce bias, they generally require a large array aperture to achieve satisfactory performance. This letter proposes a broadband bearing estimation method based on block sparse Bayesian learning. The proposed method groups modal steering vectors into a block-structured dictionary and exploits joint block sparsity across frequencies to estimate the bearing while mitigating estimation bias. Simulation and experimental results demonstrated that the proposed method provides sharper bearing peaks and better additive noise robustness than the comparison methods.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149278218","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":"Spaciousness as an acoustic measure of prosody in autistic children.","authors":"Boram Kim, Rhiannon Luyster, Jason Bishop","doi":"10.1121/10.0046854","DOIUrl":"https://doi.org/10.1121/10.0046854","url":null,"abstract":"<p><p>Distinctive prosody has been reported in autism, yet acoustic studies have yielded inconsistent findings, particularly for F0-related measures. Two dynamic measures, spaciousness (magnitude of pitch excursions) and wiggliness (rate of pitch-direction changes), offer alternatives, but spaciousness has not yet been applied to English-speaking autistic children. The present study therefore compared acoustic characteristics of prosody from autistic and language-skill matched nonautistic children (age 3-7) using spaciousness, wiggliness, F0 measures (mean, standard deviation, and range), and speech rate. Linear mixed-effects models revealed that only spaciousness showed significant group differences, and these differences were independent of utterance length. Replication in larger samples is warranted.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139705","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":"A study on quality, architecture, and performance relationships in sonar classifiers trained with simulated data.","authors":"Thomas E Blanford, David P Williams","doi":"10.1121/10.0046812","DOIUrl":"https://doi.org/10.1121/10.0046812","url":null,"abstract":"<p><p>Convolutional neural networks (CNNs) are commonly used to classify objects observed in synthetic aperture sonar imagery. Controlled laboratory data and complementary simulated imagery produced with physics-based acoustic scattering models were used to investigate the relationships between classification accuracy, simulation quality, and network architecture. Three experiments investigated simulation errors that arise from imperfect models, inaccurate knowledge of target shape, and inaccurate knowledge of target appearance due to partial burial. In a matched environment, results show CNN-based classifiers can be designed to be insensitive to simulation errors of a certain scale, allowing coarse, imperfect simulations for training.</p>","PeriodicalId":73538,"journal":{"name":"JASA express letters","volume":"6 10","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119517","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}