Archives of Acoustics is an English-language peer-reviewed online quarterly journal publishing original research papers from all areas of acoustics and abstracts from some specialized acoustical conferences. It gives free internet access to its full content to current issues. Archives of Acoustics, the peer-reviewed online quarterly journal, publishes original research papers from areas of acoustics like: linear and nonlinear acoustics: theory, acoustical measurements, and instrumentation acoustics of music: music theory, signal processing, and instrument building physiological acoustics: hearing, audiology, and psychoacoustics speech processing and communication systems: speech production and perception, voice recognition and control architectural, building, and environmental acoustics and soundscape computational and numerical acoustics sound and ultrasound in biology and medicine: ultrasonic imaging, ultrasonography, high-intensity ultrasound, therapeutic ultrasound electroacoustics: research in the field of microphones, loudspeakers, headphones, accelerometers, acoustic calibrators noise, noise control, and vibration: theory and instrumentation for noise determination and sound quality criteria, audio signal processing and transducers, acoustic materials sonochemistry: acoustic cavitation, sonoprocessing, and all aspects of physical and chemical effects of sound ultrasound and ultrasonic transducers underwater acoustics: acoustical oceanography and fisheries acoustics acousto-optics artificial intelligence in acoustic research This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. All articles are published on Creative Commons licence CC BY 4.0. Archives of Acoustics is available in Diamond Open Access and no fees are charged to the authors or readers. Journal Metrics MNiSW (2024): 100 | Impact Factor 2025: 1.1 (2024: 0.9) | CiteScore 2025: 1.6 (2024: 1.6) | SJR 2025: 0.237 (2024: 0.233) | SNIP 2025: 0.509 (2024: 0.597)
Institute of Fundamental Technological Research (IPPT) of the Polish Academy of Sciences
Copyright on any open access article in the Archives of Acoustics published by the Polish Academy of Sciences and the Institute of Fundamental Technological Research Polish Academy of Sciences is retained by the author(s). The authors grant the Polish Academy of Sciences and the Institute of Fundamental Technological Research Polish Academy of Sciences a license to publish the article and identify themselves as the original publisher. The authors also grant any user the right to use the article freely as long as its integrity is maintained and its original authors, citation details, and publisher are identified. The Creative Commons Attribution 4.0 International CC BY 4.0 formalizes these and other terms and conditions of publishing articles. Exceptions to copyright policy For the articles that were published between 2019– 2023 (including No. 1 and 2, 2023), the policies are as follows: The Creative Commons Attribution License-ShareAlike 4.0 formalizes these and other terms and conditions of publishing articles: https://creativecommons.org/licenses/by-sa/4.0/. For the articles which were previously published, before year 2019, policies that are different from the above. In all such, access to these articles is free from fees or any other access restrictions. Permissions for the use of the texts published in that journal may be sought directly from the Editorial Office of Archives of Acoustics
Study on the Physical Mechanism of Rhodamine B Degradation by Ultrasonic Cavitation Effect
The growing environmental challenge posed by textile effluents has driven the search for effective and sustainable treatment technologies. Ultrasonic degradation has emerged as a promising approach due to its ability to break down organic pollutants without introducing secondary contamination. However, the underlying physical mechanisms remain insufficiently understood, limiting the optimization of energy efficiency in practical applications. To address this gap, this study employs Rhodamine B (Rh B) as a model pollutant to investigate the fundamental principles governing ultrasonic degradation through a multi-faceted approach. First, the cavitation activity of the acoustic field under varying ultrasonic parameters is quantitatively evaluated using potassium iodide (KI) dosimetry. Second, systematic experiments are conducted to examine the synergistic effects of acoustic field intensity, sonication time, ultrasonic frequency, and power on the degradation efficiency of Rh B. Third, theoretical and numerical simulations are performed to analyze the nonlinear oscillation behavior of a single cavitation bubble and its influencing factors, thereby elucidating the physical mechanisms driving degradation. The experimental results reveal that bubble oscillation-induced cavitation generates localized high temperatures and pressures, which facilitate the cleavage of molecular bonds in Rh B. The degradation rate exhibits a positive correlation with both cavitation activity and acoustic field intensity, synergistically modulated by the operational parameters. A key novelty of this work lies in establishing an explicit correlation between parametric experimental results and detailed bubble dynamics simulations, providing mechanistic insights that extend beyond phenomenological observation. Together, these findings offer a theoretical and experimental foundation for optimizing energy efficiency in the ultrasonic degradation of organic pollutants.
Copyright (c) 2026 Jiayuan Wang, Yan Ma https://creativecommons.org/licenses/by/4.0
Low Noise Optimization of Automotive Air Conditioning Based on Response Surface Methodology
Air conditioning is an important contributor to in-vehicle noise. In order to achieve low noise optimization, investigations were performed in a typical air conditioning unit. Computational fluid dynamics and computational aeroacoustics were combined to simulate the noise characteristics. Steady and transient simulations were conducted to identify noise sources, revealing that the dipole noise is mainly distributed on the fan blades and the volute tongue, and the fan contributes more significantly to the far-field noise. Based on the response surface methodology (RSM), three key structural parameters of the fan-volute tongue clearance, volute tongue radius, and blade outlet angle were selected as design variables, while the far-field A-weighted sound pressure level (SPL) was set as the response index. The final optimization parameters are: volute tongue clearance of 13.36 mm, volute tongue radius of 11.83 mm, and blade outlet angle of 110°. The far-field SPL is reduced from 61.8 dB to 55.5 dB, with a relative reduction of 10.2 %. This research validates the effectiveness and reliability of the proposed method, providing an efficient and systematic technical reference for the noise reduction design of automotive air conditioning systems.
Copyright (c) 2026 Cheng Qian, Daqian Wang, Hao Wang, Fushen Tang, Min Lin, Jinjin Xu https://creativecommons.org/licenses/by/4.0
Experimental verification of the usefulness of G-weighted level in the assessment of infrasound noise from a wind farm
Environmental assessments of wind turbine noise commonly use microphone heights of 1.5 m or 4 m above ground level, whereas wind turbine measurement standards recommend ground-level measurements on a board to reduce wind-induced interference. This study addresses this methodological uncertainty by comparing four microphone configurations under identical in-situ conditions and relating the obtained indicators to turbine operating parameters. Measurements were performed 250 m downwind of a 2 MW Vestas V90 turbine for four configurations: board-mounted microphones with single and double windscreens, and tripod-mounted microphones at 1.5 m and 4 m above ground level. The analysis focused on G-weighted sound pressure levels and their relationship with wind speed, rotor speed and electrical power. The board-mounted configuration with a double windscreen produced the most stable time series and showed the strongest relationship with turbine operation, while being less sensitive to local near-ground wind variability than the elevated configurations. The results support the use of enhanced board-mounted wind protection for robust in-situ assessment of wind turbine infrasound.
Copyright (c) 2026 Dominik Mleczko, Tadeusz Wszołek, Paweł Pawlik, Paweł Małecki, Bartłomiej Stępień, Maciej Kłaczyński https://creativecommons.org/licenses/by/4.0
Soundscape of Nansen Basin – Central Arctic Ocean
This work mainly focuses on a deepwater soundscape study in the Nansen Basin, Central Arctic Ocean, by using Ambient Noise Measurement System (ANMS) data, which was deployed as part of the Nansen Environmental and Remote Sensing Center (NERSC-4) mooring from September 2019 to July 2020. The main objective of the work is to study the sources of underwater noise of the Central Arctic Ocean (CAO) along with their characteristic patterns. Also in this work, the seasonal variation of the sound pressure level of CAO is studied. The seasonal variation of the sound pressure level of the CAO is maximum in summer, and the minimum seasonal variation was observed during spring. The difference in seasonal variability in 1/3 octave band frequencies between summer and spring was 4.1 dB (re 1 μPa²/Hz). Shipping and marine species are the most dominant noise sources of the Central Arctic Ocean. Bowhead whales and bearded seals are the most common marine species observed in this location. The bearded seal vocalisation is more intense between 300 and 700 Hz. Bowhead whales produce two different types of simple calls i.e., sound patterns : one is S-moans, and the other is V-moans. The S-moan patterns are mainlydominated by low frequencies i.e., below 600 Hz. The V-moans patterns are dominated in the frequency range of 300 to 1230 Hz. The killer whales are also observed in the study location, which represents a shifting Arctic environment. The soundscape generated by killer whales is observed between 160 Hz and 2 kHz.
Copyright (c) 2026 Sunil Kumar Mohanta, M.C. Sanjana, Latha Ganesan, Arunbabu Elangovan, Kannan Raja https://creativecommons.org/licenses/by/4.0
Speed-confounded before–after assessment of tramway pass-by noise under track-renewal field conditions
This study investigates the system-level acoustic response of tramway track renewal under real urban operating conditions, with emphasis on the confounding role of operating speed in before–after comparisons. Pass-by noise measurements were conducted on a tram route in Poznan before (2022) and after (2025) renewal, when a conventional ballasted track was replaced by a ballastless system. During the same period, mean pass-by speed increased from 25.9 to 58.1 km/h. Energetic, psychoacoustic, and spectral indicators were analysed using direct comparisons, quartile-based speed sensitivities, and an integrated year–speed–tram type regression model. The direct comparison showed an increase in LAeq of +3.37 dB, while SEL remained nearly unchanged (Δ ≈ −0.06 dB), indicating that higher instantaneous levels were largely offset by shorter pass-by durations. Spectral analysis revealed lower measured levels of approximately 4–11 dB in the 125–200 Hz range and localised increases of up to 7–11 dB around 1.6–2 kHz. Quartile-based per-km/h derivatives indicated lower 2025 local sensitivities for LAeq, SEL, and loudness N in the pooled dataset. However, speed-doubling sensitivities showed that this apparent flattening was partly scale-dependent and not uniform across quantiles. The integrated model provided supportive evidence for changed metric–speed relationships, particularly for LAeq, although common-reference slope estimates were partly extrapolative because of limited speed overlap. The results demonstrate the usefulness of speed-sensitive analysis for interpreting before–after tramway noise measurements under changing operating regimes and should be regarded as system-level field-condition responses rather than isolated causal effects of track renewal.
Copyright (c) 2026 Tomasz Nowakowski, Jacek Dwornik, Michał Strzelczyk https://creativecommons.org/licenses/by/4.0
Riemannian Geometric Characterization of Underwater Biological Signals via Fisher-Optimized SPD Manifolds
Automated fish welfare monitoring in intensive aquaculture is hindered by environmental noise, individual variability, and data scarcity. These challenges have not been fully resolved by existing deep learning approaches. Traditional computer-vision methods are constrained by underwater turbidity, whereas Passive Acoustic Monitoring (PAM) offers a promising non-invasive alternative for assessing aquatic environments. This study proposes Fisher-SPD, a lightweight, geometry-aware framework for classifying the acoustic behaviour of cage-farmed Larimichthys crocea. A Fisher-score mechanism adaptively selects discriminative frequency bands, effectively filtering complex broadband noise commonly found in commercial sea cages. Acoustic segments are modelled as Symmetric Positive Definite (SPD) covariance matrices and mapped onto a linear tangent space via the Log-Euclidean Metric, preserving intrinsic statistical structure even under data-scarce conditions. Furthermore, a Physics-Consistency Masking mechanism applies source-level physical priors as hard inference-time constraints to robustly suppress false positives originating from background interference. Under a strict Leave-One-Subject-Out Cross-Validation (LOSO-CV) protocol, the framework achieved a mean zero-shot accuracy of 89.22% ± 2.59%, significantly outperforming ResNet-18 and other deep learning baselines, while maintaining a low inference latency of only 3.60 ms on edge devices. Through few-shot domain calibration, the system achieved 92.86% accuracy in a dual-fish overlapping-source environment. Ultimately, this framework provides a robust, data-efficient solution for real-time stress detection and welfare monitoring in modern intensive aquaculture.
Copyright (c) 2026 Lu Cao, Yang Chen, Zhaochen Shen, Qiang Fang, Yun Gao, Shipeng Yu, Shenqiu Han, Binqiang Sun, Jian Qiu, Zhongyan Huo https://creativecommons.org/licenses/by/4.0
Optimized Hydrophone Array Empowering Deep Learning–Based Phase Error Correction in Synthetic Aperture Sonar
This study addresses motion robust synthetic aperture sonar by coupling deep learning-based phase error estimation with hydrophone array optimization under 6 degrees of freedom. The objective is to deliver low sidelobe and high-fidelity imagery when surge, sway, heave, roll, pitch, and yaw inject residual phase errors that conventional autofocus and inertial aiding do not fully remove. The method is physics informed and trains an optimized array to predict residual phase from profile stacks and small image patches using a composite loss that blends image consistency, smooth proxies for peak and integrated sidelobe ratios, and phase smoothness. Array geometry is expressed in closed form and is co tuned in the loop with the corrector so that motion sensitivity is reduced before phase correction. Four hydrophone arrays are examined, namely a planar dual spiral, two helices on a cylinder, a hemispherical Fibonacci layout, and an optimized oblate hemisphere with equatorial densification and a mild tilt. Evaluation spans 24 scenarios across 6 motion axes over a 16 targets grid with PSLR, ISLR, PSNR, and RMSE as metrics. Three dimensional and nearly isotropic layouts consistently outperform planar and cylindrical baselines after correction. The optimized array ranks first overall, typically reaching side-lobe floors near −26 to −27 dB with PSNR near 49 to 50 dB and RMSE near 0.0033 and shows aggregated gains over the planar baseline of about −8 dB in sidelobe metrics and about +12 dB in PSNR, while retaining smaller but measurable advantages over the hemi-spherical Fibonacci design. The contribution unifies physics informed deep correction with interpretable array design that advances motion robust SAS image quality and offers actionable guidance for future hydrophone arrays.
Copyright (c) 2026 Hamid Hajirahimi Kashani, Seyed Alireza Seyedin https://creativecommons.org/licenses/by/4.0
The Mechanism of Formation of the Cutoff Frequency in an Acousto-Optic Delay Line and Some Proposals for its Measurement
The structure of the acousto-optic delay line and possible areas of its application are discussed. The necessity of determining the cutoff frequency of the acousto-optic delay line in all areas of its application is substantiated. The relationship between the cutoff frequency of an electric circuit and its time constant is discussed. The obtained result is extrapolated to the acousto-optic delay line, in which the cutoff frequency is formed by a completely different mechanism. The mechanism of cutoff frequency formation in the acousto-optic delay line is discussed. It is shown that the cutoff frequency in the acousto-optic delay line is formed due to the finite velocity of interaction of the acoustic wave with the light beam in the photoelastic medium. Two methods for measuring the cutoff frequency of the acousto-optic delay line are discussed: the method of system parametric measurement and the method of cursor measurement. The system-parametric method for measuring the cutoff frequency of the acousto-optic delay line is implemented based on the known values of the laser beam diameter and the velocity of propagation of the acoustic wave in the photoelastic medium. The cursor method for measuring the cutoff frequency of the acousto-optic delay line is implemented based on the parameters of the oscillogram of its response to the input action in the form of a rectangular pulse. Theoretical and experimental aspects of the application of these methods are discussed. Corresponding numerical examples and experimental results are given.
Copyright (c) 2026 Afig Hasanov, Ruslan Hasanov, Elgun Aghayev, Rovshan Ahmadov https://creativecommons.org/licenses/by/4.0
A Study of Damage Mode Recognition of Polypropylene Fiber-Reinforced Recycled Aggregate Concrete Based on Principal Components of Acoustic Emission Signals
To investigate the principal components of acoustic emission (AE) signals and the damage modes of polypropylene fiber (PPF)-reinforced recycled concrete, ten groups of specimens with coarse aggregate (CA) replacement rates of 0% and 25% and with different particle sizes, are designed and fabricated. Uniaxial compression AE tests are conducted to obtain AE parameters during the fracture process of PPF-reinforced recycled concrete. In this study, the Pearson correlation coefficient is employed to investigate the correlations among AE parameters. Then, principal component analysis (PCA) is performed on the AE signals to conduct dimensionality reduction of the multi-dimensional data. On this basis, the optimal number of clusters for the principal components of AE signals is determined based on the silhouette coefficient. Finally, the k-means clustering algorithm is introduced to perform cluster analysis on the principal components of AE signals of PPF-reinforced recycled concrete. The clustering results are compared with each other to explore the characteristics of each cluster and to identify the corresponding damage mode for each cluster. The discriminability of AE parameters with respect to damage modes is also investigated. The research findings can provide a reference for predicting the fracture mechanism of PPF-reinforced recycled concrete.
polypropylene fiber (PPF)-reinforced recycled concrete
Copyright (c) 2026 Qianxu Chen, Xin Yang https://creativecommons.org/licenses/by/4.0
Examination of Low-Frequency Sound Decay in Two Connected Enclosed Spaces Having Different Sound Absorption on Boundary Surfaces
In this study, a sound decay in two connected enclosed spaces was investigated. The research concerned the low-frequency range, because in this situation the sound decay is predominantly non-exponential. Numerical simulations were performed for a system of two connected rectangular subrooms. The larger subroom was highly reverberant, while the smaller subroom had walls that provided moderate sound damping. Simulation results showed that after switching off the harmonic source, a non-exponential behavior of sound decay is usually observed. This is because many eigenmodes are involved in the sound decay, hence this process strongly depends on both the source frequency and its position. Reverberant properties of the system were also determined using energy decay curves calculated by the reverse-time integration of the squared room impulse response. Simulations showed that the effect of the significant difference in sound absorption in subrooms is a wide range of modal reverberation time values, i.e., it is large for eigenmodes localized in a highly reverberant room and small for eigenmodes localized in a damped room. The analyzed room system is therefore characterized by an interesting feature resulting from the localization of eigenmodes. When the source is located in the larger subroom, slowly decaying modes localized in this subroom dominate the sound decay process. However, when the source is located in the smaller subroom, the sound decay in the larger subroom is much faster since non-localized modes with a shorter modal reverberation time are excited within this subroom.
Copyright (c) 2026 Mirosław Meissner https://creativecommons.org/licenses/by/4.0
From Speech to Underwater Acoustics: A Transfer Learning Framework for Real-Time Passive Diver Detection Using Keyword Spotting Models
Passive acoustic detection of divers faces challenges such as low signal-to-noise ratios (SNRs), data scarcity, and latency in conventional methods. This paper proposes keyword spotting for diver detection (KWS-DD) – a transfer learning framework that repurposes speech-oriented KWS models for data-efficient diver detection. Diver inhalation signatures are treated as acoustic ‘keywords,’ enabling adaptation of the transformer-based HuBERT architecture (pre-trained on speech) to identify quasi-periodic respiratory events in underwater audio. The core innovation of this work lies in adapting the state-of-the-art speech model HuBERT for accurate diver detection via non-speech inhalation acoustics. This approach eliminates the need for accumulation during the respiratory cycle, enabling real-time detection using a minimal amount of domain-specific data (120 inhalation samples). The solution, deployed in diverse marine conditions, achieved 94.4 % accuracy and 94.6 % F1-score for inhalation sounds. This represents a more than 50 % range extension over conventional methods, which proved unreliable at distances greater than 10 meters in low-SNR environments. The framework reduces false alarms caused by boat noise and generalizes to external datasets, validating cross-domain transferability. This work bridges AI-based speech processing and passive sonar signal processing, offering a resource-efficient solution for real-time underwater surveillance.
Copyright (c) 2026 Osama Deeb, Saier Mahmoud, Louay Saleh, Assef Jafar, Oumayma Al Dakkak, Ibrahim Chouaib https://creativecommons.org/licenses/by/4.0
Modeling of High-Speed Ultrasonic Testing of Railway Rails in Track Inspection
In the paper the theoretical modeling of ultrasonic testing of railway rails with high scanning speed is considered. The model for the calculation of the ultrasonic field generated by the ultrasonic transducers and the pulse echo amplitude received after wave reflection at the defect is developed. The model is based on well-established principles of elastodynamic theory: the Rayleigh–Sommerfeld integral, the Auld reciprocity relation, and the Kirchhoff approximation. It forms the basis for design of computer program to simulate ultrasonic inspections of railway rails with automated mobile systems. The major innovation introduced in the model is taking into account the high scanning speed of the ultrasonic probes over the rail head and the limited repetition rate of the ultrasonic system. The mentioned aspects of the high-speed rail testing require the revision of one of the basic paradigms of the current ultrasonic models, which assume that the scanning speed of the ultrasonic probe is negligible in comparison to the speed of ultrasonic waves propagating in the tested material. Actually, when scanning rails at a speed of 120 km/h, the ultrasonic probe can change its position up to 5 mm between transmitting and receiving ultrasonic pulses reflected from defects located in the rail foot. Such a shift in the probe position is not negligible and should be considered in calculations. As a consequence, the ultrasonic system’s slow repetition rate and fast scanning speed can make it less likely that certain rail flaws will be found. To quantitatively examine the severity of these phenomena, the new ultrasonic model and related simulation software was developed.
Copyright (c) 2026 Sławomir Mackiewicz, Zbigniew Ranachowski, Tomasz Katz, Tomasz Dębowski, Grzegorz Starzyński https://creativecommons.org/licenses/by/4.0
Musical Key Detection Using a Triple Composite Signature of Fifths
The article introduces a novel algorithm for key detection in musical compositions represented in symbolic form, such as MIDI. The method is based on the analysis of the triple composite signature of fifths, which is formed by combining the signatures of fifths obtained individually for the beginning, end, and entirety of the analyzed piece. The key is determined by the sign of the angle between the characteristic vector of the triple composite signature of fifths and the major/minor mode axis derived from that signature. To evaluate the algorithm’s effectiveness, experiments were conducted using Chopin’s Preludes, Op. 28, pieces from the Saarland Music Data: MIDI-Audio Piano Music, as well as pieces from the Schubert Winterreise Dataset. As a reference method, a correlation-based algorithm implementing various tonal profiles was used. The proposed algorithm achieved the highest accuracy for Chopin’s Preludes and the Schubert Winterreise Dataset (91.67% in both cases), while for the Saarland Music Data, its accuracy was lower than that of the correlational approaches (72.34%). The main advantages of the presented algorithm are low computational complexity, stable decision-making when extending the analytical window, as well as incorporation of expert analysis aspects, particularly by focusing on the beginning and end of the composition.
Copyright (c) 2026 Tomasz Łukaszewicz, Dariusz Kania https://creativecommons.org/licenses/by/4.0
Broadband Vibration-Isolating Metamaterial for MRI-Induced Vibrations
The magnetic resonance imaging (MRI) is an important diagnostic tool in medical field. The vibrations originated from the gradient coil of MRI system leads to loud operational noise. The study explores the numerical investigation of elastic metamaterial for attenuation of MRI induced vibrations that could radiate as sound at air-structure interface. The elastic metamaterials with embedded resonators can significantly attenuate the wave propagation by opening a local resonance bandgap. In this study the wave propagation properties of two models of elastic metamaterial are analysed. The dispersion diagrams are studied with parametric analysis investigating the influence of the different geometric features on the bandgap generation. The model the metamaterial was analysed with finite element analysis to investigate the wave attenuation performance. The frequency analysis of the multicellular model showed high transmission loss corresponding to the bandgaps in calculated dispersion diagrams. The results revealed that, the optimum model of the metamaterial showed overlap of 72.3 % with the vibration frequency range of the MRI scanner and the frequency analysis of the multicellular arrangement reported transmission loss up to 115.7 dB. These results demonstrate the potential of the such elastic metamaterial for targeted vibro-acoustic control and provide a framework for design of structures for wave attenuation in sensitive acoustic environments.
Copyright (c) 2026 Swapnil Arawade, Janusz Piotr Piechowicz https://creativecommons.org/licenses/by/4.0
Indian Sign Language Alphabet Recognition and Speech Synthesis Using a Hybrid Deep Learning Approach
Indian Sign Language (ISL) is vital for communication among India’s hearing-impaired community. However, the lack of standardised datasets and reliable identification frameworks has hampered the use of ISL in modern assistive technology. This paper presents a deep learning-based solution to robust ISL alphabet identification, with an emphasis on both accuracy and practical use. A curated static ISL alphabet collection was created by combining authoritative visual references from the official Indian Sign Language website and the Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVERI). Multiple deep learning models were trained and assessed, including CNN, ResNet-50, DenseNet-121, VGG16, MobileNetV2, and EfficientNet-B0, with a new hybrid CNN-ResNet architecture outperforming the others. 98% classification accuracy is achieved by the suggested approach, outperforming individual baseline models. Furthermore, the framework is expanded to support real-time applications, combining webcam-based capture with immediate conversion of recognized signs to textual and synthesized vocal output. A comprehensive performance evaluation, including the confusion matrix analysis and ROC curves, demonstrates the solution’s durability and practical applicability. This research enhances accessibility, promotes inclusive education, and prepares the path for scalable sign language translation systems in real-world human-machine interaction scenarios by enabling accurate and real-time ISL recognition with voice feedback.
Copyright (c) 2026 Aswani Sivan, Chandra Eswaran https://creativecommons.org/licenses/by/4.0
Construction Method of Sparse Dictionary for Multi-Order FRFT Domain Feature Fusion
Reverberation constitutes a primary source of interference for active sonar signals, particularly the intense reverberation originating from reflections of the incident signal. Sharing the same generation mechanism as the target echo, it severely hampers the extraction and analysis of the target signal. To enhance signal processing capabilities under strong reverberation, this paper proposes a sparse dictionary construction method based on multi-order fractional Fourier transform (FRFT) domain feature fusion. This method exploits the distinctive characteristics exhibited by target echoes and strong reverberation signals across different fractional transform domains to discriminate between them. It constructs sparse sub-dictionaries using these distinct fractional orders, trains the weights of each sub-dictionary via an adaptive gradient optimization strategy to achieve sparse representation of the signal, suppresses strong interference in the sparse domain, and reconstructs the target signal through a reconstruction process, thereby achieving the goal of extracting the target signal while suppressing strong interference. Results from processing lake trial data demonstrate that the proposed method can effectively extract target echo signals amidst strong reverberation, with the signal-to-reverberation ratio improvement consistently no less than 2.1 dB and reaching up to 15.6 dB. This method provides an effective approach for the processing and analysis of weak underwater signals.
Copyright (c) 2026 Tongjing Sun, Lei Chen, XiaoHong Deng https://creativecommons.org/licenses/by/4.0
Causality- and Passivity-Constrained Nonnegative Attention for Interpretable Structure-Borne Road Noise Prediction in Battery Electric Vehicles
In battery electric vehicles (BEVs), structure-borne road noise in the 20 Hz to 300 Hz band becomes more audible because the engine-masking component is largely absent, and conventional transfer-path formulations can be sensitive to suspension nonlinearity and ill-conditioned inversions. This paper presents a physics-informed, non-negative multi-modal fusion network (NN-MMFNet) that predicts in-cabin sound pressure from multipoint chassis excitations while keeping the mapping physically plausible and interpretable. The model combines a dual-stream encoder to separate transient impact signatures from steady resonance content with a strictly causal fusion/decoding pathway. A passivity-motivated spectral gain cap is applied to prevent non-physical amplification while preserving phase. To enable additive path attribution, the cross-modal attention weights are constrained to be non-negative. Training follows a sim-to-real workflow, using virtual-fleet pretraining and short fine-tuning on measured data. On a production BEV, NN-MMFNet reproduces the 20 Hz to 300 Hz spectrum with a 1.12 dB(A) global root mean square error (RMSE) at 60 km/h and a 0.14 dB error at the 128 Hz boom, outperforming transfer path analysis (TPA), frequency transfer matrix (FTM), and autoregressive moving average (ARMA) baselines. Impulse-response checks show a negligible passivity-violation rate (<0.01 %). The learned attention consistently points to a rear subframe-to-body mounting path near 128 Hz, and a targeted stiffness adjustment at this location reduces the measured cabin noise by 4.2 dB(A).
Copyright (c) 2026 Haijun Wang, Zhijie Huang, Zengjun Lu, Xianghua He, Tie Xu https://creativecommons.org/licenses/by/4.0
Dispersion Characteristics of Shear Horizontal-Waves in a Rotating Micro-Structured Plate with Restrained Boundaries
Shear horizontal (SH)-waves in plates are elastic stress disturbances that propagate along bounded surfaces, with in-plane shear motion perpendicular to the propagation direction, influenced by physical, geometric, and boundary conditions. Due to their sensitivity to surface and subsurface defects, SH-waves are widely employed in non-destructive testing (NDT), structural health monitoring (SHM), and material characterization. This study presents a theoretical investigation of SH wave propagation in a rotating, microstructural elastic plate within the framework of consistent couple stress theory (CCST), incorporating elastically restrained boundary conditions (ERBC). CCST introduces a characteristic length parameter to account for microstructural and size-dependent effects beyond classical elasticity. Restrained boundaries provide an intermediate model between idealized traction-free and rigid conditions, capturing the realistic boundary behavior encountered in practical applications. An analytical dispersion relation is derived to examine the combined effects of boundary restraints, microstructural parameters, and rotational speed on SH wave dispersion, with several special cases presented to validate the general formulation. Graphical results illustrate the influence of restraint stiffness, characteristic length, plate thickness, and rotation on SH wave dispersion characteristics. The findings may offer valuable insights for the design of advanced sensing devices, the development of non-destructive evaluation techniques, and the analysis of seismic wave propagation in rotating geophysical layers.
Copyright (c) 2026 Mandeep Kaur, Satish Kumar, Vikas Sharma https://creativecommons.org/licenses/by/4.0
Flanking Sound Transmission in Massive-Lightweight Connections
Assessing the impact of flanking sound transmission is one of the most significant challenges in the process of designing building partitions. Acoustic parameters declared by manufacturers of lightweight systems are subject to errors of up to several decibels – and in the case of inaccurate construction on site, these differences can reach even higher values. One factor contributing to this is the phenomenon known as flanking sound transmission, which involves the transmission of acoustic energy through partitions connected to the partition directly dividing two adjacent rooms. For this reason, estimating the resultant acoustic insulation of a partition, taking flanking paths into account, is crucial at an early stage of the design process to ensure compliance with the requirements outlined in standard recommendations, and the literature. Currently, there are regulations and studies that provide guidance on calculating the estimated reduction in acoustic insulation due to flanking transmission. However, in practice, situations arise that have not yet been addressed in standards or the literature. Examples include partitions made of plasterboard, which are among the most common types of partition walls in Poland, yet are not covered by current normative procedures, as well as glass systems. This study aims to further explore this topic by analysing the impact of combining a massive partition with flanking lightweight partitions for selected structures (glass, plasterboard with single or double panelling, with full or partial sound-absorbing material infill, and without infill) and connection types.
Copyright (c) 2026 Agnieszka Wójtowicz, Tadeusz Kamisiński, Jarosław Rubacha https://creativecommons.org/licenses/by/4.0
Study on Dual-Stage Amplification Cascaded Piezoelectric Transducer for High-Power Applications
To reduce the size and enhance the efficiency of cascaded sandwich transducers with conical horns, a novel structural configuration of such transducers is investigated. This transducer incorporates two sets of piezoelectric stacks, enabling two-stage amplification to improve efficiency. An equivalent circuit model of the cascaded sandwich transducer with a conical horn is established, and analytical expressions for key performance parameters, including input impedance, velocity amplification ratio, and resonant characteristics, are systematically derived. Through theoretical and simulation analyses, the dynamic influence of key structural parameters on electromechanical energy conversion efficiency is determined, specifically including the output radius of the second stage, the relative position of the variable cross-sections of two sets of piezoelectric ceramic sandwich structures, and the spacing between the two sets of piezoelectric stacks. Furthermore, a performance optimization strategy based on piezoelectric single-crystal materials is proposed. Numerical simulation results, validated against the theoretical models, reveal the governing principles of piezoelectric material properties on transducer performance. Experimental results demonstrate excellent agreement between the operational characteristics of the optimized transducer and predictions obtained from both theoretical models and finite element simulations. This work provides significant guidance for the optimization of multi-mode transducers and demonstrates promising application potential in high-power ultrasonic fields.
Copyright (c) 2026 Guo Li, Peiyu Tan, Ruihui Ma, Feilong Li, Xiaoli Zhang, Hua Tian https://creativecommons.org/licenses/by/4.0
In Memoriam Professor Eugeniusz Kozaczka
Professor Eugeniusz Tadeusz Kozaczka, member of the Polish Academy of Sciences, passed away on May 27, 2025, in Gdynia. We write these words with profound sorrow and deep regret, mourning the loss of such an exceptional person as Professor Eugeniusz Kozaczka.
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0
Impact of Perforated Sheet Geometry on the Insertion Loss of Absorptive Silencers
This study evaluates the influence of perforated sheet geometry on the acoustic and aerodynamic performance of absorptive silencers. A modular silencer is developed, enabling the installation of six different perforated metal sheets with varying hole shapes (round, square, elongated), sizes (2 mm to 20 mm), and open area ratios (22 % to 45 %). Glass wool is used as the sound-absorbing filling. Insertion loss, self-noise, and pressure drop are measured in a large reverberation chamber, within the frequency range from 50 Hz to 10 000 Hz, for airflow velocities of 4 m/s, 6 m/s, and 8 m/s. The results indicate that all configurations provide comparable attenuation at low frequencies. Silencers with small round perforations (diameter 2 mm to 6 mm) ensure higher insertion loss and lower self-noise in the mid-frequency range of 1000 Hz to 5000 Hz, without any measurable increase in pressure drop compared to variants with larger or elongated holes. For frequencies above 6300 Hz, perforated sheets with larger holes perform better. Pressure loss differences between all configurations do not exceed 1 Pa at a given flow velocity. The results confirm that aperture size is the primary parameter affecting silencer acoustic effectiveness, while aperture shape and perforation ratio are secondary. These findings provide practical guidelines for optimal silencer design in ventilation systems, ensuring maximum noise reduction with minimal airflow resistance.
Copyright (c) 2026 Kamil Wójciak, Joanna Maria Kopania, Patryk Gaj https://creativecommons.org/licenses/by/4.0
Analysis on Modal Distribution and Modal Density-Based Crossover Frequency in Cabin-Sized Enclosures
In the sound field simulation of cabin-sized enclosures, the Schroeder frequency (SF) is still employed to estimate the crossover frequency (CF) that determines the validity ranges of wave-based and geometrical acoustic methods. However, because cabin-sized enclosures exhibit distinct modal behaviors from typical medium- and large-scale rooms, the validity of SF in such enclosures has not been thoroughly tested. This study introduces the modal density-based crossover frequency (MDCF) to systematically evaluate the applicability of SF in cabin-sized enclosures. The MDCF employs the same dense modal criterion as SF. However, its modal parameters, are derived from the numerical eigenfrequency analysis. This contrasts with the SF formula, where these parameters are determined solely by the room volume and reverberation time. Ten models are constructed for evaluation, grouped into two volume sets: 8 m3 (cabin-sized) and 80 m3 (common-sized). Each set comprises five distinct geometrical shapes from rectangular models to simplified vehicle shapes. The results reveal that, for cabin-sized enclosures under low absorption boundary conditions, the MDCF is typically 70 Hz to 150 Hz lower than SF; the discrepancies decrease to 20 Hz to 50 Hz in 80 m3 rooms. Furthermore, the MDCF varies with room shapes at a constant volume, while the SF remains nearly unchanged. These findings demonstrate that MDCF provides a more reliable CF estimation for rooms with irregular shapes, highlighting the importance of considering accurate modal parameters in the acoustic analysis of cabin-sized models.
Copyright (c) 2026 Ziyu Wang, Liangfen Du, Guangzheng Yu https://creativecommons.org/licenses/by/4.0
TimeGAN and Coordinated Attention Prototype Network Based Prediction Model for Infrasound Signal
Due to the complexity of the infrasound environment and the high costs associated with data collection, frequent acquisition of infrasound data is often impractical, resulting in a limited amount of labeled data. To address the challenge of low classification prediction accuracy caused by data scarcity, this paper proposes an infrasound prediction model based on a time-series generative adversarial network (TimeGAN) and coordinated attention prototype network (CAPN) (TimeGAN-CAPN). The model begins by introducing TimeGAN, where the generative network is trained using a combination of unsupervised and supervised learning. This approach enables the network to operate within the latent space of temporal features and generate time-series data that closely aligns with the distribution of the original data. These generated samples are then combined with the original data to form an augmented dataset. Subsequently, the augmented data is input into the CAPN, which enhances the sample size per class, allowing for more precise class prototypes and improving the prediction accuracy of the model. Furthermore, the quality and diversity of the data generated by TimeGAN are quantitatively and qualitatively assessed using maximum mean discrepancy (MMD) and t-distributed stochastic neighbor embedding (t-SNE), facilitating a comparison and verification of the generated data’s performance. Experimental results show that TimeGAN-CAPN significantly outperforms the CAPN model in classification tasks with limited infrasound data, achieving an increase in accuracy of 7.15 %. This demonstrates that the proposed method is highly effective for predicting infrasound-related disasters, particularly in scenarios with small sample sizes.
time-series generative adversarial network
Copyright (c) 2026 Quanbo Lu, Xiaojuan Huang, Rao Li, Mei Li, Dong Zhu https://creativecommons.org/licenses/by/4.0
An Empirical Approach to Investigate Environmental Effects on Acoustic Signal Speed in Oceanic Layers
This paper investigates and demonstrates the effects of three significant environmental contributors: temperature, depth and salinity impact on the acoustic signal propagation across distinctive ocean layers: mixed, thermocline, and deep layers. In the field of underwater wireless sensor networks (UWSN), exact and precise determination of coordinates for sensor localization is very crucial for data validation. Temperature dominates the upper layers; depth becomes the prime factor for the deeper domain with minimal thermal variations. Salinity while having a diminished effect, facilitates minor changes in propagation and deviation of acoustic signal speed. In our work we have analyzed these interdependencies by using different empirical models (e.g., Mckenzie, Medwin) customized to each layer, accounting to their incomparable environmental parameters. In mixed layers, changes in sound speed are mainly caused by thermal factors, where depth is of minimal importance, and the influence of salinity is insignificant, but with increasing depth, the temperature begins to decrease, and depth (pressure) begins to become important, and changes in salinity and temperature become almost equivalent. By evaluating ocean layer specified empirical formulas, we have calculated the average speed of sound and measure the corresponding contribution of all parameters. Our work has provided a substructure which helps to optimize the identification or localization of UWSN nodes. The results of this work underscored the essential to have an adaptive sound speed modeling in order to achieve enhanced and precise acoustic signal communication systems.
Copyright (c) 2026 Khondoker Munim Salehin, Md. Khalid Mahbub Khan, Anisur Rahman https://creativecommons.org/licenses/by/4.0
Semi-Supervised Learning for Sediment Classification Using Convolutional Neural Networks with Digital Elevation Model and Backscatter Data
Accurate sediment classification is crucial for advancing marine research, environmental monitoring, and sustainable seabed use. However, acquiring large amounts of labeled data in such settings is often challenging, expensive, and time-consuming. To address this limitation, a semi-supervised learning framework has been proposed that leverages convolutional neural networks for sediment classification using both labeled and unlabeled data. The approach utilizes pseudo-labeling, where confident predictions on unlabeled samples are iteratively incorporated into training to enhance model generalization. The method is applied and evaluated on a dataset that includes multi-modal inputs such as a digital elevation model and multibeam sonar backscatter data. Experimental results indicate that semi-supervised learning with convolutional neural networks can achieve high classification accuracy in scenarios characterized by limited labeled data and a large volume of unlabeled data. This approach highlights the potential of deep learning combined with semi-supervised strategies for efficient underwater environment classification.
Copyright (c) 2026 Paweł Nadachowski, Zbigniew Łubniewski, Karolina Trzcińska, Radosław Wróblewski, Maria Rucińska, Jarosław Tęgowski https://creativecommons.org/licenses/by/4.0
Ultrasonic Estimation of Pressure Dependent Non-Linearity Index in Liver
This study introduces a proof-of-concept methodology for evaluating pressure-dependent non-linear acoustic properties of liver tissue. The proposed non-linearity index (NLI) is derived from echo amplitudes obtained at two substantially different acoustic pressures. Unlike previous harmonic-based approaches, the method relies solely on the fundamental frequency band, allowing clinical implementation without additional system modifications. The image acquired for the lower pressure is then amplified to correct for the pressure difference between the beams. Next, the NLI is estimated as a ratio of local amplitudes of the amplified low-pressure image (ALPI) to the high-pressure image (HPI). In the case of nonlinear media some energy of the wave is transferred from the pulse fundamental frequency to higher harmonics, which affects mainly the HPI. With the harmonics being filtered out from the signal, the HPI amplitude becomes lower than the ALPI amplitude. As a result, the NLI becomes higher than 1 and increases with the non-linearity of the imaged tissue. The hydrophone measurements were compared to the simulation (k-Wave) of the ultrasonic field in water and vegetable oil. Next, we performed NLI imaging of healthy and fatty livers using SonixTouch (Ultrasonix) systems and two acoustic pressures of 390 kPa and 1590 kPa. Preliminary studies – imaging healthy and fatty livers using SonixTouch (Ultrasonix) systems were performed on the 4 livers of the authors of the article showed that for ‘healthy’ livers the NLI was below 1.1, while in one of the authors with previously diagnosed steatosis falling between score 1 and 2, the NLI locally exceeded 1.3. These results show that the obtained NLI values increase with the degree of steatosis, which agrees with theoretical expectations based on tissue B/A coefficients. The work emphasizes methodological feasibility and physical consistency rather than clinical validation, given the limited number of volunteers and ethical restrictions on patient recruitment.
Copyright (c) 2026 Andrzej Nowicki, Jurij Tasinkiewicz, Piotr Karwat, Norbert Żołek, Ihor Trots, Ryszard Tymkiewicz https://creativecommons.org/licenses/by/4.0
Few-Shot Transfer for Speech Enhancement Using SEGAN with Stability Guardrails
High-quality speech communication is often compromised by background noise, reducing intelligibility and perceived quality.We investigate data-efficient few-shot transfer of the speech enhancement generative adversarial network (SEGAN) to a new noise domain. Starting from a generator pre-trained on VoiceBank–DEMAND, we adapt the model to MiniLibriMix using only 300 paired noisy–clean examples. To prevent overfitting and catastrophic forgetting, we introduce stable adversarial few-shot enhancement (SAFE), a three-fold stabilisation strategy with (1) exponential-moving-average (EMA) weight averaging, (2) L2-SP weight anchoring to the source-domain parameters, and (3) a teacher–student consistency loss. SAFE maintains VoiceBank performance (PESQ ≈ 1.84; STOI ≈ 90 %) and, after an optional perceptual fine-tuning stage (L1 + MR-STFT), yields substantial target-domain gains on MiniLibriMix (PESQ 1.11 → 1.26, STOI 71.5 % → 81.5 %) with only a minor source-domain trade-off in STOI. Ablation experiments demonstrate that EMA provides the strongest stabilising effect, while L2-SP and consistency regularisation offer complementary benefits. These results suggest that stable few-shot adaptation may make lightweight time-domain speech enhancers practical for rapid deployment in novel acoustic environments.
Copyright (c) 2026 Rubi Sharma, Firos A. https://creativecommons.org/licenses/by/4.0
Application of Acoustic Metamaterials in the Design of Muffling Unit of Internal Combustion Engine
Aiming at the problems of large volume, high exhaust resistance and difficulty in suppressing noise in the 500 Hz to 100 Hz frequency band of traditional internal combustion engine exhaust mufflers, a noise reduction unit design based on acoustic metamaterials is proposed. Based on the equivalent medium theory, an acoustic model with a ring structure and multi-region variable refractive index was established. Phase control is achieved by helically winding the acoustic channel to change the refractive index, and the basic dimensions of the acoustic metamaterial muffling unit are calculated. The sound field distribution, transmission loss and flow field characteristics of the muffling unit are simulated and analyzed. This structure utilizes a multi-layer acoustic channel structure, effectively alleviating the problem of insufficient low-frequency noise elimination caused by the asymmetry of Fano interference. It achieved a transmission loss of over 10 dB within 85 % of the 500 Hz to 1000 Hz frequency band, and still maintained excellent noise reduction performance under high-frequency conditions through multi-level phase control. By connecting multiple units in series, a transmission loss of 10 dB can be achieved within 85 % of the 500 Hz to 1000 Hz frequency band. The exhaust flow field of the muffling unit was simulated and analyzed. Whether used alone or in series with the traditional muffling structure, the exhaust resistance remained within the range of 360 Pa to 370 Pa. Experimental tests show that when the metamaterial muffler unit is used in combination with the traditional muffler, it effectively achieves targeted noise elimination in the 500 Hz to 1000 Hz frequency band, and also demonstrates clear noise reduction capabilities in higher frequency ranges. The high noise suppression characteristics, high gas passage characteristics and compact volume characteristics of this structure provide more potential analysis methods and design schemes for the research and development of internal combustion engine mufflers and noise reduction accessories.
Copyright (c) 2026 Tianshuo Li, Lei Zheng, Zhengyang Bi, Hongchao Ji https://creativecommons.org/licenses/by/4.0
Modeling and Investigation of a Multi-Resonant Metamaterial Sound Insulator
A design of a multi-resonant acoustic metamaterial sound insulator is proposed to attenuate multi-tonal and broadband noise. The unit cell of the metamaterial consists of a porous material with four, nine, and sixteen embedded Helmholtz resonators and its sound attenuation performance is studied using the finite element method (FEM). A theoretical approach based on the transfer matrix method is proposed and the theoretical results of the sound absorption and the transmission loss (TL) agree well with FEM results. Compared to the porous layer with one embedded resonator that presents one TL and one sound absorption resonant peak, the metamaterial made of four, nine, and sixteen embedded resonators exhibits, respectively, four, nine, and sixteen sound absorption and TL resonant peaks. The sound absorption at various incidence angles and the diffuse field sound absorption of the proposed metamaterial are studied. At each resonant frequency, the acoustic pressure reaches its maximum in the cavity of the corresponding resonator while in the associated neck, the acoustic velocity peaks alongside significant acoustic power dissipation density. As the incidence angle increases, the acoustic pressure in the cavity at the resonant frequencies decreases as well as the velocity in the necks and the power dissipation density becomes negligible, resulting in a decrease of the sound absorption. As the number of resonators within the porous layer increases, the sound absorption and the TL frequency band enlarge. Compared to the conventional porous layer, the sound absorption, and the TL are significantly improved at the resonant frequencies of the resonators.
Copyright (c) 2026 Zacharie Laly, Raymond Panneton, Noureddine Atalla, Sebastian Ghinet https://creativecommons.org/licenses/by/4.0