Hasil untuk "Acoustics. Sound"

E. Morton

Lauri Savioja, Peter Svensson

Computerized room acoustics modeling has been practiced for almost 50 years up to date. These modeling techniques play an important role in room acoustic design nowadays, often including auralization, but can also help in the construction of virtual environments for such applications as computer games, cognitive research, and training. This overview describes the main principles, landmarks in the development, and state-of-the-art for techniques that are based on geometrical acoustics principles. A focus is given to their capabilities to model the different aspects of sound propagation: specular vs diffuse reflections, and diffraction.

L. Brekhovskikh, Y. Lysanov, R. Beyer

Hao Jiang, Edgar Choueiri

Deep learning-based Personal Sound Zones (PSZs) rely on simulated acoustic transfer functions (ATFs) for training, yet idealized point-source models exhibit large sim-to-real gaps. While physically informed components improve generalization, individual contributions remain unclear. This paper presents a controlled ablation study on a head-pose-conditioned binaural PSZ renderer using the Binaural Spatial Audio Neural Network (BSANN). We progressively enrich simulated ATFs with three components: (i) anechoically measured frequency responses of the particular loudspeakers(FR), (ii) analytic circular-piston directivity (DIR), and (iii) rigid-sphere head-related transfer functions (RS-HRTF). Four configurations are evaluated via in-situ measurements with two dummy heads. Performance metrics include inter-zone isolation (IZI), inter-program interference (IPI), and crosstalk cancellation (XTC) over 100-20000 Hz. Results show FR provides spectral calibration, yielding modest XTC improvements and reduced inter-listener IPI imbalance. DIR delivers the most consistent sound-zone separation gains (10.05 dB average IZI/IPI). RS-HRTF dominates binaural separation, boosting XTC by +2.38/+2.89 dB (average 4.51 to 7.91 dB), primarily above 2 kHz, while introducing mild listener-dependent IZI/IPI shifts. These findings guide prioritization of measurements and models when constructing training ATFs under limited budgets.

Yubing Yang, Xukun Yin, Xiu Yang et al.

Helicobacter pylori infection is closely associated with chronic gastritis, peptic ulcers, and gastric cancer, rendering rapid and noninvasive diagnostic technologies clinically essential. Current breath tests, such as the 13C-urea breath test (13C-UBT), typically rely on breath collection bags followed by offline analysis, which limits real-time monitoring capabilities. To overcome this constraint, we presented a mid-infrared photoacoustic spectroscopy (MIR-PAS) system for real-time detection of CO2 isotopes and evaluation of 13C-UBT responses. A dual-channel differential resonant photoacoustic cell (DPAC) with a minimal sample volume of 10.3 mL was designed to enhance acoustic signal collection, achieving a resonance frequency of 3775.7 Hz and a Q-factor of 27. Target absorption lines of 12CO2 (2299.64 cm-¹) and 13CO2 (2299.80 cm-¹) were selected within the strong ν3 band to ensure high-resolution isotopic discrimination using a 4.35 μm quantum cascade laser. The sensor demonstrated excellent linear response (R2 > 0.994) across 500–2500 ppm and achieved detection limits of 8.98 ppb for 12CO2 and 2.81 ppb for 13CO2 with the optimal averaging. δ13C measurements exhibited a precision of 0.066 ‰ at 76 s averaging time. Breath-sampling tests further revealed distinct temporal release patterns of CO2 isotopes during exhalation. These results confirmed that the developed MIR-PAS system provides a compact, sensitive, and robust platform for isotopic CO2 analysis and demonstrates strong potential for point-of-care H. pylori diagnostics.

Zhiwang Zhang, Qi Wei, Ying Cheng et al.

Jiuyang Lu, Chunyin Qiu, M. Ke et al.

Summary form only given. Valleytronics is quickly emerging as an exciting field in fundamental and applied research. In this Letter, we study the acoustic version of valley states in sonic crystals and reveal a vortex nature of such states. Besides the selection rules established for exciting valley polarized states, a mimicked valley Hall effect of sound is proposed further. The extraordinary chirality of valley vortex states, detectable in experiments, may open new possibility in sound manipulations. This is appealing to scalar acoustics that lacks spin degree of freedom inherently. Besides, the valley selection enables a handy way to create vortex matter in acoustics, in which the vortex chirality can be controlled flexibly. Potential applications can be anticipated with the exotic interaction of acoustic vortices with matter, such as to trigger the rotation of the trapped microparticles without contact.

Amir Salimi, Abram Hindle, Osmar R. Zaiane

Manual sound design with a synthesizer is inherently iterative: an artist compares the synthesized output to a mental target, adjusts parameters, and repeats until satisfied. Iterative sound-matching automates this workflow by continually programming a synthesizer under the guidance of a loss function (or similarity measure) toward a target sound. Prior comparisons of loss functions have typically favored one metric over another, but only within narrow settings: limited synthesis methods, few loss types, often without blind listening tests. This leaves open the question of whether a universally optimal loss exists, or the choice of loss remains a creative decision conditioned on the synthesis method and the sound designer's preference. We propose differentiable iterative sound-matching as the natural extension of the available literature, since it combines the manual approach to sound design with modern advances in machine learning. To analyze the variability of loss function performance across synthesizers, we implemented a mix of four novel and established differentiable loss functions, and paired them with differentiable subtractive, additive, and AM synthesizers. For each of the sixteen synthesizer--loss combinations, we ran 300 randomized sound-matching trials. Performance was measured using parameter differences, spectrogram-distance metrics, and manually assigned listening scores. We observed a moderate level of consistency among the three performance measures. Our post-hoc analysis shows that the loss function performance is highly dependent on the synthesizer. These findings underscore the value of expanding the scope of sound-matching experiments and developing new similarity metrics tailored to specific synthesis techniques rather than pursuing one-size-fits-all solutions.

Jing Liu, Enqi Lian, Moyao Deng

An abstract sound is defined as a sound that does not disclose identifiable real-world sound events to a listener. Sound fusion aims to synthesize an original sound and a reference sound to generate a novel sound that exhibits auditory features beyond mere additive superposition of the sound constituents. To achieve this fusion, we employ inversion techniques that preserve essential features of the original sample while enabling controllable synthesis. We propose novel SDE and ODE inversion models based on DPMSolver++ samplers that reverse the sampling process by configuring model outputs as constants, eliminating circular dependencies incurred by noise prediction terms. Our inversion approach requires no prompt conditioning while maintaining flexible guidance during sampling.

M Sineau, F Mietlicki, D Bernfeld et al.

Energy noise indicators are generally used to characterize the exposure of populations to transportation noise in relation to their long-term annoyance, but they do not adequately reflect the repetitive nature of noise peaks generated by railway traffic. The GENIFER project aims to test a study protocol designed to rank railway noise events according to the instantaneous annoyance they cause to residents. This study will be carried out in a sector exposed to railway noise in the {Î}le-de-France region and will require the recruitment of 60 volunteer local residents. It will propose the use of innovative tools for collecting information, including an electronic remote-control allowing participants to rate the annoyance they feel when trains pass by, and noise sensor instrumentation allowing the simultaneous collection of the acoustic characteristics of railway noise peaks. It also includes semi-directive interviews and a questionnaire to identify co-determinants of annoyance. The instantaneous annoyance scores collected will also be compared with those obtained from commented listening to sound samples of passing trains. In addition to assessing the acceptability of the protocol by the participants, this study aims to validate the feasibility of ranking railway noise events according to their acoustic characteristics in terms of the annoyance expressed.

Antoni Jérôme, Duvauchelle Philippe, Ege Kerem et al.

The Laboratoire Vibrations Acoustique is a research unit of INSA Lyon, founded in the late 1960s to study vibrations and their consequences on noise emitted by machines and structures. The aim of this article is to review the historical contributions and main developments of the laboratory over the last fifty years. After examining the early years of the laboratory, the authors retrace the developments and key scientific contributions that have enabled it to gain renown at national and international levels in the field of vibration and acoustical engineering.

Zhuocheng Xu, Catherine Tonry, Milo S.P. Shaffer et al.

This study investigates the mesoscale deagglomeration mechanisms of multi-walled carbon nanotubes (MWCNTs) in aqueous solutions with and without added surfactant (Triton X-100), using high-speed imaging and numerical simulations. High-speed observations revealed that within the cavitation zone (CZ, defined as the region of high bubble intensity), the addition of surfactant had no obvious effects on deagglomeration behaviour, with most agglomerates remaining intact and only occasional fragmentation events observed. In contrast, in regions outside the CZ, surfactant addition significantly increased the number and stability of microbubble clusters, leading to more frequent interactions with MWCNT agglomerates. Numerical simulations performed under matched experimental conditions confirmed a spatial variation in bubble dynamics, with enhanced microbubble formation and persistence in surfactant-containing solutions, particularly at distances away from the sonotrode. These findings provide direct mechanistic evidence that surfactant not only stabilises dispersed CNTs but also facilitates microbubble-mediated deagglomeration outside the CZ. The results highlight the role of structured bubble activity in extending the effective dispersion region during ultrasonication, offering insight into the optimisation of CNT processing in surfactant-assisted systems.

Jian Kang

In the field of environmental acoustics, the conventional approach of reducing ‘sound level’ does not always deliver the required improvements in quality of life. Soundscape, defined by the ISO as the ‘acoustic environment as perceived or experienced and/or understood by a person or people, in context’, promotes a holistic approach, regarding sounds as ‘resources’ rather than just ‘wastes’. The first part of this review/position paper, mainly using the works by the author and the teams/collaborators as examples, discusses the current developments in soundscape, in terms of soundscape understating and exchanging, collecting and documenting, harmonising and standardising, creating and designing, and outreaching, showing that while considerable works have been carried out, much work is still needed, in terms of basic research, and more importantly, research towards practice. The second part of this paper then explores a soundscape approach in the urban sound design/planning process. With a proposed framework for designing soundscape in urban open public spaces, considering four key components, including characteristics of each sound source, acoustic effects of the space, social/demographic aspect of the users, and other physical conditions, design potentials are demonstrated.

Gabriel Bibbó, Thomas Deacon, Arshdeep Singh et al.

This paper presents a residential audio dataset to support sound event detection research for smart home applications aimed at promoting wellbeing for older adults. The dataset is constructed by deploying audio recording systems in the homes of 8 participants aged 55-80 years for a 7-day period. Acoustic characteristics are documented through detailed floor plans and construction material information to enable replication of the recording environments for AI model deployment. A novel automated speech removal pipeline is developed, using pre-trained audio neural networks to detect and remove segments containing spoken voice, while preserving segments containing other sound events. The resulting dataset consists of privacy-compliant audio recordings that accurately capture the soundscapes and activities of daily living within residential spaces. The paper details the dataset creation methodology, the speech removal pipeline utilizing cascaded model architectures, and an analysis of the vocal label distribution to validate the speech removal process. This dataset enables the development and benchmarking of sound event detection models tailored specifically for in-home applications.

Shitong Fan, Feiyang Xiao, Wenbo Wang et al.

Microphone array techniques are widely used in sound source localization and smart city acoustic-based traffic monitoring, but these applications face significant challenges due to the scarcity of labeled real-world traffic audio data and the complexity and diversity of application scenarios. The DCASE Challenge's Task 10 focuses on using multi-channel audio signals to count vehicles (cars or commercial vehicles) and identify their directions (left-to-right or vice versa). In this paper, we propose a graph-enhanced dual-stream feature fusion network (GEDF-Net) for acoustic traffic monitoring, which simultaneously considers vehicle type and direction to improve detection. We propose a graph-enhanced dual-stream feature fusion strategy which consists of a vehicle type feature extraction (VTFE) branch, a vehicle direction feature extraction (VDFE) branch, and a frame-level feature fusion module to combine the type and direction feature for enhanced performance. A pre-trained model (PANNs) is used in the VTFE branch to mitigate data scarcity and enhance the type features, followed by a graph attention mechanism to exploit temporal relationships and highlight important audio events within these features. The frame-level fusion of direction and type features enables fine-grained feature representation, resulting in better detection performance. Experiments demonstrate the effectiveness of our proposed method. GEDF-Net is our submission that achieved 1st place in the DCASE 2024 Challenge Task 10.

Eric Grinstein, Elisa Tengan, Bilgesu Çakmak et al.

Abstract In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many works have analysed and extended the original SRP method to reduce its computational cost, to allow it to locate multiple sources, or to improve its performance in adverse environments. In this work, we review over 200 papers on the SRP method and its variants, with emphasis on the SRP-PHAT method. We also present eXtensible-SRP, or X-SRP, a generalized and modularized version of the SRP algorithm which allows the reviewed extensions to be implemented. We provide a Python implementation of the algorithm which includes selected extensions from the literature.

Lihao Wang, Haohua Lv, Yaohong Zhao et al.

Hydrogen cyanide (HCN) is a toxic industrial chemical, necessitating low-level detection capabilities for safety and environmental monitoring. This study introduces a novel approach for detecting hydrogen cyanide (HCN) using a clamp-type custom quartz tuning fork (QTF) integrated with a dual-tube acoustic micro-resonator (AmR) for enhanced photoacoustic gas sensing. The design and optimization of the AmR geometry were guided by theoretical simulation and experimental validation, resulting in a robust on-beam QEPAS (Quartz-Enhanced Photoacoustic Spectroscopy) configuration. To boost the QEPAS sensitivity, an Erbium-Doped Fiber Amplifier (EDFA) was incorporated, amplifying the laser power by approximately 286 times. Additionally, a transformer-based U-shaped neural network, a machine learning filter, was employed to refine the photoacoustic signal and reduce background noise effectively. This combination yielded a significantly low detection limit for HCN at 0.89 parts per billion (ppb) with a rapid response time of 1 second, marking a substantial advancement in optical gas sensing technologies. Key modifications to the QTF and innovative use of AmR lengths were validated under various experimental conditions, affirming the system's capabilities for real-time, high-sensitivity environmental monitoring and industrial safety applications. This work not only demonstrates significant enhancements in QEPAS but also highlights the potential for further technological advancements in portable gas detection systems.

K.K. Nejumal, M.I. Satayev, Manoj P. Rayaroth et al.

The degradation of recalcitrant organic pollutants by sulphate radical (SO4•−) represents one of the most recent developments in oxidation-based water treatment. In most cases, persulfate (PS) acts as a precursor of sulphate radicals. This study employed ultrasound-activated PS to generate reactive species, facilitating the degradation of bisphenol S (BPS), a well-known contaminant of emerging concern (CECs). An ultrasound with a frequency of 620 kHz and 80 W power was utilised for the degradation studies. The applied oxidation system successfully resulted in the complete degradation of BPS in both pure and real environmental water samples. Additionally, the Chemical oxygen demand (COD) was reduced to an acceptable limit in both matrices, with a reduction of 85 % in pure water and 73 % in river water. The degradation was monitored by varying chemical parameters such as pH, inorganic ions, and organics concentration. The results indicate that under specific pH conditions, the degradation efficiency followed the order of pH 3 > 4 > 7 > 11. The presence of coexisting matrices suppressed the efficiency by scavenging the reactive species. Utilizing high-resolution mass spectrometry (HRMS) analysis, this study identified seven intermediate products during identified during the degradation of BPS. Furthermore, a comprehensive mechanism has been deduced for the transformation and degradation process. All the results presented in this study underscore the applicability of the US/PS system in the removal of CECs.

Xiangning Bu, Zheng Tong, Muhammad Bilal et al.

This study aimed to investigate the effect of ultrasonic power and temperature on the impurity removal rate during conventional and ultrasonic-assisted leaching of aphanitic graphite. The results showed that the ash removal rate increased gradually (∼50 %) with the increase in ultrasonic power and temperature but deteriorated at high power and temperature. The unreacted shrinkage core model was found to fit the experimental results better than other models. The Arrhenius equation was used to calculate the finger front factor and activation energy under different ultrasonic power conditions. The ultrasonic leaching process was significantly influenced by temperature, and the enhancement of the leaching reaction rate constant by ultrasound was mainly reflected in the increase of the pre-exponential factor A. Ultrasound treatment improved the efficiency of impurity mineral removal by destroying the inert layer formed on the graphite surface, promoting particle fragmentation, and generating oxidation radicals. The poor reactivity of hydrochloric acid with quartz and some silicate minerals is a bottleneck limiting the further improvement of impurity removal efficiency in ultrasound-assisted aphanitic graphite. Finally, the study suggests that introducing fluoride salts may be a promising method for deep impurity removal in the ultrasound-assisted hydrochloric acid leaching process of aphanitic graphite.

Morteza Abedini, Stefanie Hanke, Fabian Reuter

We quantitatively study cavitation damage non-invasively, in-place and time-resolved at microsecond resolution. A single, laser-induced bubble is generated in an aqueous NaCl solution close to the surface of an aluminum sample. High-speed chronoamperometry is used to record the corrosion current flowing between the sample and an identical aluminum electrode immersed in the same solution. This configuration makes it possible to measure the cavitation damage in the nanometer thin passive layer of the aluminum surface via the corrosion current from the repassivation. Synchronously with the corrosion current, the bubble dynamics is recorded via high-speed imaging. Correlation between the two measurements allows contributing cavitation damage to the respective stages of the bubble dynamics. The largest cavitation-induced currents were observed for the smallest initial bubble-to-surface stand-off distances. As the bubble re-expands and collapses again in several stages, further current peaks were detected implying a sequence of smaller damage. At intermediate stand-offs the bubble was not damaging and at large stand-off distances, the bubble was only damaging during the second collapse which again occurs at the solid surface.