Search Results (217)

The acoustic field of an opera house is much more difficult to predict than those of concert halls because, in the fly tower, the absorption characteristics vary from time to time, according to the opera piece layout. For this reason, the paper aims to find a simplified fly tower model to be used as a fixed reference in a preliminary acoustic prediction for opera houses. Firstly, referring to a case study, the effects of the fly tower Depth and absorptive characteristics are investigated to identify the simplified model. As a traditional opera is set on an empty stage, and modern pieces are supported by a virtual projected environment, the influence of the variable stage elements on Reverberation Time RT, Clarity C80, and Strength G is considered, comparing the traditional Semiramide opera to a modern digital one, according to the Just Noticeable Difference JND. Results confirm the utility of the suggested fly tower model, which does not require any set definition. Full article

The acoustic environment of dental clinics plays a critical role in shaping patient experience, staff performance, and overall clinical effectiveness. This comprehensive review, supported by systematic search procedures, investigates how soundscapes in dental settings influence psychological, physiological, and operational outcomes. A total of 60 peer-reviewed studies were analyzed across dental, healthcare, architectural, and environmental psychology disciplines. Findings indicate that mechanical noise from dental instruments, ambient reverberation, and inadequate acoustic zoning contribute significantly to patient anxiety and professional fatigue. The review identifies emerging strategies for acoustic optimization, including biophilic and sustainable design principles, sound-masking systems, and adaptive sound environments informed by artificial intelligence. Special attention is given to the integration of lean management and circular economy practices for sustainable dental architecture. A design checklist and practical framework are proposed for use by dental professionals, architects, and healthcare planners. Although limited by the predominance of observational studies and geographic bias in the existing literature, this review offers a comprehensive, interdisciplinary synthesis. It highlights the need for future clinical trials, real-time acoustic assessments, and participatory co-design methods to enhance acoustic quality in dental settings. Overall, the study positions sound design as a foundational element in creating patient-centered, ecologically responsible dental environments. Full article

Light alloy wheel rims, despite their widespread use, remain vulnerable to fatigue-related defects and mechanical damage. This study presents a method for assessing their technical condition based on acoustic parameter analysis and classification using a deep neural network. Diagnostic data were collected using a custom-developed ADF (Acoustic Diagnostic Features) system, incorporating the reverberation time (T₆₀), sound absorption coefficient (α), and acoustic energy (E). These parameters were measured during laboratory fatigue testing on a Wheel Resistance Test Rig (WRTR) and from used rims obtained under real-world operating conditions. The neural network was trained on WRTR data and subsequently employed to classify field samples as either “serviceable” or “unserviceable”. Results confirmed the high effectiveness of the proposed method, including its robustness in detecting borderline cases, as demonstrated in a case study involving a mechanically damaged rim. The developed approach offers potential support for diagnostic decision-making in workshop settings and may, in the future, serve as a foundation for sensor-based real-time rim condition monitoring. Full article

The architecture of contemporary museums often emphasizes visual aesthetics, such as large volumes, open-plan layouts, and highly reflective finishes, resulting in acoustic challenges, such as excessive reverberation, poor speech intelligibility, elevated background noise, and reduced privacy. This study quantified the impact of surface—specific absorption treatments on acoustic metrics across eight gallery spaces. Room impulse responses calibrated virtual models, which simulated nine absorption scenarios (low, medium, and high on ceilings, floors, and walls) and evaluated reverberation time (T₂₀), speech transmission index (STI), clarity (C₅₀), distraction distance (r_D), Spatial Decay Rate of Speech (D_2,S), and Speech Level at 4 m (L_p,A,S,4m). The results indicate that going from concrete to a wooden floor yields the most rapid T₂₀ reductions (up to −1.75 s), ceiling treatments deliver the greatest STI and C₅₀ gains (e.g., STI increases of +0.16), and high-absorption walls maximize privacy metrics (D_2,S and L_p,A,S,4m). A linear regression model further predicted the STI from T₂₀, total absorption (Sabins), and room volume, with an 84.9% conditional R², enabling ±0.03 accuracy without specialized testing. These findings provide empirically derived, surface-specific “first-move” guidelines for architects and acousticians, underscoring the necessity of integrating acoustics early in museum design to balance auditory and visual objectives and enhance the visitor experience. Full article

Sound event localization and detection (SELD) is a fundamental task in spatial audio processing that involves identifying both the type and location of sound events in acoustic scenes. Current SELD models often struggle with low signal-to-noise ratios (SNRs) and high reverberation. This article addresses SELD by reformulating direction of arrival (DOA) estimation as a multi-class classification task, leveraging deep convolutional recurrent neural networks (CRNNs). We propose and evaluate two modified architectures: M-DOAnet, an optimized version of DOAnet for localization and tracking, and M-SELDnet, a modified version of SELDnet, which has been designed for joint SELD. Both modified models were rigorously evaluated on the STARSS23 dataset, which comprises 13-class, real-world indoor scenes totaling over 7 h of audio, using spectrograms and acoustic intensity maps from first-order Ambisonics (FOA) signals. M-DOAnet achieved exceptional localization (6.00° DOA error, 72.8% F1-score) and perfect tracking (100% MOTA with zero identity switches). It also demonstrated high computational efficiency, training in 4.5 h (164 s/epoch). In contrast, M-SELDnet delivered strong overall SELD performance (0.32 rad DOA error, 0.75 F1-score, 0.38 error rate, 0.20 SELD score), but with significantly higher resource demands, training in 45 h (1620 s/epoch). Our findings underscore a clear trade-off between model specialization and multifunctionality, providing practical insights for designing SELD systems in real-time and computationally constrained environments. Full article

Studies underscore the significance of coir fibers as a sustainable building material. Based on these insights, this research aims to evaluate coir fiber composite panels of various thicknesses as eco-friendly sound absorbing alternatives to synthetic construction materials like rockwool and fiberglass, aligning its use with the United Nations Sustainable Development Goals. Acoustic absorption was quantified with an impedance tube, and subsequent simulations compared the performance of coir composite panels with that of conventional materials, which constitutes an underexplored evaluation. Using 10 receiver points, the simulations reproduced the acoustic conditions of a multipurpose auditorium before and after the coir covering of parts of the rear and posterior walls. The results indicate that when coir coverings account for approximately 10% of the auditorium surface, reverberation times at 250, 500, 2000, and 4000 Hz are reduced by roughly 1 s. Furthermore, the outcomes reveal that early reflections occur more rapidly in the coir-enhanced model, while the values of the early decay time parameter decrease across all receiver points. Although the original configuration had poor speech clarity, the modified model achieved optimal values at all the measurement locations. These findings underscore the potential of coir fiber panels in enhancing acoustic performance while fostering sustainable construction practices. Full article

Churches are spaces designed with a unique acoustic identity, which is intimately connected to the oratory and musical needs of the historical period in which they were built. For instance, their typically long reverberation time is appropriate to specific uses, such as liturgical functions and choral music performances, but it may impair the repurposing of the space for other functions. Indeed, an acoustic environment suitable for choral or sacred music may not be compatible with other musical genres such as chamber music, solo performances, or small instrumental ensembles, which require greater clarity and frequency-balanced acoustic properties. In such cases, careful analysis of the environment and specific acoustic conditioning become essential steps to enable the space to be used for novel purposes, without compromising its artistic and historical integrity. In this work, we analyze and improve the acoustics of the church of Saints Marcellino and Pietro through space-time acoustic measurements and simulations. After developing and validating our model, we propose various solutions to optimize the church acoustics, transforming it into a functional concert hall while preserving its original identity and artistic grandeur. Full article

As a fundamental technology in environmental perception, sound source localization (SSL) plays a critical role in public safety, marine exploration, and smart home systems. However, traditional methods such as beamforming and time-delay estimation rely on manually designed physical models and idealized assumptions, which struggle to meet practical demands in dynamic and complex scenarios. Recent advancements in deep learning have revolutionized SSL by leveraging its end-to-end feature adaptability, cross-scenario generalization capabilities, and data-driven modeling, significantly enhancing localization robustness and accuracy in challenging environments. This review systematically examines the progress of deep learning-based SSL across three critical domains: marine environments, indoor reverberant spaces, and unmanned aerial vehicle (UAV) monitoring. In marine scenarios, complex-valued convolutional networks combined with adversarial transfer learning mitigate environmental mismatch and multipath interference through phase information fusion and domain adaptation strategies. For indoor high-reverberation conditions, attention mechanisms and multimodal fusion architectures achieve precise localization under low signal-to-noise ratios by adaptively weighting critical acoustic features. In UAV surveillance, lightweight models integrated with spatiotemporal Transformers address dynamic modeling of non-stationary noise spectra and edge computing efficiency constraints. Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. These directions aim to propel SSL toward intelligent systems characterized by high precision, strong robustness, and low power consumption. This work provides both theoretical foundations and technical references for algorithm selection and practical implementation in complex real-world scenarios. Full article

Deep learning approaches for multi-source sound localization face significant challenges, particularly the need for extensive training datasets encompassing diverse spatial configurations to achieve robust generalization. This requirement leads to substantial computational demands, which are further exacerbated when localizing overlapping sources in complex acoustic environments with reverberation and noise. In this paper, a new methodology is proposed for simultaneous localization of two overlapping sound sources in the time–frequency domain in a closed, reverberant environment with a spatial resolution of ${10}^{°}$ using a small-sized microphone array. The proposed methodology is based on the integration of the sound source separation method with a single-source sound localization model. A hybrid model was proposed to separate the sound source signals received by each microphone in the array. The model was built using a bidirectional long short-term memory (BLSTM) network and trained on a dataset using the ideal binary mask (IBM) as the training target. The modeling results show that the proposed localization methodology is efficient in determining the directions for two overlapping sources simultaneously, with an average localization accuracy of 86.1% for the test dataset containing short-term signals of 500 ms duration with different signal-to-signal ratio values. Full article

In this paper, we discuss the results of hydroacoustic sounding in the frequency range of units of kHz, conducted during voyage No. 90 of the research vessel “Akademik Mstislav Keldysh”. The employment of a vertical antenna array and electronic phasing to the recorded data made it possible to determine both the reflection coefficient from the bottom at incidence close to normal, and the diffuse scattering coefficients at oblique angles for the surface and the bottom. Based on the processing of experimental data, and with the help of computer modeling, an analysis of the structure of hydroacoustic signals scattered by the bottom and free surface of water was carried out. An approach combining the Green’s function and the scattering function was used to model the reverberation signal. The models of formation of the Doppler spectrum of the scattered acoustic signal were refined, taking into account the influence of sound propagation conditions in the marine environment. The comparison of the results of experimental studies of bottom reverberation in the waters of the Barents and Kara Seas with numerical calculations of the ray structure of the acoustic field demonstrates good agreement. Full article

Blended Synchronous Learning helps teachers and students communicate without geographical restrictions. The effect of communication between the face-to-face end and the remote end was not only affected by the performance of the equipment but also by the acoustic conditions in the classroom. This paper measured the acoustic parameters in the hybrid classrooms and conducted subjective speech intelligibility tests. It was found that for the hybrid classroom with a decentralized sound reinforcement system, the background noise level was high because lots of equipment was needed for synchronous learning. The speech intelligibility scores of the remote end were lower than those at the face-to-face end. Acoustic parameters of reverberation time (RT) and excessive signal-to-noise ratio (SNR) showed a negative correlation with speech intelligibility scores in the remote end. It was recommended that the sound pressure level (SPL) of the sound reinforcement system should not be too high and that appropriate sound absorption treatment be performed. The size of the hybrid classroom should be controlled to prevent the sound that arrived 50 ms after the direct sound from arriving. When SNR was 33 dB(A) for hybrid classrooms, which had a good performance in the face-to-face end with the speech intelligibility scores, T₂₀ should be within 0.8 s to achieve the target value of 83% for SI scores at the remote end. Full article

This study explores the archaeoacoustics of rock imagery at Site 26LN211, the northernmost petroglyph site in the White River Narrows (WRN) Archaeological District, Nevada, USA. The research examines the relationship between rock writing placement and acoustic properties, considering their potential significance to indigenous groups such as the Southern Paiute and Western Shoshone. Fieldwork conducted in 2024 employed impulse response recordings to analyze sound behavior in various spatial configurations, including near and distant measurements. The results indicate that, unlike other WRN sites with strong echoes and reverberation, Site 26LN211 exhibits clear sound transmission with limited acoustic reflections. This suggests its suitability for oral storytelling, song recitatives, and ritual practices rather than sound-enhanced ceremonial performances. Additionally, the presence of vision quest structures above the site implies spiritual significance, although the results do not show a significant acoustic relationship between them and the petroglyph zone. Comparative studies with other indigenous sites reinforce the role of acoustics in shaping cultural landscapes. These findings contribute to broader discussions on the interplay between rock writing, sound, and indigenous traditions, emphasizing the need for preservation. Full article

Theaters in ancient Pompeii played a vital role in Roman entertainment, shaping the auditory experiences of spectators. This study examines the acoustic properties of the Amphitheater, the Grand Theater, and the Odeon using impulse response (IR) analysis to reconstruct their soundscapes. Next, the study considers the impact of typical musical instruments, vocal performances, and ambient sounds—such as gladiatorial combat—on these spaces’ acoustics. Findings reveal significant differences in reverberation times, sound clarity, and spatial characteristics, shaped by each theater’s design. These sites, preserved after the eruption of Mount Vesuvius, provide a unique opportunity to analyze how architecture influenced sound propagation. The Amphitheater, with its vast open structure, enhanced large-scale events, while the Grand Theater’s semi-enclosed design balanced musical and theatrical performances. The Odeon, the most intimate of the three, prioritized speech clarity. These insights highlight how Roman architects engineered performance spaces to accommodate diverse entertainment forms. By combining acoustic measurements with historical context, this research offers a deeper understanding of ancient Pompeii’s soundscapes and the auditory experiences of its inhabitants and offers insights for composition and soundscape creations that take inspiration from these prominent historical architectural and cultural icons whilst exploring its potential within contemporary immersive listening practices. Full article

In this study, the limits of using the impedance tube, or Kundt tube, are examined using the two-microphone method to obtain the normal acoustic absorption coefficient when analyzing the sound absorption properties of lightweight acoustic fabrics. Lightweight porous fabrics with 3D microstructures that have been previously evaluated in reverberation chambers are used. For these materials, a test methodology will be developed in the impedance tube that aims to replicate the conditions of the tests carried out in the reverberation chamber. The samples are tested maintaining the same separation from the final rigid wall and are placed in the impedance tube in two different ways: first, exposing the flat samples to the wave, and second, in pleated format. The results show that it is not possible to consider the results obtained with both methodologies in samples of light textiles with three-dimensional microstructures to be the same. The similarity is limited to low frequencies (100–315 Hz) but bias, excessive dispersion of the data, different global results and shape indicators obtained suggest that both methods are not identical. Full article

Machine learning (ML) robustness for voice disorder detection was evaluated using reverberation-augmented recordings. Common vocal health assessment voice features from steady vowel samples (135 pathological, 49 controls) were used to train/test six ML classifiers. Detection performance was evaluated under low-reverb and simulated medium (med = 0.48 s) and high-reverb times (high = 1.82 s). All models’ performance declined with longer reverberation. Support Vector Machine exhibited slight robustness but faced performance challenges. Random Forest and Gradient Boosting, though strong under low reverb, lacked generalizability in med/high reverb. Training/testing ML on augmented data is essential to enhance their reliability in real-world voice assessments. Full article