Archives of Acoustics

This study investigates the degree of vocal variation between men and pre- and postmenopausal women. The sample comprised 108 volunteers aged 18 to 66, divided into control and validation groups. Each participant was subjected to voice recordings of five sustained vowels. Acoustic parameters were extracted using Praat software. The most significant parameters in intergroup correlation between the canonical discriminant function and acoustic variables were: fundamental frequency (F0), shimmer, harmonics-to-noise ratio (HNR), and intensity. Premenopausal female voices were labeled with 97% correctness and male voices with 95.5% correctness. Interestingly, 65.5% of postmenopausal women were accurately classified as female voices and on average they had lower vocal pitches compared to premenopausal women. The differences in male and female voices are probably due to the difference in the size of the larynx and the length of the vocal cords. Hormonal changes during menopause may affect, but not significantly, the morphology of the laryngeal structures which develop during childhood and adolescence.

ISO 12913 standards provide a unified framework for describing and assessing soundscapes, however, the lack of a Polish translation has so far limited their practical use. This paper presents the first application of a validated Polish version of the ISO/TS 12913-2 perceptual attributes, enabling full cross-language comparability of results. Whereas Polish research has traditionally focused on noise annoyance and broad judgements of acoustic comfort or discomfort, we outline the complete ISO-compliant assessment procedure, which combines: a soundwalk, questionnaires and audio-visual recording. The study was conducted at eight diverse urban locations in Poznań, Poland. Participants rated the soundscapes using eight attributes: przyjemne, tętniące życiem, bogate w wydarzenia, chaotyczne, dokuczliwe, monotonne, ubogie w wydarzenia, spokojne. Each rating set is mapped to a point in the 2D pleasantness-eventfulness space defined in ISO/TS 12913-3, facilitating visual comparison of locations and the identification of design needs. Results reveal pronounced perceptual differences between spatial typologies and demonstrate that the standardized approach provides richer, multidimensional information about the acoustic environment than conventional noise indicators. The proposed methodology establishes a reference framework for Polish soundscape studies and can support the creation of more people-friendly urban acoustic environments.

This study investigated the influence of building layout on the outdoor acoustic environment through field measurements conducted in four courtyards at the University of Batna 1. Acoustic parameters including sound pressure level (SPL) attenuation, reverberation time (RT), early decay time (EDT), clarity (D50), and the rapid speech transmission index (RaSTI) were evaluated. Results showed that square-shaped courtyards retained sound the longest (RT20 exceeding 2.3 s at 1000 Hz), U-shaped courtyards exhibited the most irregular reverberation patterns, and linear courtyards provided the most stable sound decay. The D50 and RaSTI values were highest in linear courtyards, indicating superior speech intelligibility, while square and U-shaped layouts demonstrated reduced intelligibility due to extended reverberation. The SPL attenuation was also more consistent in linear configurations compared to the variable patterns observed in enclosed geometries. These findings demonstrate that building form plays a decisive role in shaping outdoor acoustic conditions and highlight the importance of considering acoustic performance in early design decisions. The results are broadly applicable to the planning of courtyards, plazas, and semi-enclosed urban spaces. Future work should explore additional variables such as building height, fa¸cade materials, vegetation, and seasonal effects to develop comprehensive guidelines for acoustically optimized outdoor environments.

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.

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).