Water fountains are potential tools for soundscape improvement, but little is known about their perceptual properties. To explore this, sounds were recorded from 32 fountains installed in urban parks. The sounds were recorded with a sound-field microphone and were reproduced using an ambisonic loudspeaker setup. Fifty-seven listeners assessed the sounds with regard to similarity and pleasantness. Multidimensional scaling of similarity data revealed distinct groups of soft variable and loud steady-state sounds. Acoustically, the soft variable sounds were characterized by low overall levels and high temporal variability, whereas the opposite pattern characterized the loud steady-state sounds. The perceived pleasantness of the sounds was negatively related to their overall level and positively related to their temporal variability, whereas spectral centroid was weakly correlated to pleasantness. However, the results of an additional experiment, using the same sounds set equal in overall level, found a negative relationship between pleasantness and spectral centroid, suggesting that spectral factors may influence pleasantness scores in experiments where overall level does not dominate pleasantness assessments. The equal-level experiment also showed that several loud steady-state sounds remained unpleasant, suggesting an inherently unpleasant sound character. From a soundscape design perspective, it may be advisable to avoid fountains generating such sounds.
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http://dx.doi.org/10.1121/1.4934956 | DOI Listing |
J Neurodev Disord
January 2025
Graduate Neuroscience Program, University of California, Riverside, CA, USA.
Background: Fragile X syndrome (FXS) is a leading known genetic cause of intellectual disability and autism spectrum disorders (ASD)-associated behaviors. A consistent and debilitating phenotype of FXS is auditory hypersensitivity that may lead to delayed language and high anxiety. Consistent with findings in FXS human studies, the mouse model of FXS, the Fmr1 knock out (KO) mouse, shows auditory hypersensitivity and temporal processing deficits.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Signal Theory and Communications, Universidad de Valladolid, 47002, Valladolid, Spain.
Sound-based uroflowmetry (SU) offers a non-invasive alternative to traditional uroflowmetry (UF) for evaluating lower urinary tract dysfunctions, enabling home-based testing and reducing the need for clinic visits. This study compares SU and UF in estimating urine flow rate and voided volume in 50 male volunteers (aged 18-60), with UF results from a Minze uroflowmeter as the reference standard. Audio signals recorded during voiding were segmented and machine learning algorithms (gradient boosting, random forest, and support vector machine) estimated flow parameters from three devices: Ultramic384k, Mi A1 smartphone, and Oppo smartwatch.
View Article and Find Full Text PDFJ Neurosci
January 2025
Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, 20742.
Hearing is an active process in which listeners must detect and identify sounds, segregate and discriminate stimulus features, and extract their behavioral relevance. Adaptive changes in sound detection can emerge rapidly, during sudden shifts in acoustic or environmental context, or more slowly as a result of practice. Although we know that context- and learning-dependent changes in the sensitivity of auditory cortical (ACX) neurons support many aspects of perceptual plasticity, the contribution of subcortical auditory regions to this process is less understood.
View Article and Find Full Text PDFEvol Anthropol
March 2025
Center for the Advanced Study of Human Paleobiology, George Washington University, Washington DC, USA.
Sci Rep
January 2025
Institute for the Future of Human Society, Kyoto University, Kyoto, Japan.
Objective digital measurement of gamblers visiting gambling venues is conducted using cashless cards and facial recognition systems, but these methods are confined within a single gambling venue. Hence, we propose an objective digital measurement method using a transformer, a state-of-the-art machine learning approach, to detect total gambling venue visitations for gamblers who visit multiple gambling venues using sounds in gamblers' environments. We sampled gambling and nongambling event datasets from websites to create a gambling play classifier.
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