Search Results (4)

Urban noise pollution significantly degrades people’s health and well-being and, furthermore, traditional noise reduction strategies often overlook individual perception differences. This study proposed to explore the role of eco-acoustic indices in capturing the interplay between biophony, geophony, and anthrophony, and their relationship with classical acoustic metrics and the perceived soundscapes within a University Campus (University of “Mila-no-Bicocca”, Italy). The study area is divided in to eight different sites in “Piazza della Scienza” square. Sound measurements and surveys conducted in June 2023 across four paved sites and adjacent courtyards involved 398 participants (51.7% female, 45.6% male, 2.7% other). The main noise sources included road traffic, technical installations, and human activity, where traffic noise was more prominent at street-level sites (Sites 1–4) and technical installations dominated underground courtyards (6–8). Human activity was most noticeable at Sites 4–8, especially at Site 5, which showed the highest activity levels. A circumplex model revealed that street-level sites were less pleasant and eventful than courtyards. Pairwise comparisons of noise variability showed significant differences among sites, with underground locations offering quieter environments. Eco-acoustic analysis identified two site groups: one linked to noisiness and spectral features, the other to intensity distribution metrics. Technical installations, people, and traffic noises showed distinct correlations with acoustic indices, influencing emotional responses like stimulation and liveliness. These findings emphasize the need to integrate subjective perceptions with objective noise metrics in soundscape descriptions. Full article

Ecoacoustics is arguably the best method for monitoring marine environments, but analyzing and interpreting acoustic data has traditionally demanded substantial human supervision and resources. These bottlenecks can be addressed by harnessing contemporary methods for automated audio signal analysis. This paper focuses on the problem of assessing dolphin whistles using state-of-the-art deep learning methods. Our system utilizes a fusion of various resnet50 networks integrated with data augmentation (DA) techniques applied not to the training data but to the test set. We also present training speeds and classification results using DA to the training set. Through extensive experiments conducted on a publicly available benchmark, our findings demonstrate that our ensemble yields significant performance enhancements across several commonly used metrics. For example, our approach obtained an accuracy of 0.949 compared to 0.923, the best reported in the literature. We also provide training and testing sets that other researchers can use for comparison purposes, as well as all the MATLAB/PyTorch source code used in this study. Full article

Visual observations of the marine biodiversity can be difficult in specific areas for different reasons, including weather conditions or a lack of observers. In such conditions, passive acoustics represents a potential alternative approach. The objective of this work is to demonstrate how information about marine biodiversity can be obtained via detailed analysis of the underwater acoustic environment. This paper presents the first analysis of the Saint-Pierre-and-Miquelon (SPM) archipelago underwater acoustic environment. In order to have a better knowledge about the marine biodiversity of SPM, acoustic recordings were sampled at different time periods to highlight seasonal variations over several years. To extract information from these acoustic recordings, standard soundscape and ecoacoustic analysis workflow was used to compute acoustic metrics such as power spectral density, third-octave levels, acoustic complexity index, and sound pressure levels. The SPM marine acoustic environment can be divided into three main sound source classes: biophony, anthrophony, and geophony. Several cetacean species were encountered in the audio recordings including sperm whales (which were detected by visual observations and strandings of 3 males in 2014), humpback, and blue whales. Full article

Ecoacoustics is a recent ecological discipline focusing on the ecological role of sounds. Sounds from the geophysical, biological, and anthropic environment represent important cues used by animals to navigate, communicate, and transform unknown environments in well-known habitats. Sounds are utilized to evaluate relevant ecological parameters adopted as proxies for biodiversity, environmental health, and human wellbeing assessment due to the availability of autonomous audio recorders and of quantitative metrics. Ecoacoustics is an important ecological tool to establish an innovative biosemiotic narrative to ensure a strategic connection between nature and humanity, to help in-situ field and remote-sensing surveys, and to develop long-term monitoring programs. Acoustic entropy, acoustic richness, acoustic dissimilarity index, acoustic complexity indices (ACIt_f and ACIf_t and their evenness), normalized difference soundscape index, ecoacoustic event detection and identification routine, and their fractal structure are some of the most popular indices successfully applied in ecoacoustics. Ecoacoustics offers great opportunities to investigate ecological complexity across a full range of operational scales (from individual species to landscapes), but requires an implementation of its foundations and of quantitative metrics to ameliorate its competency on physical, biological, and anthropic sonic contexts. Full article