43 research outputs found

    Assessing and modeling the role of the noticeability of sound events and attention in urban sound perception

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    The influence of vegetation and shape-related features in making parks more noise resistant

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    The aim of this paper is to assess the effect of vegetation-related parameters and shape-related features on noise levels in park areas. For the current research, eight case study parks of various sizes were identified in Antwerp and noise levels were measured inside and around them. The measurements were conducted during multiple days using portable custom-made sound recording devices. The analysis was performed by correlating the input with the output parameters. Input data include green space and shape metrics, while output parameters consist of various noise indices (L10, L50, L90, LAeq, LCeq-LAeq) averaged for the entire parks. In a more focused scale the same analysis was attempted referring to measurement points inside the parks.Correlations in this case were identified only between green space features and L90. The entire analysis denotes that green space features can be an important factor in noise reduction within the parks,independently of the effects from the surrounding environment

    The influence of vegetation and surrounding traffic noise parameters on the sound environment of urban parks

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    The main aim of this study was to investigate the effects of vegetation and traffic-noise parameters on the sound environment of urban parks. Eight parks of different sizes and varying proximity to the city's ring road were selected in Antwerp, Belgium. The sound environment was evaluated with a dual approach, using primarily simulated traffic data from the surrounding roads and then measurement noise data from mobile devices within the parks. Percentile weighted sound levels were calculated considering various indicators (LA(10), LA(50), LA(90), L-Aeq) with special emphasis on background noise (LA(90)) and peak values (LA(10)). Results showed that simulated noise levels were slightly overestimated compared to the actual ones. Within the parks very small differences were found no matter whether measurement points were examined individually or aggregated on grids. Overall, background noise (L-A90) presented more fluctuations than LAID. At the same time, the average noise levels both for L-A90 and L-A10 were higher in the surrounding environment of the parks compared to the inside - most probably because of traffic sound sources and the proximity to main roads. Additional analysis was also performed within the parks for the identification of "hot" and "cold" spots for L-A90 using GIS tools. Relationships between noise levels and morphological features of the surrounding environment were also identified. The final step of analysis dealt with the effects of tree or grass areas in noise indices. The effect of additional sources other than traffic is also explained as part of the limitations and the actual findings of this research

    Machine listening for park soundscape quality assessment

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    The increasing importance attributed to soundscape quality in urban design generates a need for a system for automatic quality assessment that could be used for example in monitoring. In this work, the possibility for using machine listening techniques for this purpose is explored. The outlined approach detects the presence of particular sounds in a human-inspired way, and therefore allows to draw conclusions about how soundscapes are perceived. The system proposed in this paper consists of a partly recurrent artificial neural network modified to incorporate human attention mechanisms. The network is trained on sounds recorded in typical urban parks in the city of Antwerp, and thus becomes an auditory object creation and classification system particularly tuned to this context. The system is used to analyze a continuous sound level recording in different parks, resulting in a prediction of sounds that will most likely be noticed by a park visitor. Finally, it is shown that these indicators for noticed sounds allow to construct more powerful models for soundscape quality as reported in a survey with park visitors than indicators that are more regularly used in soundscape research
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