A computational model of auditory attention for use in soundscape research

Acoustic information masking effects of natural sounds on traffic noise based on psychological health in open urban spaces

The use of existing resources, such as natural sounds, to promote the mental health of citizens is an area of research that is receiving increasing attention. This research contributes to existing knowledge by combining a field psychological walk method and an experimental acoustic control method to compare the acoustic information masking effects of water and birdsong sounds on traffic noise based on the psychological health responses of 30 participants to such effects. The influence of traffic noise and contextual sounds on the psychological health of participants identified the potential of natural sounds in the acoustic information masking of traffic noise. Furthermore, it was found that 65.0 dBA water sounds did not mask 60.0 dBA traffic noises. However, 45.0 dBA birdsong sounds did mask it, but this effect was not significant. Additionally, contextual factors with and without crowd activity sounds were not significant in influencing psychological health through birdsong. This study contributes to public health cost savings. It may also guide the development of new ideas and methods for configuring open urban spaces according to public health needs.

Low-Cost Sensors for Urban Noise Monitoring Networks-A Literature Review

Noise pollution reduction in the environment is a major challenge from a societal and health point of view. To implement strategies to improve sound environments, experts need information on existing noise. The first source of information is based on the elaboration of noise maps using software, but with limitations on the realism of the maps obtained, due to numerous calculation assumptions. The second is based on the use of measured data, in particular through professional measurement observatories, but in limited numbers for practical and financial reasons. More recently, numerous technical developments, such as the miniaturization of electronic components, the accessibility of low-cost computing processors and the improved performance of electric batteries, have opened up new prospects for the deployment of low-cost sensor networks for the assessment of sound environments. Over the past fifteen years, the literature has presented numerous experiments in this field, ranging from proof of concept to operational implementation. The purpose of this article is firstly to review the literature, and secondly, to identify the expected technical characteristics of the sensors to address the problem of noise pollution assessment. Lastly, the article will also put forward the challenges that are needed to respond to a massive deployment of low-cost noise sensors.

Effects of adding natural sounds to urban noises on the perceived loudness of noise and soundscape quality

Introducing pleasant natural sounds to mask urban noises is an important soundscape design strategy to improve acoustic comfort. This study investigates the effects of signal-to-noise ratio (SNR) between natural sounds (signal) and the target noises (noise) and their temporal characteristics on the perceived loudness of noise (PLN) and overall soundscape quality (OSQ) through a laboratory experiment. Two types of urban noise sources (hydraulic breaker and traffic noises) were set to A-weighted equivalent sound pressure levels (SPL) of 55, 65, and 75 dB and then augmented with two types of natural sounds (birdsong and stream), across a range of SNRs. Each acoustic stimulus was a combination of noise and natural sound at SNRs from -6 to 6 dB. Averaged across all cases, the subjective assessment of PLN showed that augmenting urban noise separately with the two natural sounds reduced the PLN by 17.9%, with no significant differences found between the birdsong and stream sounds. Adding natural sounds increased the OSQ by on average 18.3% across the cases, but their effects gradually decreased as the noise level increased. The OSQ of the birdsong and stream sounds were similar for traffic noise, whereas the stream sound was rated higher than the birdsong for the breaker noise. The results suggest that increasing the dissimilarity in temporal structure between the target noise and natural sounds could enhance the soundscape quality. Appropriate SNRs were explored considering both PLN and OSQ. The results showed that the SNR of -6 dB was desirable when the A-weighted SPL of the noise rose to 75 dB.

What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective

Selective attention plays an essential role in information acquisition and utilization from the environment. In the past 50 years, research on selective attention has been a central topic in cognitive science. Compared with unimodal studies, crossmodal studies are more complex but necessary to solve real-world challenges in both human experiments and computational modeling. Although an increasing number of findings on crossmodal selective attention have shed light on humans' behavioral patterns and neural underpinnings, a much better understanding is still necessary to yield the same benefit for intelligent computational agents. This article reviews studies of selective attention in unimodal visual and auditory and crossmodal audiovisual setups from the multidisciplinary perspectives of psychology and cognitive neuroscience, and evaluates different ways to simulate analogous mechanisms in computational models and robotics. We discuss the gaps between these fields in this interdisciplinary review and provide insights about how to use psychological findings and theories in artificial intelligence from different perspectives.

Designing Supportive Soundscapes for Nursing Home Residents with Dementia

Sound and its resulting soundscape is a major appraisal component of the living environment. Where environmental sounds (e.g., outdoor traffic sounds) are often perceived as negative, a soundscape (e.g., containing natural sounds) can also have a positive effect on health and well-being. This supportive effect of a soundscape is getting increasing attention for use in practice. This paper addresses the design of a supportive sonic environment for persons with dementia in nursing homes. Starting from a review of key mechanisms related to sonic perception, cognitive deficits and related behavior, a framework is derived for the composition of a sonic environment for persons with dementia. The proposed framework is centered around using acoustic stimuli for influencing mood, stimulating the feeling of safety and triggering a response in a person. These stimuli are intended to be deployed as added sounds in a nursing home to improve the well-being and behavior of the residents.

Improving the soundscape quality of urban areas exposed to aircraft noise by adding moving water and vegetation

Research shows that the sight of trees and the sound of moving water improve the soundscape quality of outdoor spaces exposed to road traffic noise. Effects are attributed to non-energetic masking, visual attentional distortion, and congruence between sight and hearing. However, there is no literature on such effects for aircraft noise. Aircraft noise varies from other traffic sources, i.e., in terms temporal variability, duration, and spectral composition, complicating the application of findings without further research. In a virtual reality experiment reported in this article, participants were asked to rate scenarios with different sound levels of flyovers, urban typologies, vegetation, and/ or water features. The results showed a significant improvement of the soundscape quality when (1) vegetation and (2) moving water were present, and especially when (3) vegetation and moving water were presented simultaneously, especially for residential areas in terms of the relative change. Moving water also reduced the saliency of aircraft flyovers significantly, changing the constellation of fore- and background sounds. Moving water raised the perceived audibility of the most dominant sound source too, which could be attributed to non-energetic masking effects. The findings of this study indicate that soundscape strategies can complement noise abatement in areas prone to aircraft noise.

Presenting and processing information in background noise: A combined speaker-listener perspective

Transferring information orally in background noise is challenging, for both speaker and listener. Successful transfer depends on complex interaction between characteristics related to listener, speaker, task, background noise, and context. To fully assess the underlying real-life mechanisms, experimental design has to mimic this complex reality. In the current study, the effects of different types of background noise have been studied in an ecologically valid test design. Documentary-style information had to be presented by the speaker and simultaneously acquired by the listener in four conditions: quiet, unintelligible multitalker babble, fluctuating city street noise, and little varying highway noise. For both speaker and listener, the primary task was to focus on the content that had to be transferred. In addition, for the speakers, the occurrence of hesitation phenomena was assessed. The listener had to perform an additional secondary task to address listening effort. For the listener the condition with the most eventful background noise, i.e., fluctuating city street noise, appeared to be the most difficult with markedly longer duration of the secondary task. In the same fluctuating background noise, speech appeared to be less disfluent, suggesting a higher level of concentration from the speaker's side.

Dimensions Underlying the Perceived Similarity of Acoustic Environments

Scientific research on how people perceive or experience and/or understand the acoustic environment as a whole (i.e., soundscape) is still in development. In order to predict how people would perceive an acoustic environment, it is central to identify its underlying acoustic properties. This was the purpose of the present study. Three successive experiments were conducted. With the aid of 30 university students, the first experiment mapped the underlying dimensions of perceived similarity among 50 acoustic environments, using a visual sorting task of their spectrograms. Three dimensions were identified: (1) Distinguishable–Indistinguishable sound sources, (2) Background–Foreground sounds, and (3) Intrusive–Smooth sound sources. The second experiment was aimed to validate the results from Experiment 1 by a listening experiment. However, a majority of the 10 expert listeners involved in Experiment 2 used a qualitatively different approach than the 30 university students in Experiment 1. A third experiment was conducted in which 10 more expert listeners performed the same task as per Experiment 2, with spliced audio signals. Nevertheless, Experiment 3 provided a statistically significantly worse result than Experiment 2. These results suggest that information about the meaning of the recorded sounds could be retrieved in the spectrograms, and that the meaning of the sounds may be captured with the aid of holistic features of the acoustic environment, but such features are still unexplored and further in-depth research is needed in this field.

Computational Models of Auditory Scene Analysis: A Review

Auditory scene analysis (ASA) refers to the process (es) of parsing the complex acoustic input into auditory perceptual objects representing either physical sources or temporal sound patterns, such as melodies, which contributed to the sound waves reaching the ears. A number of new computational models accounting for some of the perceptual phenomena of ASA have been published recently. Here we provide a theoretically motivated review of these computational models, aiming to relate their guiding principles to the central issues of the theoretical framework of ASA. Specifically, we ask how they achieve the grouping and separation of sound elements and whether they implement some form of competition between alternative interpretations of the sound input. We consider the extent to which they include predictive processes, as important current theories suggest that perception is inherently predictive, and also how they have been evaluated. We conclude that current computational models of ASA are fragmentary in the sense that rather than providing general competing interpretations of ASA, they focus on assessing the utility of specific processes (or algorithms) for finding the causes of the complex acoustic signal. This leaves open the possibility for integrating complementary aspects of the models into a more comprehensive theory of ASA.

Audio-visual interactions in environment assessment

The aim of the study was to examine how visual and audio information influences audio-visual environment assessment. Original audio-visual recordings were made at seven different places in the city of Poznań. Participants of the psychophysical experiments were asked to rate, on a numerical standardized scale, the degree of comfort they would feel if they were in such an environment. The assessments of audio-visual comfort were carried out in a laboratory in four different conditions: (a) audio samples only, (b) original audio-visual samples, (c) video samples only, and (d) mixed audio-visual samples. The general results of this experiment showed a significant difference between the investigated conditions, but not for all the investigated samples. There was a significant improvement in comfort assessment when visual information was added (in only three out of 7 cases), when conditions (a) and (b) were compared. On the other hand, the results show that the comfort assessment of audio-visual samples could be changed by manipulating the audio rather than the video part of the audio-visual sample. Finally, it seems, that people could differentiate audio-visual representations of a given place in the environment based rather of on the sound sources' compositions than on the sound level. Object identification is responsible for both landscape and soundscape grouping.

Describing and classifying urban sound environments with a relevant set of physical indicators

Categorization is a powerful method for describing urban sound environments. However, it has only been applied, until now, to discrete noise data collection, whereas sound environments vary continuously both in space and time. Therefore, a procedure is developed in this paper for describing the variations of urban sound environments. The procedure consists of mobile measurements, followed by a statistical clustering analysis that selects relevant noise indicators and classifies sound environments. Analysis are based on a 3 days + 1 night survey where geo-referenced noise measurements were collected over 19 1-h soundwalk periods in a district of Marseille, France. The clustering analysis showed that a limited subset of indicators is sufficient to discriminate sound environments. The three indicators that emerged from the clustering, namely, the Leq, A, the standard deviation σL eq, A, and the sound gravity spectrum SGC[50 Hz-10 kHz], are consistent with previous studies on sound environment classification. Moreover, the procedure proposed enables the description of the sound environment, which is classified into homogenous sound environment classes by means of the selected indicators. Thus, the procedure can be adapted to any urban environment, and can, for instance, favorably enhance perceptive studies by delimiting precisely the spatial extent of each typical sound environment.