The purpose of this case study was to explore the relationship between land use and sound sources and how to characterize urban environments in this respect. To this end, binaural recordings and 360° videos were used in a listening experiment, where 20 university students assessed the dominance of sound sources coupled with the appropriateness of land use variables and variables of social and recreational activities. Principal Components Analysis showed that the activity-based environment can be explained by two main components related to the degree of manmade features and the density of people. These components are closely associated with sounds

Field measurements and numerical modelling were used to study the acoustic performance of a low screen in an urban road setting. The results show the usefulness of low screens as well as suggests improvements in screen design. For the measurements, an acoustic screen built up from concrete modules was temporarily installed beside a small park on the reservation between a two-lane road and a track for walking and cycling. A larger traffic system, of which the two-lane road is a part, determines the daytime equivalent noise level within the urban area. The screen height was about 1.4m as measured from the level of the road surface and the width of the screen top was 0.3 m. Measurements were carried out both at 20 m distance from the road (within the park) and at 5 m distance from the road (at the cycle track). Insertion loss in maximum level, using controlled light-vehicle pass-by at 50 km/h, was measured to 10 dB at 5 m distance and to 6 dB at 20 m distance, at 1.5 m height. Insertion loss in equivalent level was measured within the park to 4 dB at 1.5 m height. A listening experiment confirmed a perceived improvement from installing the screen. The measured results were also compared with predicted results using a boundary element method (BEM) and a noise mapping software, the latter showing good agreement, overestimating the equivalent level insertion loss by 1 dB in the park. The BEM comparison showed reasonable agreement in maximum level insertion loss considering that facade reflections were excluded, with an overestimation of 5 dB at the cycle track, and good agreement in the park, overestimating by up to 1 dB the equivalent and maximum level insertion losses. BEM predictions were used to also investigate other screen designs, showing a positive effect of an acoustically soft screen top, significant for a screen width of 0.2 m and increasing for wider screens.

This study aims at examining the effect of socio-cultural context, including language, on soundscape assessments in urban parks. In total, 95 persons took part in three laboratory experiments, conducted in France (30 participants), Korea (30 participants) and Sweden (35 participants). Twenty-eight audio-visual excerpts from recordings conducted in five urban parks were used as stimuli. The participants evaluated soundscape quality using attribute scales provided in their own native languages. Principal Components Analysis produced two principal components of perceived affective quality, Pleasantness and Eventfulness. There were high levels of similarity in attributes associated with the Pleasantness among the three countries, whereas some differences were observed in the attributes related to Eventfulness. Two hierarchical cluster analyses were conducted based on perceived dominance of sound sources, and component scores of perceived affective quality. There were no significant differences in clustering results based on perceived dominance of sound sources among the different nationalities. In contrast, discrepancies were found in the clustering results based on perceived affective quality. In particular, perceptual responses to human sounds, birdsong, and water sounds, which are closely related to Eventfulness, were significantly different across the three cultural backgrounds. These findings provide empirical evidence of socio-cultural differences in soundscape assessment.

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.

In investigating the quality of urban open space, it is important to investigate how the visual and auditory components contribute to the total quality. The majority of studies investigating audio-visual interaction in environmental perception have concerned how visual stimuli affect auditory perception, such as how vegetation affects the perception of the sound of road traffic from a motorway (e.g., Anderson, Mulligan, Goodman, Regen, 1983). In general, these studies indicate that how people perceive sound depends on the visual context. That is, some sounds are more appropriate in one context than in another, which seems to depend on the participants’ expectations. For example, a city center is expected to sound like a city center, and not like a forest, and vice versa. Typically, a mismatch resulted in discomfort.

A handful of laboratory studies investigated how perception of auditory and visual aspects related to the perception of the composite of audio-visual information (e.g., Gifford & Ng, 1982; Kuwano, Namba, Komatsu, Kato, & Hayashi, 2001; Morinaga, Aono, Kuwano, & Kato, 2003). Chiefly, these studies showed that visual aspects of environments were more important than auditory aspects. However, how important the visual aspects were, was highly variable across different environments. This indicates that auditory information might dominate over visual information at some point (see also Gan, Luo, Breitung, Kang, & Zhang, 2014; Preis, Koci ski, Hafke-Dys, & Wrzosek, 2015).

The present paper concerns a case study conducted in collaboration with the City of Stockholm, Sweden, in the summer of 2016. The purpose was to characterize and to investigate the potential for improving the quality of the environment in a centrally located park area in the city. Walks were conducted in situ together with 61 residents. In the walks the participants assessed five preselected sites in and near the park area, with regards to their perceived total, auditory and visual qualities.

This study investigated the effects of a mock-up version of a low-height sound absorbent street furniture and a fountain on the local soundscape in a pocket park in Stockholm. Binaural recordings were conducted at two distances from the main road (on the sidewalk and in the park). The recordings were conducted with or without the mock-up, and with the local fountain either turned on or off. Thirty-two students (16 women, Mage = 26.6 yrs., SDage = 5.7) participated in a listening experiment, and assessed eight experimental sounds, in context of 12 fill sounds, on how pleasant or eventful they were. ANOVA showed that the mock-up had a stronger effect on pleasantness on the sidewalk than in the park, and the fountain contributed to pleasantness only in the absence of the mock-up. Moreover, the fountain reduced the eventfulness in the park but not on the sidewalk. The results are in line with previous case studies. Taken together, they suggest that it is better to build low-height sound absorbent street furniture  han fountains, to improve the urban soundscape.

The purpose of this study was to investigate whether or not a computer may predict the outcome of soundscape assessments, based on acoustic data only. It may be argued that this is impossible, because a computer lack life experience. Moreover, if the computer was able to make an accurate prediction, we also wanted to know what information it needed to make this prediction. We recruited 33 students (18 female; Mage = 25.4 yrs., SDage = 3.6) out of which 30 assessed how pleasant and eventful 102 unique soundscape excerpts (30 s) from Stockholm were. Based on the Bag of Frames approach, a Support Vector Regression learning algorithm was used to identify relationships between various acoustic features of the acoustics signals and perceived affective quality. We found that the Mel-Frequency Cepstral Coefficients provided strong predictions for both Pleasantness (R2 = 0.74) and Eventfulness (R2 = 0.83). This model performed better than the average individual in the experiment in terms of internal consistency of individual assessments. Taken together, the results show that a computer can predict the outcome of soundscape assessments, which is promising for future soundscape mapping.

Soundscape exists through human perception of the acoustic environment. This paper investigates how soundscape currently is assessed and measured. It reviews and analyzes the main soundscape descriptors in the soundscape literature, and provides a conceptual framework for developing predictive models in soundscape studies. A predictive soundscape model provides a means of predicting the value of a soundscape descriptor, and the blueprint for how to design soundscape. It is the key for implementing the soundscape approach in urban planning and design. The challenge is to select the appropriate soundscape descriptor and to identify its predictors. The majority of available soundscape descriptors are converging towards a 2-dimensional soundscape model of perceived affective quality (e.g., Pleasantness–Eventfulness, or Calmness–Vibrancy). A third potential dimension is the appropriateness of a soundscape to a place. This dimensions provides complementary information beyond the perceived affective quality. However, it depends largely on context, and because a soundscape may be appropriate to a place although it is poor, this descriptor must probably not be used on its own. With regards to predictors, or soundscape indicators, perceived properties of the acoustic environment (e.g., perceived sound sources) are winning over established acoustic and psychoacoustic metrics. To move this area forward it is necessary that the international soundscape community comes together and agrees on relevant soundscape descriptors. This includes to agree on numerical scales and assessment procedures, as well as to standardize them.

Three conservation methods were executed on bonnets in plain monochrome silk, to investigate which method is perceived as the most visually aesthetic; 11 bonnets were produced, 10 given identical damages, and 9 were conserved, 3 with each method. The damage was secured onto a support fabric with laid couching, a long stitch fastened with short perpendicular stitches, or brick couching, short stitches placed like brick-work, or covered with crepeline (a semi-transparent silk). The participants were 30 Swedish textile conservators (29 women; ages 29-78 years, M = 51.9, SD = 12.9), and 30 museum visitors (20 women; ages 15-74 years, M = 41.1, SD = 18.3). The participants' task was to rate the bonnets on a 100-point continuous preference scale, based on how visually attractive they found each bonnet. Preferences were compared between the two groups of participants and the conservation methods. The bonnets with crepeline were the most preferred, and those with laid couching were the least preferred, among both groups of participants.

Aesthetic quality is central to textile conservators when evaluating a conservation method. However, the literature on textile conservation chiefly focuses on physical properties, and little is known about what factors determine aesthetic quality according to textile conservators. The latter was explored through two experiments. Experiment 1 explored the underlying attributes of aesthetic quality of textile conservation interventions. Experiment 2 explored the relationships between these attributes and how well they predicted aesthetic quality. Rank-order correlation analyses revealed two latent factors called Coherence and Completeness. Ordinal regression analysis revealed that Coherence was the most important predictor of aesthetic quality. This means that a successful conservation intervention is visually well-integrated with the textile item in terms of the material and method.