Adam Craig – Adam.Craig@gcu.ac.uk
Don Knox – D.Knox@gcu.ac.uk
David Moore – J.D.Moore@gcu.ac.uk

Glasgow Caledonian University
School of Engineering and Built Environment
70 Cowcaddens Road
Glasgow
United Kingdom
G4 0BA

Popular version of paper 5aNS6
Presented Friday morning, October 31st 2014
168th ASA Meeting, Indianapolis

The term ‘soundscape’ is widely used to describe the sonic landscape and can be considered the auditory equivalent of a visual landscape. Current soundscape research looks into the view of sound assessment in terms of perception and has been the subject of large scale projects such as the Positive Soundscapes Project (Davies et al. 2009) i.e. the emotional attributes associated with particular sounds. This research addresses the limitations of current noise assessment methods by taking into account the relationship between the acoustic environment and the emotional responses and behavioural characteristics of people living within it. Related research suggests that a variety of objective and subjective factors influence the effects of exposure to noise, including age, locale, cross-cultural differences (Guyot at el. 2005) and the time of year (Yang and Kang, 2005). A key aspect of this research area is the subjective effect of the soundscape on the listener. This paradigm emphasises the subjective perception of sound in an environment – and whether it is perceived as being positive or negative. This approach dovetails with advancing sound and music classification research which aims to categorise sounds in terms of their emotional impact on the listener.

Annoyance is one of the main factors which contribute to a negative view of environmental noise, and can lead to stress-related health conditions. Subjective perception of environmental sounds is dependent upon a variety of factors related to the sound, the geographical location and the listener. Noise maps used to communicate information to the public about environmental noise in a given geographic location are based on simple noise level measurements, and do not include any information regarding how perceptually annoying or otherwise the noise might be.

Selected locations for recording - image courtesy of Scottish Noise Mapping
Figure 1 Selected locations for recording – image courtesy of Scottish Noise Mapping

This study involved subjective assessment by a large panel of listeners (N=167) of a corpus of sixty pre-recorded urban soundscapes collected from a variety of locations around Glasgow City Centre (see figure 1). Binaural recordings were taken at three points during each 24 hour period in order to capture urban noise during day, evening and night. Perceived annoyance was measured using Likert and numerical scales and each soundscape measured in terms of arousal and positive/negative valence (see figure 2).

craig_figure2
Figure 2 Arousal/Valance Circumplex Model Presented in Listening Tests

Coding of each of the soundscapes would be essential process in order to test the effects of the location on the variables provided by the online survey namely annoyance score (verbal), annoyance score (numeric), quadrant score, arousal score, and valence score. The coding was based on the environment i.e. urban (U), semi-open (S), or open (O); the density of traffic i.e. high (H), mid (M), low (L); and the distance form the main noise source (road traffic) using two criteria >10m (10+) and <10m (10-). The coding resulted in eight different location types; UH10-, UH10+, UM10+, UL10-, SM10+, SL10-, SL10+, and OL10+.

To capture quantitative information about the actual audio recordings themselves, the MIRToolkit for MATLAB was used to extract acoustical features from the dataset. Several functions were identified that could be meaningful for measuring the soundscapes in terms of loudness, spectral shape, but also rhythm, which could be thought of in not so musical terms but as the rate and distribution of events within a soundscape.

As expected, correlations between extracted features and locations suggest where there are many transient events, higher energy levels, and where the type of events include harsh and dissonant sounds i.e. heavy traffic, resulted in higher annoyance scores and higher arousal scores but perceived more negatively than quiet areas. In those locations where there are fewer transient events, lower energy levels, and there are less harsh and possibly more positive sounds i.e. birdsong, resulted in lower annoyance scores and lower arousal scores as well as being perceived more positively than busy urban areas. The results shed light on the subjective annoyance of environmental sound in a range of locations and provide the reader with an insight as to what psychoacoustic features may contribute to these views of urban soundscapes.

References

Davies, W., Adams, M., Bruce, N., Cain, R., Jennings, P., Carlyle, A., … Plack, C. (2009, October 26). A positive soundscape evaluation system. Retrieved from http://usir.salford.ac.uk/2468/1/Davies_et_al_soundscape_evaluation_euronoise_2009.pdf

Guyot, F., Nathanail, C., Montignies, F., & Masson, B. (2005). Urban sound environment quality through a physical and perceptive classification of sound sources : a cross-cultural study Methodology.

Scottish Noise Mapping (2014). Scottish Noise Mapping: Map Search [Online] http://gisapps.aecomgis.com/scottishnoisemapping_p2/default.aspx#/Main. [Accessed 20th June 2014]

Yang, W., & Kang, J. (2005). Soundscape and Sound Preferences in Urban Squares: A Case Study in Sheffield. Journal of Urban Design, 10(1), 61–80. doi:10.1080/13574800500062395

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