Analysing the effectiveness of approaches to auralisation for applications inenvironmental acoustics
Alex SOUTHERN(1) , Frank STEVENS(2) , Damian MURPHY(2)(1) AECOM Ltd., United Kingdom, alex.southern@aecom.com(2) AudioLab, University of York, Heslington, frank.stevens@york.ac.uk / damian.murphy@york.ac.uk

Abstract
Auralisation is becoming more commonplace as a means of communicating and disseminating plans for changes
in our environmental landscape due to major infrastructure projects such as road, rail and airport developments,
where noise can be a signiﬁcant issue. This paper presents an approach to this challenge in the context ofa major public consultation for a UK road project as well as commenting on different means for facilitatingpresentation of, and engagement with, both audio and visual material. Although such methods are generally
used for information only, every effort is made to ensure that the ﬁnal result is both plausible and comparable
to existing on-site conditions, and calibrated accordingly, with a view to supporting other more standardised
methods and metrics. However, it is also possible to develop more quantitative measures as to how effective andsuccessful such auralisations are in terms of conveying a representation of a given scene, and any planned forinterventions. In this work the Self Assessment Manikin and soundscape classiﬁcation descriptors are used in aseries of listening tests to better understand the approach that has been adopted for these types of projects.
Keywords: Sound, Insulation, Transmission

1

INTRODUCTION

This paper presents the results of a listening study that uses the Self Assessment Manikin and soundscapeclassiﬁcation descriptors, as presented previously in (14)(15), for road trafﬁc auralisations (16) as typically presented at public consultations as part of the UK planning consent process. The motivation for the study is tounderstand if these methods for rating and categorising auralisations, or sound demonstrations, using simple andquick to administer surveys might provide a way to enhance the planning and decision making processes when
considering the potential noise impacts of a proposed development. Note that the use of sound demonstration ispreferred as a less technical and more accessible term when dealing with and presenting auralisations to nontechnical stakeholders and user groups. We also analyse the results using the Perceived Noise Impact Rating(RPNI ) (12) to better understand the general applicability of this metric for quantifying attitudes towards noise
impact.
The remainder of the paper is organised as follows: ﬁrst we provide some background to the consultation process and the adoption of auralisations for stakeholder engagement; Section 3 presents the method and technique
for the survey and is followed by the results and conclusions.

2

BACKGROUND

Nationally Signiﬁcant Infrastructure Projects (NSIPs) are developments considered by the UK Government to
be of signiﬁcant national importance such that the developer must apply to the Planning Inspectorate for aDevelopment Consent Order (DCO) to receive permission to undertake the work (3), rather than the more usualapplication for local planning permission. The process of applying for a DCO is set out in the UK Planning Act
2008 and has 6 stages: Pre-application; Acceptance; Pre-examination; Examination; Decision and Post-Decision.
The ﬁrst stage, Pre-application, is relevant to this work as there is a statutory requirement for the developer
to consult the public, and other relevant concerned bodies, and provide an opportunity for them to comment1683

and potentially inﬂuence the developing proposals. Prior to this statutory consultation it is not uncommon
for developers to undertake an additional non-statutory consultation where design options are presented andcomments from the public and other bodies are invited.
The government provides relevant guidance on consultation principles (1)(2) and included in this advice are suggestions to, "avoid lengthy documents", and provide, "enough information to ensure those consulted understandthe issues and can give informed responses". The guidance also suggests that consideration should be given to
tailor the consultation to the needs and preferences of different groups or demographics, such as older people
or younger people which might not respond to traditional consultation methods.
In relation to communicating noise impacts, the traditional approach is to present noise level predictions for any
proposed changes in the form of sound-level/noise contours that present the relative change from a baseline.
This usually requires an acoustic specialist to help interpret the resulting contour maps and so avoid misinterpretation of what changes in decibel quantities might mean. While such contour maps are well established
as a means of conveying the results of noise level predictions, they do not help many stakeholders understandwhat the real-world impact might be in terms of changes in overall or frequency dependent sound level, and byextension what the resulting qualitative sound character might be. Furthermore, this limitation also makes the
positive/negative impacts of any scheme, design or planned mitigation strategy equally difﬁcult to communicate
effectively.
Such consultations are seen as the best opportunity for local communities, local authorities and other stakeholders to inﬂuence proposed designs and so understand any potential impacts, positive and/or negative. Hence, inrecent years, there has been a growing interest and demand for the use of auralisations - or sound demonstrations - at stakeholder engagement events on NSIPs to more effectively present, and enable engagement with,changes in noise levels, and by extension, the associated soundscape. Sound demonstrations presenting multiple acoustic contexts arising from various scheme options can therefore help to highlight the potential impactof the proposed scheme, particularly in relation to road, railway or airport developments, where changes innoise levels resulting from the scheme’s completion are potentially signiﬁcant and of wider public concern. By
making these comparisons directly, stakeholders are able to arrive at a more informed opinion about how thedevelopment might impact on them and their community.
However, what is missing from any such consultation, given that the sound demonstrations are used to inform
rather than to formally test, is any robust measure of the perceived impact of the resulting soundscape as
presented to a listener. The next section presents the methods that will be used to gather and assess such
perceptual data based on established methods from environmental soundscape studies.

3

METHOD

This section introduces the key methods used in the listening tests that follow, the metrics that will be derived
and analysed, a description of the the auralisations used in the study, and the approach to administering thelistening test survey itself.
3.1 The Self Assessment Manikin
The Self Assessment Manikin (SAM) is a method for measuring emotional responses to various stimuli developed by Bradley and Lang in 1994 (5). It was developed from factor analysis of a set of Semantic Differential(SD) pairs rating both aural (6) and visual stimuli (4) (using, respectively, the International Affective Digital
Sounds database, or IADS, and the International Affective Picture System, or IAPS). The three factors developed for rating emotional response to a given stimuli are:• Valence: How positive or negative the emotion is, ranging from unpleasant feelings to pleasant feelingsof happiness.
• Arousal: How excited or apathetic the emotion is, ranging from sleepiness or boredom to frantic excite-

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Figure 1. The Self-Assessment Manikin (SAM) as used in this study, after (5) previously used in (13).
ment.
• Dominance: The extent to which the emotion makes the subject feel they are in control of the situation,
ranging from not at all in control to totally in control.
These results were used by Bradley and Lang to create the SAM itself as a set of pictorial representations of
the three identiﬁed factors. The version of the SAM used in this experiment (as shown in Fig. 1) contains only
the Valence and Arousal dimensions following results from previous studies showing these two factors of the
SAM to be most useful in the context of environmental soundscape assessment (13).
3.2 Soundscape Classiﬁcation Descriptors
A soundscape is usually considered as the aural equivalent of a landscape (10), but more recently the ISO
12913-1:2014, Acoustics - Soundscape - Part 1: Deﬁnition and conceptual framework (7) has provided a more
precise deﬁnition, where soundscape is deﬁned as the perception or understanding of an acoustic environment
which is made up of sound sources. Typically, sound sources can be split into three categories - natural,
human, and mechanical - and previous work has shown how the prevalence of sounds belonging to these categories might affect the subjective rating of a soundscape in terms of emotional experience, as well as how asoundscape is perceived as belonging to each of these three categories when used more generally as soundscapeclassiﬁcation descriptors (14). The work showed that soundscapes rated as more mechanical in nature tend to
exhibit lower valence and higher arousal in the SAM results, and that highly natural soundscapes will exhibit
high valence and low arousal. We adopt these descriptors again in the survey for this work in order to gain
further understanding of how they might provide a more robust and quantitative insight to the collective opinionof a surveyed population subjected to a series of prepared sound demonstrations.
3.3 Survey Approach
The survey was administered as an online set of 20 questions which required the subject to use over ear
headphones set at a constant volume and undertaken in a relatively quiet space. The majority of the participants
were audio or acoustics professionals from various parts of the world, including New Zealand, Australia, USA
and Canada, but predominantly the UK. Each question required a 10s auralisation to be rated using the Valenceand Arousal dimensions of the SAM (using a discrete selection on the 5-point scale of the SAM) and using
the three soundscape classiﬁcation descriptors (also using a discrete selection on a 5-point scale ranging from
’Not At All’ through to ’Very Much’). The 10s audio clips represented ﬁve locations relating to a typical road
trafﬁc scheme in the UK Without and With the proposed scheme in place - that is, the soundscape as currently
experienced, and the soundscape as potentially experienced with any proposed changes made. The participants
were not aware of these locations, nor whether the examples were presented with or without scheme. The clips
were presented in a random order for each participant. The results are presented in Section 4 and include theperceived noise impact rating which is explained below in section 3.4. The audio clips consist of a mix ofrural countryside sounds with distant road trafﬁc, busy A-roads (dual and single carriageway), and road junction
approaches consisting of vehicles moving at different speeds and accelerating/decelerating. Visual stimuli did
not accompany the audio clips to avoid biasing test subjects towards preference with or without scheme, and to1685

Figure 2. In (a) an example of a the circumplex model of affect deﬁned by the valence and arousal dimensionsof the SAM. A 2D graphical representation of emotion. In (b) a visual representation showing how RPNI maps
onto the the Circumplex Model of Affect.)avoid any bias based on recognising the locations being presented.
3.4 The Rating of Perceived Noise Impact
Valence and arousal can be used to represent emotional state on the Circumplex Model of Affect, as shown in
Figure 2(a) (9). Derived from this we also used the Rating of Perceived Noise Impact, RPNI , in this study as
ﬁrst introduced in (12):(1)
RPNI = 1 − 0.5(1 − A +V )where parameters A and V are the Arousal and Valance scores from the SAM. RPNI can therefore be determined
for an individual or across a population, or subset or scenarios, providing the convenience of a single ﬁgure
objective parameter, but with a relationship to the underlying subjective responses for a presented soundscape.
RPNI has been shown to be an appropriate measure of the subjective experience of a soundscape, and potentiallyable to identify differing emotional states not shown by arousal and valence results individually (13). Figure2(b) presents a visual representation of how RPNI maps onto the Circumplex Model of Affect from which it has
been derived.

4

RESULTSIn the following the results are presented from 28 test participants for the Soundscape Categorisation, SAM and
RPNI for responses to all 20 questions for the 5 locations With (W) and Without (WO) the scheme in place inFigure 3, Figure 4 and Figure 5 respectively. For each rating scale the mean value is plotted with bars showing
the standard error.
At Locations 1, 2 and 5 it can be observed that with the scheme in place the participants have rated thesoundscape in a positive way - higher valence, lower arousal, lower RPNI . This quantiﬁcation supports theinformal comments and opinions expressed by some of the participants after listening to the clips. Similarly,
for location 3 there seems to be a slight beneﬁt from the scheme, for example at this location the existingroad is barely audible and becomes even less audible with the scheme in place. This situation is captured andconﬁrmed by the survey results, the arousal is slightly lower and the valence is slightly higher with the scheme
in place and this is also supported by the RPNI which is lower with the scheme in place. It is worth recalling

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Categorisation Results

2
1.5

NaturalHuman
Mechanical1

Rating

0.5
0
-0.5
-1
-1.5
-2

L1W L1WO L2W L2WO L3W L3WO L4W L4WO L5W L5WO

Scene

Figure 3. Results of the categorisation scoring for all 5 locations with (W) and without (WO) the scheme inplace. The mean value is plotted with bars showing the standard error.
that the W and WO scheme scenarios are presented randomly and cannot be directly compared AB style by theparticipant. This is an example of the robustness of the survey method for capturing the opinion towards more
subtle changes in the perceived soundscape.
The results for location 4 are mixed/negligible and again this corresponds with the informal comments of theparticipants. At location 4 the road trafﬁc sound level does not differ between with and without scheme, thisis because the busy local road heard is not affected by the scheme being in place and as a result masks any
increase in road trafﬁc resulting from the scheme. This means there is no change at this location, and it is
not a pleasant place to be, both of which are apparent when looking at the categorisation results, which are
the same in both with and without scheme across all of the results in Figure 3, Figure 4 and Figure 5 (a),Further to this L4 and L5W scored very similarly for valence and RPNI , despite one being distant highspeedroad trafﬁc and the other being close proximity engine and tyre noise including acceleration and deceleration
vehicle movements. If we put these in to the context of L5WO which was the soundscape that was rated as
most mechanical and received the lowest valence scores, it suggests that while L4 and L5W are not idyllic the
results could well be indicating that RPNI in the region of 0.5 and 0.6 indicates an acoustic environment that istolerable.
In addition, it can be observed that for this dataset that the mechanical and valence scores are inversely related.
This suggests that the presence of mechanical sounds when being used to quantify vehicles and road noise
might well be used to estimate the valence scores, and as such reduce the number of ratings that consultees
need to do.
Overall, looking at the RPNI scores, and calculating the differences between them With and Without scheme is
one way to simply indicate objectively the mood of the surveyed population, see Figure 5 (c). This quantiﬁes
the most beneﬁcial and contentious parts of a scheme and where people are less concerned about noise.
The test results were also tested for normality using a Shapiro-Wilk’s test (11). This testing indicated that noneof the results were normally distributed. As such, a Mann-Whitney U-test (8) has been used to evaluate thesigniﬁcance of the effect of the presence of each scheme at each of the ﬁve locations.
Figure 5 (b) shows the Mann-Whitney U-test results for the ﬁve locations, indicating where there is a signiﬁcantdifference between the results for each rating scale (i.e. valence, arousal, the three soundscape categories, and
RPNI ) for each of the ﬁve locations, comparing the location with and without the scheme present in each case.

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2

SAM Results
Valence
Arousal1.5
1Rating

0.5
0
-0.5
-1
-1.5
-2

L1W L1WO L2W L2WO L3W L3WO L4W L4WO L5W L5WO

Scene

Figure 4. Results of the SAM scoring of Valence and Arousal for all 5 locations with (W) and without (WO)
the scheme in place. The mean value is plotted with bars showing the standard error.
It is clear from these results L3 and L4 which as previously described have very little or no change, respectively
have been quantiﬁed as such by the participants of the survey by looking at the Mann-Whitney U-test results.

5

CONCLUSIONSIn this paper we have presented results of a soundscape listening survey undertaken with the goal of quantifying the collective opinion of the soundscape survey participants. Currently the feedback, if any, from sounddemonstrations delivered at public consultation does not tend to capture or quantify the opinions of the people
listening to them. It could be helpful to the planning process if general mood and attitudes of the population
could be quantiﬁed in some objective way and this work has explored this possibility.
The results have indicated that a combination of the soundscape categorisation rating and the valence and arousal
dimensions of the self assessment manikin presented in the form of RPNI could provide a means of quantifying
subjective opinions about a scheme. This approach has potential value to the planning application process
to help developers quantify where public opinion about noise is being driven by factors/attitudes other thannoise, and to communicate in the planning application the locations where changes in road trafﬁc noise levelare subjectively negligible, adverse or beneﬁcial. The relative magnitude of the planned changes can also be
indicated in the form of differences in the perceived noise impact rating between with and without scheme inplace.
The results also support the ﬁndings from previous work in (14) that the soundscapes rated as more mechanicalin nature tend to exhibit lower valence and higher arousal in the SAM results, and that highly natural soundscapes will exhibit high valence and low arousal. It was observed that for the test soundscapes used in thisstudy, which consisted of mainly natural and/or or road related noise, that the mechanical and valence scores
might be inversely related and as such could mean one of them could be omitted when conducting surveys onsoundscapes with a similar sound character.
The results in this work also support previous ﬁndings that the SAM is a powerful tool for soundscape analysis,
and further to this the calculation of the perceived noise impact rating is a potential useful and informative
way to quantify the attitudes of survey group towards planned changes to an environment and including themagnitude of those changes whether positive or negative.

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1

R PNI Results

0.9

L1

0.8

L2

L3

L4

L5

Valence

0.7

ArousalR PNI

0.6
Natural

0.5
0.4

Human

0.3

Mechanical

0.2

R PNI

0.1
0

L1W L1WO L2W L2WO L3W L3WO L4W L4WO L5W L5WO

Scene

(a)

(b)

(c)
Figure 5. In (a) Results of the perceived noise impact rating, RPNI , calculated from the SAM valence andarousal scores using equation 1 for all 5 locations with (W) and without (WO) the scheme in place. The meanvalue is plotted with bars showing the standard error. In (b) Mann-Whitney U-test results comparing the resultsfor each rating scale for each of the 5 locations with and without the scheme in place. A dark square indicatesa signiﬁcant difference at 95% conﬁdence (p < 0.05). In (c) The difference between the With and Without
results for the Perceived Noise Impact Rating, a positive difference indicates a positive attitude towards thepotential change.

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Further work should include new surveys for other schemes to help conﬁrm the ﬁndings in this work, andwould ideally involve members of the public, unlike this work in which acoustics and audio specialists were
the test participants.

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