Acoustics — Soundscape — Part 3: Data analysis

This document provides requirements and supporting information on analysis of data collected in-situ through methods as specified in ISO/TS 12913-2.

Acoustique — Paysage sonore — Partie 3: Analyse de données

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Acoustics — Soundscape —
Part 3:
Data analysis
Acoustique — Paysage sonore —
Partie 3: Analyse de données
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ISO/TS 12913-3:2019(E)
ISO 2019

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ISO/TS 12913-3:2019(E)

© ISO 2019
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ISO/TS 12913-3:2019(E)

Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 General . 1
5 Analysis of quantitative data . 2
6 Analysis of qualitative data . 2
7 Analysis of binaural data. 2
8 Triangulation . 3
Annex A (informative) Analysis of data related to Method A . 4
Annex B (informative) Analysis of data related to Method B . 8
Annex C (informative) Analysis of data related to Method C .10
Annex D (informative) Analysis of binaural data .12
Annex E (informative) Triangulation .16
Annex F (informative) Laboratory studies .17
Bibliography .19
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ISO/TS 12913-3:2019(E)

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iso/ foreword .html.
This document was prepared by Technical Committee ISO/TC 43, Acoustics, Subcommittee SC 1, Noise.
A list of all parts in the ISO 12913 series can be found on the ISO website.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/ members .html.
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ISO/TS 12913-3:2019(E)

The ISO 12913 series on soundscape was developed in order to enable a broad international consensus
and to provide a foundation for communication across disciplines and professions with an interest
in soundscape. ISO 12913-1 provides the definition of and a conceptual framework for the term
‘soundscape’. ISO/TS 12913-2 provides requirements and supporting information on data collection and
reporting for soundscape studies, investigations and applications. This document provides guidance on
how to analyse data collected in agreement with ISO/TS 12913-2.
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Acoustics — Soundscape —
Part 3:
Data analysis
1 Scope
This document provides requirements and supporting information on analysis of data collected in-situ
through methods as specified in ISO/TS 12913-2.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements of this document. For dated references, only the edition cited applies. For
undated references, the latest edition of the referenced document (including any amendments) applies.
ISO 12913-1, Acoustics — Soundscape — Part 1: Definition and conceptual framework
ISO/TS 12913-2:2018, Acoustics — Soundscape — Part 2: Data collection and reporting requirements
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 12913-1 and ISO/TS 12913-2
and the following apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at http:// www .electropedia .org/
factor influencing the collected responses that is not controlled or systematically considered
EXAMPLE Sequential effect, certain scaling effects like the range effect, or demand characteristics.
4 General
As mentioned in the Introduction of ISO/TS 12913-2:2018, “The concept of soundscape was adopted to
provide a holistic approach to the acoustic environment, beyond noise, and its effect on the quality of life.
Soundscape investigations intend to assess all sounds perceived in an environment in all its complexity.
To do this, soundscape studies use a variety of data collection methods related to human perception, the
acoustic environment and the context. Importantly, the study of soundscape relies primarily upon human
perception, and only then turns to physical measurement.” Data collection is based on this focus and
requires a respective analysis (see References [1],[2]).
For the analysis of qualitative and quantitative data through methods specified in ISO/TS 12913-2,
methods and tools shall be applied as provided in this document. Given the diversity of the data collected
(qualitative and quantitative), corresponding analysis methods could take precedence depending on
the needs of the project or the research question, and should be integrated for a holistic understanding
of the soundscape. In general, descriptive statistics are used to describe and summarize the collected
perceptual data, such as measures of central tendency, measures of dispersion (see Reference [3]).
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For quantitative measures of dependence, inferential statistics using parametric and non-parametric
tests shall be applied depending on the respective data. Fulfilment of model assumptions (e.g. normality
distribution) shall be carefully assessed, especially in the case of small numbers of participants. If
needed, appropriate remedial measures shall be applied. However, as soundscape investigations are
intended to be “holistic in covering all auditory sensations as well as all other context variables such
as visual stimuli and personal expectations” [ISO/TS 12913-2], the use of statistical analysis methods
(e.g. statistical hypothesis testing) is recommended, but may be less important in case of qualitative
or explorative methods. For qualitative data, a variety of approaches are available to systematically
analyse qualitative data using some kind of step by step coding principles to generalize the observations.
In addition, soundwalks are a method for bringing diverse parties together and provide a common basis
for communication.
Because of factors that could influence results, a thorough discussion of potential confounders (i.e. bias
effects) shall complete the general data analysis. Confounders are, for example, the sequential effect
(a previous site influences the assessments of the following site) (see Reference [4]) certain scaling
effects, like the range effect (tendency to use full range of a scale independent from stimuli set) (see
Reference [5]), or demand characteristics (cues, like the instruction text or the behaviour of the person
leading the soundwalk, that signal the research goal and influence assessments) (see Reference [6]).
NOTE Based on the collected data, it is possible to study classification of sites. For the study of classification
of sites, different statistical clustering methods are available, which allows for identifying relevant variables for
clustering and determining the similarity or dissimilarity of sites.
5 Analysis of quantitative data
The quantitative data obtained by means of questionnaires in soundscape investigations shall be
analysed depending on the respective level of measurement (i.e. nominal, ordinal, interval, and
ratio). Any correlation analysis shall be chosen in accordance with the level of measurement of the
questionnaire data. Inferential statistical tests regarding the level of significance of differences in
evaluation between sites and/or correlations shall be carried out and probability values reported.
Any chosen method (e.g. measure of central tendency, measure of dispersion, correlation analysis, and
statistical hypothesis testing method) shall be reported. For more information, see Annex A (Method A)
and Annex B (Method B).
6 Analysis of qualitative data
Data from qualitative interviews shall be transcribed for reporting and further analysis. The style of
transcription, whether clean read, verbatim or strict verbatim transcription, depends on the object
of the investigation. For the analysis via the Grounded Theory, the clean read transcription style is
sufficient. Violations of common rules for conducting interviews (ethical rules, being suggestive, being
prejudiced) shall be reported, and the related data excluded from further analysis.
Qualitative data shall be analysed by scientifically proven systematic text analysis methods, such as
the Grounded Theory (see Reference [7]), Qualitative Content Analysis (see Reference [8]) or Social
Network Analysis as part of mixed-methods design (see Reference [9]). The process of analysis shall
follow these methods and be described. For more information, see Annex C.
In addition to established text analysis methods, other methods to gather and analyse qualitative data
(such as behavioral mapping, observational analyses, analysis of social interaction, walking patterns;
see examples in References [61], [62], [63], [64]) are available and, if determined appropriate in certain
cases, shall be applied.
7 Analysis of binaural data
The binaural recordings are the basis for characterizing the acoustic environment at the receiver as
the sound from all sound sources modified by the environment [ISO 12913-1]. The measurements and
their psychoacoustic analyses enable the determination of the (basic) auditory sensations evoked by
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the sound. Any binaural recording shall be equalized for the analysis as specified in ISO/TS 12913-2,
approximating a monaural microphone measurement.
After applying the recording equalization, the remaining signals of the left and right channels are
separately processed to determine (psycho-)acoustic metrics.
The different metrics used (e.g. L , L , L , L , N , N , N , S , IACC) shall be linked to the
Aeq,T Ceq,T AF5,T AF95,T 5 95 rmc 50
perception and the assessment of the concerned people [ISO/TS 12913-2]. In general, the consideration
of acoustic analysis results shall provide a basis for the evaluation and classification of soundscapes by
complementing the perceptual data. Moreover, based on the results of the binaural data analysis, given
sufficient position data, maps based on psychoacoustic and other data can be determined. For more
information, see Annex D.
8 Triangulation
The general idea of triangulation is to achieve a higher level of validity if different methods applied lead
to the same result and hierarchical agglomerative clustering complement each other. Triangulation for
soundscape measurement is a technique that facilitates validation of data through cross verification of
three components: people, context and acoustic environment. In particular, it refers to the application
and combination of several research methods in the study of the same phenomenon. For more
information, see Annex E.
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Annex A

Analysis of data related to Method A
A.1 General
Method A, described in C.3.1 of ISO/TS 12913-2:2018, consists of category scales containing five
response categories.
A.2 Determination of central tendencies of responses
For the analysis of the collected responses by means of Method A as described in C.3.1 of
ISO/TS 12913-2:2018, numbers shall be assigned to the response categories of the category scales as
The five response categories of questionnaire part 1 (see Figures C.2 and C.3 of Annex C of
ISO/TS 12913-2:2018) from left (‘not at all’) to right (‘dominates completely’) are assigned scale values
from 1 to 5.
The five response categories of questionnaire part 2 (see Figure C.4 of Annex C of ISO/TS 12913-2:2018)
from left (‘strongly agree’) to right (‘strongly disagree’) are assigned scale values from 5 to 1.
The five response categories of questionnaire part 3 (see Figure C.5 of Annex C of ISO/TS 12913-2:2018)
from left (‘very good’) to right (‘very bad’) are assigned scale values from 5 to 1.
The five response categories of questionnaire part 4 (see Figure C.6 of Annex C of ISO/TS 12913-2:2018)
from left (‘not at all’) to right (‘perfectly’) are assigned scale values from 1 to 5.
For all category scales, the level of measurement is ordinal, which means that the median values
should be reported as the measure of central tendency, and the range as the measure of dispersion. See
Table A.1.
Table A.1 — Assigned scale values to rating scales of Method A and statistical measures
Scale values to be Measure of central Measure of
Part (see ISO/TS 12913-2)
assigned tendency dispersion
1 (sound source identification) 1 ,2 ,3, 4, 5 median range
2 (perceived affective quality) 5, 4, 3, 2, 1 median range
3 (assessment of surrounding sound 5, 4, 3, 2, 1 median range
4 (assessment of the appropriateness) 1, 2, 3, 4, 5 median range
A.3 Determination of two soundscape dimensions based on perceived affective
quality responses
Environmental psychologists have repeatedly demonstrated that when people are asked to freely
describe how they perceive environments they respond affectively (see Reference [10]).
These affective responses can be represented in a two-dimensional model where the main dimension
is related to how pleasant or unpleasant the environment was judged, and therefore noted as
pleasantness. The second dimension is related to the amount of human and other activity (see
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Reference [11]). For soundscape, this second dimension is represented by how eventful or uneventful
the acoustic environment is perceived to be, and therefore noted as eventfulness (see Reference [12]).
An eventful environment is busy with human activity, for example a city centre or other sound events
produced by non-human agents, whereas an uneventful environment is completely devoid of human
activity, for example a wilderness area or during late evening hours in a residential area without social,
commercial and industrial activity. If the previously mentioned pleasantness and eventfulness axes
are taken as perpendicular, further labelling corresponding to human judgments can be prescribed to
two additional axes rotated 45°on the same plane. At a rotation of 45° from the two main dimensions,
are two alternative dimensions representing environments that are chaotic and stressful versus calm,
and environments that are monotonous and dull versus vibrant and exciting (see References [12] and
[13]). According to the two-dimensional model, vibrant soundscapes are both pleasant and eventful,
chaotic soundscapes are both eventful and unpleasant, monotonous soundscape are both unpleasant
and uneventful, and finally calm soundscapes are both uneventful and pleasant.
NOTE Based on the tradition in environmental noise research, the term ’annoying’ is used instead of
‘unpleasant’ in the model used in this document. However, some sociological models ascribe a stronger sense of
intentionality to sounds that are annoying compared to those that are unpleasant.
The results from part 3 (see A.1) are further processed to derive the values on two dimensions
(pleasantness and eventfulness) for each site. Results can be reported in a two-dimensional scatter
plot with coordinates for the two dimensions ‘pleasantness’ and ‘eventfulness’ (see Figure A.1). The
coordinates for ‘pleasantness’ are plotted on the X-axis, and the coordinates for ‘eventfulness’ on the
Y-axis. Every data point in the scatter plot represents one investigated site.
The coordinate for pleasantness P is calculated by means of Formula (A.1):
Pp=−()ac+°cosc45 ⋅−()achv+°os45 ⋅−()m (A.1)
The coordinate for eventfulness E is calculated by means of Formula (A.2):
Ee=−()uc+°cosc45 ⋅−()hcav+°os45 ⋅−()m (A.2)
a is annoying;
ca is calm;
ch is chaotic;
e is eventful;
m is monotonous;
p is pleasant;
u is uneventful;
v is vibrant.
In Formulas (A.1) and (A.2), cos45° is used as a weighting function to adjust for the 45° rotation in the
two-dimensional model (Figure A.1). The range of the coordinates that results from the formulas is
±+4329=± ,66 . To change the range to ±1, divide the coordinates by 43+ 2 .
() ()
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Figure A.1 — Graphical representation of Formulas (A.1) and (A.2)
NOTE The generality of the two-dimensional model is still under examination (see for example Reference [65])
and it is noted that the two-dimensional model requires further validation across languages and sites.
A.4 Link of Method A results to acoustic data
Rating data collected via questionnaires should be linked to the results of the acoustic data analyses
in order to identify potential relationships (see References [14] and [15]). These relationships may be
investigated by means of statistical analyses, such as correlation analyses, linear regression or ANOVA
(see References [47]). The adequate correlation analysis depends on the level of the measurement scale
(e.g. ordinal vs. interval). For ordinal data, the Spearman's rank correlation coefficient, r , should
be calculated (see Reference [16], [46], and [60]) using Formulas (A.3) and (A.4).
6⋅ d
∑ i
r =−11 for untied ranks (A.3)
nn− 
2⋅ −−TU− d
 
∑ i
 
r = for tied ranks (A.4)
   
nn− nn−
2⋅ −T ⋅ −U
   
12 112
   
d is the difference in paired ranks;
n is the number of cases;

∑ jj
T= ;


U= ;
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t is the number of in t tied ranks of the variable x;
j j
u is the number of in u tied ranks of the variable y;
j j
k(x) and k(y) are the numbers of tied ranks of the variables x and y.
The determined correlation coefficient should be reported as a numerical measure of statistical
relationship between two variables. In addition, the statistical significance of the correlation should be
determined, and the probability value reported.
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Annex B

Analysis of data related to Method B
B.1 General
Method B, described in C.3.2 of ISO/TS 12913-2:2018, consists of five-point unipolar continuous-
category scales, a ranking test and free words data, which should be separately analysed. The free
words data refer to method B as described in C.3.2 of ISO/TS 12913-2:2018 where, after listening,
the soundwalk participants are requested to write down their thoughts and feelings while still at the
specific location.
B.2 Determination of central tendencies of responses
Part 1 (assessment of the sound environment — ISO/TS 12913-2:2018, Figure C.7)
The responses on the five-point unipolar continuous-category scales are assigned the scale values from
1 to 5 in dependence of the marked point on the scale (see Table B.1). The values used for analysis
shall be determined at least with one decimal place. This shall be done by using a ruler and measuring
the position of the marked point on the scale with the accuracy of one decimal point or, in case of
assessments digitally collected on a computer screen, by determining the marked point on the scale with
the accuracy of one decimal point (rounded). The level of measurement is interval (see Reference [17]),
which means that the arithmetic mean value for each site should be reported as the measure of central
tendency. For each determined arithmetic mean value, the standard deviation and the 95 % confidence
interval should be calculated. However, the ratings may not represent an interval scale, and statistics
for an ordinal scale level may be additionally applied.
NOTE If considered to provide further information, other measures of central tendency can be determined.
Part 2 (sound source recognition, including ranking — ISO/TS 12913-2:2018, Figure C.8)
The ranking responses are assigned the values starting with 1 (natural numbers) up to 8 (if 8 different
sources are listed), indicating the most noticeable sound sources at a site (see Table B.1). The level of
measurement is ordinal, which means that the median value for all recognized sound source at each
site should be reported as the measure of central tendency.
The indication of certain sound sources, assessed as most noticeable by the different soundwalk
participants, can be related to the collected ratings of part 1. A specific focus on a sound source or on a
set of sources might influence the assessment of the sound environment in its entirety, and thus should
be explored. The data might allow studying the relevance of sound source focus to the perception and
assessment of multi-sound source scenarios as acoustic environments usually are.
Table B.1 — Assigned scale values to rating scales of Method B and statistical measures
Scale values Measure of Measure of
Part (see ISO/TS 12913-2)
to be assigned central tendency dispersion
1 (assessment of the sound 1 - 5 arithmetic mean standard deviation
2 (sound source recognition) 1 ,2 ,3, 4, 5, 6, 7, 8 median range
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Part 3 (subsequent comments — ISO/TS 12913-2:2018, Figure C.9)
For analyses, the responses related to part 3 (subsequent comments) gained by a soundwalk should
be systematically analysed. For it, the provided comments are clustered by increasing the level of
abstraction of the used word to identify meaningful categories. This analysis process can be realized
according to established methods of empirical social research, such as the Grounded Theory (see
Reference [7]) or Qualitative Content Analysis (see Reference [8]). By means of categories identified
and the frequency of occurrence of certain categories at each site, standard statistical analysis can be
performed (e.g. in terms of histograms). This analysis is performed per site and per condition (e.g. time
of the day), where applicable.
The analysis can be additionally performed for all sites together investigating the general character of
the investigated area covered by the soundwalk and for later comparison to other investigated areas.
NOTE Free response data are needed to understand the meaning of scaling or responses to structured
questionnaires. People involved can use their own words to describe their perception and feelings.
B.3 Link of Method B results to acoustic data
The analysis of the link between results and acoustic data should be determined according to A.4. For
interval data, the Pearson correlation coefficient, r, should be calculated (see Reference [48]) according
to the Formulas (B.1) and (B.2).
r= (B.1)
σ is the standard deviation of the array x ;
x i
σ is the standard deviation of the array y ;
y i
xx− ⋅−yy
() ()

cov()xy, = (B.2)
is the arithmetic mean value of the array x ;
is the arithmetic mean value of the array y ;
n is the number of cases.
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Annex C

Analysis of data related to Method C
Method C, described in C.3.3 of ISO/TS 12913-2:2018, provides a guideline for a narrative interview
consisting of several open questions that allow for deepening the understanding of the effects of
The guideline referring to satisfaction with the living space, residential experience, experiences with/
relation to sounds in life, daily routines, co-inhabitants, neighbours, spatial identification of sound
effects should be systematically analysed according to an established interview analysis using explicit
systematic procedures.
An established analysis method is the Grounded Theory, which enables the development of integrative
diagrams leading to a systematic model of categories that give access to main strategies of habits with
regard to living in an acoustic environment (see References [18] to [23]). The Grounded Theory is simply
the discovery of emerging patterns in data. The Gr

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