Pleasantness of typical acoustic environments inside a living room in a
European residential context
Romain DEDIEU(1,2) , Catherine LAVANDIER(2) , Cédric CAMIER(1) , Sylvain BERGER(1)(1) Saint-Gobain Research Paris, 39 quai Lucien Lefranc 93303 Aubervilliers Cedex, FRANCE,

romain.dedieu@saint-gobain.com, cedric.camier@saint-gobain.com, sylvain.berger@saint-gobain.com(2) ETIS, UMR 8051, Université de Cergy Pontoise, Site de Saint Martin, 2 rue Adolphe Chauvin, 95 302 Cergy-Pontoise Cedex,

FRANCE, catherine.lavandier@saint-gobain.com

Abstract
Acoustic comfort defined in first approach as the absence of unwanted sounds and the quality of desired sounds
while doing an activity arouses a growing interest in sociology, psychology and building industry. Comfort is
influenced by the acoustic performances of building, by the various types of sound sources, and by individual
aspects (sociological background, musical preferences etc.). A study based on three perceptive tests aims toaddress these aspects. The first perceptive test consists in the evaluation of pleasantness for various soundsources according to their semantic content and their origin (from the neighbor, the outside, or the room).
Thus, 67 focused listeners rated the pleasantness of every stimulus. Statistical analysis showed a consensus on
intrusive sounds coming from outside, people preferring bird songs and rejecting site work sounds. For intrusive
sounds coming from neighbors, there is also a consensus, people preferring classical music and rejecting humansounds. Participants can be clustered in two groups, one preferring nature sounds and the other preferring music
sounds. Moreover, the ratings of the human sound pleasantness (diner, laughs, etc.) are influenced by the soundsensitivity of the participant, the more sensitive the less pleasant the sound.
Keywords: Perception, Comfort, Building

1

INTRODUCTION

In residential building, various sound sources may be heard without consent or control. These sounds may havedifferent origins (from the neighbor, the outside, the room itself, the staircase) and types (mechanical, living,nature, etc.). Pleasantness of these sound sources may vary according to human preferences and socio cultural
factors. Comfort in dwellings is however generally only based on respect of regulations but the type of sourcesthat compose the intruding sounds is also important as revealed by a lot of field surveys [1–6]. In order to study
the influence of intruding sources on the comfort inside living room, several perceptual tests are organised in alaboratory context: (1) study of the source preferences, (2) study of masking sources and (3) study of comfort
due to the combination of the intruding sources (neighbor and outside sounds) in a living room. In this paper,
only the first test is presented. The aim of this test is to characterize the corpus participants who will be
involved into the 3 perceptual tests, focussing on their taste about intruding sounds. The method is based on alistening approach. Participants are asked to listen carefully every sound stimulus and rate sound pleasantness
on a semantic scale going from unpleasant to pleasant.

2

METHOD AND MATERIAL

2.1 Participants
67 listeners participated in the listening test. An hearing test was conducted for every participant right after
the perceptive test. The audiogram release showed that 1 listener had hearing losses too significant in order toremain in the corpus based on the audiometric classification of hearing impairment [7]. Among the 66 remaining
participants (42 % male / 58% female), 54% are workers aged 30 to 50 and 46% are students aged 18 to 30.

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All participants grew up in urban or outlying suburbs and they lived in a residential building at the time of thelistening test. Median of the noise sensitivity distribution is about 6.5 over 10 based on a self evaluation scale.
2.2 Sound sources
Semantic categories of urban sounds environments have been studied and defined in the literature [8–11]. Categorization of environmental sound sources including domestic stimuli have also been studied [12, 13] distinguishing categories according to their types. Acoustic comfort in residential buildings has been exploredfollowing an on-site approach [1, 2], and [3, 4]. Perceptive questionnaires were filled by residents living inbuildings respectively in Sweden, France, and Finland. Based on this literature review, 35 sound sources havebeen selected and presented in table 1. Sound stimuli have been chosen to be the prototypes of their semantic
categories. This corpus of stimuli aims to represent the wide variety of sound sources potentially encounteredin a dwelling. Every sound stimulus is listened at the same equivalent sound pressure level Leq equal to 35
dB(A) so that mostly the semantic content might affect the perception. Background noise in the room is about
23 dB(A). Stimuli were composed in selecting samples from sound libraries (BBC sound library, Free Sound,
Urban Sound, Universal sound bank, and Free sound) or thanks to direct measurements carried out using either
Zoom H7 recorder (with XY mics) or ORTF CCM Schoeps microphones. Each stimulus has a 30 s durationand is played in loop. In both cases, a mix of Left+Right channels is performed to get mono signals. These
mono signals are then auralized following a method described in section 2.4.
2.3 Building performances
When a sound stimulus encounters a building component, the propagation through the materials filters the incoming signal. In order to account for the building acoustic performances, simulation is carried out based on
Statistical Energy Analysis (SEA). SEA calculation is described in standard NF EN 12354-1 [14]. Simulations
are based on a building described in in table 2.
2.4 The laboratory
The laboratory and its sound reproduction system have been presented at CFA’18 [15].
Figure 1 presents a picture of the furnished laboratory/living room. The
sound reproduction system consists in 16 Yamaha HS7-I speakers and 1 Figure 1. Picture of the spatialGenelec 7070A subwoofer driven by 1 audio processor Yamaha DME64N. ized sound reproduction laboraSound strategies are designed and controlled through the software Max/MSP tory (La MIR, Neuville sur Oise,
7. As described in table 1, neighbors sound sources may have two different France)
origins, either from above or next door and outdoor sounds all come fromthe front facade. Auralization strategy consists in placing 9 regularly spaced
virtual point sources for radiating surfaces of the room (the facade, the ceiling, and the adjacent neighbor’s partition). Every point source is then spatially rendered using Vector Based Amplitude Panning (VBAP) [16]. The
ventilation coming from the room itself is auralized as a point source virtually placed at 138 deg. in azimuth and 43 deg. in elevation.
2.5 Subjective assessments and questionnaires
Participants were asked to listen carefully to the sounds for 30 seconds before answering on a tablet controlled with the software Max/MSP 7. The
General User Interface (GUI) consists in 6 tactile sliders going from -50 to+50 (-50: Unpleasant; 50: Pleasant) corresponding to 6 sounds evaluated at the time. Every stimulus is listened
separately. On the other hand, a questionnaire has been designed to evaluate mostly non-acoustic factors. The
questionnaire is organized in five main parts (general information, feedbacks on the listening test about soundrealism and ability to identify the origin of sound, participant’s dwelling description, sound sensitivity evaluation

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Table 1 – Sound stimuli description
Designation
Traf.
Steady Traf.
Hum. & Traf.
Hum. & Traf. 2
Traf. & Nat.
Traf. & Nat. 2
Nat. & Hum.
Nat. & Hum. 2
Hum.
Nat.
Nat. 2
Hum. & Traf. & Nat.
Road work
Flyover
Vacc. next door
Washer
Flush
Diner
Party
Argument
Children next door
Children next door 2
TV Doc.
TV Film
Music LF next door
Music Pop.
Music Guitar
Music Piano
Tears
Work
Vacc. above
Children above
Music LF above
Ventilation
Staircase

Description
Urban trafic on Paris street
Highway Trafic
Trafic on small street with human voices(child and woman) and footsteps
Trafic on small street
with human voices and footsteps
Trafic, storm and rain
Trafic, and birds chirpingChildren playing and birds chirping
Bird chirping,people chatting and walking
People talking
Birds chirping, water streaming
Water streaming
Birds chirping, cars passing,child talking, and footsteps
Work site with jack-hammer blows
Aircraft flyover
Vacuum cleaner
Washer in spinning mode
Pipe noise of toilet flushingneighbors talking, laughing
Music and neighbors talking, laughing
Woman arguingChildren playing with furniture ratting
Voices of children playing
Television broadcastingan BBC wildlife documentary
Television broadcasting the film
The Dark Knight
2.1 HI-FI system playing Hip-Hop music
Kendrick Lamar - Humble
2.1 HI-FI system playing
Pop. music Ed Sherann - Shape of youneighbor playing the guitar
Erik Satie Gnossienne No. 01
neighbor playing the piano
Chopin Nocturne No. 20 in C-Sharp Minor
Woman crying
neighbor’s drill working
Vaccum cleaner
Children playing with furniture ratting
2.1 HI-FI system playing Hip-Hop music
Kendrick Lamar - Humble
Ventilation system
Footsteps and slamming door
in staircase

Type
Mechanical
MechanicalMix*

Origin

Mix*
Mix*
Mix*
Mix*
Mix*
LivingNatureNatureMix*

FacadeMechanical
Mechanical
Mechanical
Mechanical
Mechanical
LivingMix*
LivingLivingLivingLivingLivingNeighbor next door

Music
Music
Music
Music
LivingMechanical
Mechanical
LivingMusic
Mechanical
LivingNeighbor from above
From the room
Neighbor next door

based on Griefahn [17] questionnaire, and quality of life assessment [18].
2.6 Procedure
Listeners were first informed of the nature of the experiment (Pleasantness evaluation of several sound stimuli). The experiment started with a training session consisting in four stimuli allowing the listeners to become
familiar with the computer tool and to the various types of sound sources they may listen. The listening test
was then carried out. Six sound stimuli are rated on the same screen. Once the 6 first stimuli are listened and4172

Table 2 – Acoustic performances of the building components simulated for the perceptive test. Global indicator
Rw computed according to ISO 717/1 standard.

Rw(C;Ctr ) (dB)

Facade12cm concrete 4mm glazing
57(-2;-6)22(0;-1)

Floor
15cm concrete
57(-2;-6)

Neighbor’s lateral wall
Alveolar partition 72
29(-1;-1)

assessed, participants may continue to the next sheet to listen and evaluate the next sounds and so on until the35th stimulus. At any time, participants are allowed to go back to the previous sheets in case they wish tochange their ratings or listen again previous sounds stimuli. The origin of the different sounds was not specified. As soon as they finished the listening test, they filled the final questionnaire. Finally, an audiogram test
was performed and participants could leave the session with their audiogram.

3

RESULTS

3.1 Sound localisation: Neighbor above & next door
As described in table 1, three sound sources have been listened from two specific directions, one time comingfrom the ceiling, the other coming in direction of the neigbor next door from the right. This duplication on
two distinct directions is meant to evaluate whether the origin of sound influences the pleasantness assessment.
Results show that mean and median values for each pair are very close (maximum 2 pt. differences in meanon the 100 point scale). Paired Student tests have also been carried out and results show that mean differences
are not significant since p-value > 0.05 in all cases. Hypothesis H0 : µ0 = µ1 is accepted, there is no significant
difference of pleasantness according to the origin of sound when the origin is clearly identified (from ceilingVs. next door). For the rest of the study, all assessments of sounds heard from the ceiling were removed fromthe dataset so as not to artificially increase their influence in the analysis.
3.2 Principal Component Analysis (PCA)
PCA allows to get summarized results to better understand how participants evaluated the stimuli.
The principal components are the principal axes of variability
in the dataset. When the dataset consists in a large number of Figure 2. Correlation diagram projected on
variables, PCA analysis tends to summarize all variables in a the two main dimensions of variability
few dimensions for which inertia is maximized. At first, PCA iscarried out in taking every participant as a variable. This first
PCA should help regrouping highly correlated individuals andhas been carried out using the programming language R, in applying the PCA() function available in FactoMineR package developed by Lê; Josse; Husson [19]. Results are presented on fig.
2. Figure 2 shows the two main dimensions of variability (70%of the total variability) and the correlations of every participant
to both axes. First, the diagram demonstrates that the first axeof variability is consensual. Indeed, almost all participants arehighly and positively correlated to the first axe. Figure 3a shows
the sound stimuli on this plan of maximal variability (Dimensions 1 & 2). The consensus is found both for intrusive sounds
coming from the neighbor as well as from the outside. For intrusive sounds coming from outside, people prefer bird songs andreject site work sounds. For intrusive sounds coming from neighbors, there is also a consensus, people preferring classical music and rejecting human sounds. Moreover, the4173

mean variable, ie the average over all participants for every stimulus is computed. Then, the correlation coefficient between the first principal component and this vector "Mean" is calculated and found equal to 1.0 as
showed in blue on fig. 2. The first component of maximal variability is the mean of pleasantness for this corpus
of sound stimuli. Sound stimuli with a low and negative coordinate on the principal component are unpleasantin average and those with high and positive coordinates are pleasant in average. Figure 2 shows that one groupof participants is very correlated to the mean and the first principal component. Indeed for 27 participants,
correlation between their individual responses profile and the mean variable is equal or higher than 0.80. In
contrast, participants 18 and 21 who are opposed on dimension 2 are among the least correlated variables.
Second, in order to interpret what dimension 2 refers to, fig. 3a shows the sound stimuli on the same planof maximal variability. Correlations of participants 18 and 21 on both dimensions are presented again as areminder. Dimension 2 is mostly influenced by the participants’ preferences regarding music stimuli compared(a) Correlation diagram(b) Pleasantness ranking

Figure 3. Sound pleasantness profile for the 35 stimuli. (a) Representation on the correlation diagram ; (b)Rank of typical sound sources in residential building - Mean sound pleasantness and standard deviation
to nature stimuli. For instance, participants 18 and 21 are opposed on dimension 2. Participant 21 perceives
pleasant all kind of music stimuli coming from the neighbor. His preference goes toward the music stimuli
rather than stimuli of nature. Participant 18’s perception is the opposite, preferring sounds of nature comingfrom the outside compared to any kind of music stimuli coming from the neighbor.
So this analysis discriminated two groups of participants, one which appreciates music whereas the other appreciates the natural sounds such as bird songs. Non-acoustic describing these two groups have not been found.
Finally, PCA showed that even if there is significant inter-individual variability, the main source of variability
in the dataset is the mean pleasantness variable summarizing 60% of total variability. Ranking sound sources
pleasantness according to their mean is presented on fig. 3b. In average, only 6 sound stimuli have been perceived positively (sounds of nature and sounds of music). In contrast, the most unpleasant sound in average are
the site work and trafic from the outside, and all human related activities such as a party, a woman crying, orsome footsteps from the neighbor or the staircase.
3.3 Clustering into 2 groups
Hierarchical Clustering on Principal Components (HCPC) is carried out to show relations between participants based on the similarities in their pleasantness profile [19]. Similarities are measured based on the eu-

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clidean distance following Ward method (minimization on the inter-cluster variability). HCPC results are presented in a dendrogram on fig. 4. In order to decide how many clusters must be taken into account, 3
statistical methods have been tested. The result depends on the method (elbow, silhouette, or gap statistic)
and varies from 1 to 4 recommended clusters. The choice of two clusters is finally confirmed due to theease of the interpretation. Group 1 and 2 consist in respectively 32 and 34 individuals. These two groups
are made of other participants than those formed thanks to the PCA and defined due to music preferences.
Two types of tests have been carried out in order to characterize these two groups. Based on the questionnaire an- Figure 4. Participants dendrogram from HCPC
swers, some pieces of information are either on the qual- following Ward method
itative form or on the quantitative form (noise sensitivity,
age, etc.). In order to evaluate whether a quantitative variable characterizes one cluster, 1 statistical test is carriedout for each cluster and for every quantitative variable. The
v.test as defined in section 3.3 of FactoMineR package description [19], tends to compare the values taken by thevariable for a given cluster compared to those taken by arandom variable. If the hypothesis H0 assuming that thevalues taken by the variable for the given cluster are random, then the quantitative variable does not describe thecluster. In contrast, if the values taken by the variable for the given cluster are unlikely to follow a random
distribution, then the quantitative variable well characterize the cluster. Results of the v-test1 are presented ontable 3. Table 3 presents 12 of the variables for which the v.test is higher than 1.96. The p-value describing therisk to be wrong in assuming H0 invalid is also presented with the addition of the mean and standard deviationof the quantitative variables in each cluster compared to overall. Two descriptive variables (not used for the
Table 3 – Description of clusters through quantitative variables
Designationv.testp.value

Sensitivity
Acoustic comfort
Children next door
Staircase
Diner
TV FilmHum.
TV Docu.
Party
Argument
Work
Children next door 2

2.91
-2.11
-6.01
-5.29
-4.81
-4.72
-4.25
-4.14
-4.41
-3.95
-3.79
-3.75

3.60e-03
3.50e-02
1.88e-09
1.21e-07
1.48e-06
2.35e-06
2.15e-05
3.39e-05
3.39e-05
7.72e-05
1.52e-04
1.75e-04

Mean in category (± SD)
Cluster 1
Cluster 2
7.03±1.41
5.94±1.38
2.81±1.18
3.47±1.24-40.12±9.65-14.76±12.73-40.62±11.08-17.97±14.59-37.28±12.82-15.15±16.56-32.84±13.20-14.03±12.85-26.00±16.14-7.53±13.60-31.34±15.95-12.21±15.95-31.34±15.95-15.15±19.39-41.31±12.40-22.82±19.47-47.15±12.24-35.64±14.24-32.94±14.24-17.02±15.90

Overall mean
6.47±1.50
3.15±1.26-27.06±17.01-28.95±17.25-25.88±18.52
23.15±16.06-16.48±17.52-21.48±18.60
21.48±18.60-31.79±18.85-41.23±12.24-24.74±17.08

HCPC calculation) have a significant contribution to describe the two clusters: the evaluation of noise sensitivity
and the evaluation of how the participants perceive the acoustic acoustic comfort in their dwelling. Statisticalanalysis shows that noise sensitivity for participants in cluster 1 (respectively in cluster 2) is significantly higher(resp. lower) than the overall mean sensitivity. Moreover, participants in cluster 1 feel less satisfied with theirhome’s acoustic comfort than participants part of cluster 2 (2.81 resp. 3.47) compared to the overall mean evaluation of comfort (3.15/5).
Participants in cluster 1 are more sensitive, are less satisfied of the acoustic comfort in their dwelling , andperceive more unpleasant intrusive sounds related to human activity (Children playing, Footsteps in the staircase, Diner, Film etc.). In contrast, participant in cluster 2 are less sensitive to noise, are more satisfied of the
1 "v.test" values are only mentioned for the cluster 1. For the cluster 2, they are the same in absolute but with the opposite sign4175

acoustic comfort in their dwelling, and perceive more pleasant intrusive sounds related to human activity. The
other two quantitative and descriptive variables (self-evaluation of life quality, and age) do not describe these 2
clusters. χ2 −tests have not allowed to better describe the clusters with the remaining descriptive and qualitative
variables. For instance, there is not significantly more workers aged 30-50 and less students aged 18-30 in 1
cluster. Moreover, mean sound pleasantness per cluster and per sound stimulus are calculated and presented on
fig. 5. In general, participants in cluster 1 evaluated less pleasant almost all sound stimuli. Mean differences
are significant.
Figure 5. Clusters comparison - Mean sound pleasantness according to the sound stimuli

4

CONCLUSION

Subjectivity in human perception generates variability when evaluating the pleasantness for the various typesof sounds in residential building. The present study aims to quantify this variability and evaluates whether it
can be explained by individuals preferences or socio-cultural factors. In order to address this problematic, alistening test was conducted in a sound spatialization laboratory. Pleasantness of 35 sound stimuli has been
rated on a semantic scale from unpleasant to pleasant. Principal component analysis revealed a consensual
dimension highly correlated to the mean pleasantness variable. Some sounds are perceived either unpleasant forall (site work, trafic, or neighbor’s work) or pleasant for all(sounds of nature, classical music). Human activities
coming from neighbor are also perceived unpleasant. However, PCA and HCPC found out two main viewpoints.
One group dislikes human related activities coming from the neighor with a rating much lower than the othergroup. This group is composed of individuals more sensitive to noise in average and are unsatisfied with theacoustic comfort at home. In contrast, the second group is made of people rather less sensitive to noise andmore satisfied with their dwelling acoustic comfort. They seem to better tolerate intrusive sounds since they
rated more pleasant almost all sound sources. Preferences are also found out regarding sounds of nature versus
sounds of classical music indicating that even if all of them are perceived pleasant, one group of individuals
prefers intrusive classical music coming form the neighbor whereas the other group prefers listening to soundsof nature coming from the outside of the building.

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