ArticlePDF Available

Abstract and Figures

Auditory masking of unwanted sounds by wanted sounds has been suggested as a tool for outdoor acoustic design. Anecdotal evidence exists for successful applications, for instance the use of fountain sounds for masking road traffic noise in urban parks. However, basic research on auditory masking of environmental sounds is lacking. Therefore, we conducted two listening experiments, using binaural recordings from a city park in Stockholm exposed to traffic noise from a main road and sound from a large fountain located in the center of the park. In the first experiment, 17 listeners assessed the loudness of the road traffic noise and fountain sounds from recordings at various distances from the road, with or without the fountain turned on. In the second experiment, 16 listeners assessed the loudness of systematic combinations of a singular fountain sound and a singular road traffic noise. The results of the first experiment showed that the fountain sound reduced the loudness of road traffic noise close to the fountain, and that the fountain sound was equally loud or louder than the road traffic noise in a region 20-30 m around the fountain. This suggests that the fountain added to the quality of the city park soundscape by reducing the loudness of the (presumably unwanted) traffic noise. On the other hand, results from the second experiment showed that road traffic noise was harder to mask than fountain sound, and that the partial loudness of both sources was considerably less than expected from a model of energetic masking. This indicates that auditory processes, possibly related to target-masker confusion, may reduce the overall masking effect of environmental sounds. (C) 2010 Institute of Noise Control Engineering.
Content may be subject to copyright.
Auditory masking of wanted and unwanted sounds in a city park
Mats E. Nilsson
a)
, Jesper Alvarsson
b)
, Maria Rådsten-Ekman
c)
and Karl Bolin
d)
(Received: 31 August 2009; Revised: 21 June 2010; Accepted: 21 June 2010)
Auditory masking of unwanted sounds by wanted sounds has been suggested as
a tool for outdoor acoustic design. Anecdotal evidence exists for successful
applications, for instance the use of fountain sounds for masking road traffic
noise in urban parks. However, basic research on auditory masking of
environmental sounds is lacking. Therefore , we conducted two listening
experiments, using binaural recordings from a city park in Stockholm exposed
to traffic noise from a main road and sound from a large fountain located in the
center of the park. In the first experiment, 17 listeners assessed the loudness of
the road traffic noise and fountain sounds from recordings at various distances
from the road, with or without the fountain turned on. In the second experiment,
16 listeners assessed the loudness of systematic combinations of a singular
fountain sound and a singular road traffic noise. The results of the first
experiment showed that the fountain sound reduced the loudness of road traffic
noise close to the fountain, and that the fountain sound was equally loud or
louder than the road traffic noise in a region 2030 m around the fountain. This
suggests that the fountain added to the quality of the city park soundscape by
reducing the loudness of the (presumably unwanted) traffic noise. On the other
hand, results from the second experiment showed that road traffic noise was
harder to mask than fountain sound, and that the partial loudness of both
sources was considerably less than expected from a model of energetic masking.
This indicates that auditory processes, possibly related to target-masker
confusion, may reduce the overall masking effect of environmental sounds.
© 2010 Institute of Noise Control Engineering.
Primary subject classification: 56.3; Secondary subject classification: 61.5
1 INTRODUCTION
In urban open areas, natural sounds such as sounds
from water, are typically perceived as wanted whereas
traffic noise is perceived as unwanted
1,2
. In such areas,
the obvious approach to soundscape improvement
would be to reduce the noise. This is, however, often
impossible due to political, economical, safety, or
aesthetic reasons. For instance, noise barriers are often
considered to be too expensive or visually intrusive in
central urban areas. An alternative approach would be
to promote the wanted sounds in order to mask the
unwanted sound. This is an old idea and anecdotal
evidence exists for successful applications, for instance
the use of fountain sounds for masking road traffic
noise in urban parks
3–6
. Systematic research on the
potentials and limitations of the method is, however,
lacking. This research need motivated the present
psychoacoustic study, which evaluated the masking
potential of fountain sound and road traffic noise in a
typical city park.
A masking sound makes a target sound inaudible
(complete masking) or less loud (partial masking) by
decreasing the signal-to-noise ratios in the frequency
regions surrounding the target sound at the basilar
membrane
7
. This type of masking is called “energetic”
masking, to be distinguished from “informational”
masking due auditory mechanisms at higher levels of
a)
Gösta Ekman Laboratory, Institute of Environmental
Medicine, Karolinska Institutet & Department of Psychol-
ogy, Stockholm University, SE-106 91 Stockholm SWE-
DEN; email: mats.nilsson@psychology.su.se.
b)
Gösta Ekman Laboratory, Institute of Environmental
Medicine, Karolinska Institutet & Department of Psychol-
ogy, Stockholm University, SE-106 91 Stockholm SWE-
DEN; email: jesper.alvarsson@psychology.su.se.
c)
Gösta Ekman Laboratory, Institute of Environmental
Medicine, Karolinska Institutet & Department of Psychol-
ogy, Stockholm University, SE-106 91 Stockholm SWE-
DEN; email: maria.radsten.ekman@psychology.su.se.
d)
The Marcus Wallenberg Laboratory, Kungliga Tekniska
Högskolan, Stockholm SWEDEN; email: kbolin@kth.se.
524 Noise Control Eng. J. 58 (5), Sept-Oct 2010
processing
8
. The overall masking of a sound may then
be defined as the sum of energetic and informational
masking
9
. An example of informational masking would
be confusion due to target-masker similarity, which has
been suggested as relevant for environmental sounds
10
.
If a part of the masking sound is confused with the
target sound, then the overall masking would decrease.
And, conversely, if part of the target sound is confused
with the masking sound, then the overall masking
would increase.
Glasberg and Moore
11
have proposed a model of
energetic masking of time-varying sounds. The model
takes into account the processes at the auditory periph-
ery that affects energetic masking, including the
frequency response of the outer and middle ear, the size
of critical bands and masking across adjacent critical
bands. For sound combinations with limited informa-
tional masking, the model predicts masking well
11
.
However, if informational masking is substantial, the
model will do worse because it only considers energetic
masking. Differences between results of listening
experiments and predictions of the models may thus
indicate the amount of informational masking, because
listening experiments always measure overall masking,
whereas the model only predicts energetic masking.
This article presents the result of two listening
experiments on auditory masking of road traffic and
fountain sounds. The purpose of the first listening
experiment was to explore the masking effect of
fountain sounds and road traffic noise using realistic
recordings conducted in a city park. The purpose of the
second experiment was to quantify the masking effect,
using systematically manipulated sound levels of
fountain and road traffic sounds, and to assess the
amount of energetic and informational masking by
comparing masking obtained in the listening experi-
ment with predictions of Glasberg and Moore’s
model
11
.
2 EXPERIMENT 1: METHOD
2.1 Equipment
The sounds were recorded using a binaural head and
torso simulator Brüel & Kjær type 4100, with two
microphones type 4190 and two pre-amplifiers type
2669, one conditioning amplifier NEXUS Brüel &
Kjær type 2690 A 0S4 and a calibrator Brüel & Kjær
type 4231 plus adapter model 0887. A portable
computer Dolch NPAC-Plus P111, with a 6-channel
LynxTwo sound card, stored the recordings with 24 bit
resolution and 48 kHz sampling frequency using Sound
Forge 7. Editing and mixing of experimental sounds was
conducted using the same program.
The listening experiment was conducted in a semi
soundproof room. The experimental sounds were fed
into a digital filter and D/A-converter Rane RPM 26z,
and were then presented through Sennheiser HD 600
headphones. The whole listening system was calibrated
using a pink-noise signal, which was measured using a
binaural head (B&K type 4100) at the point of the
listener’s head. The frequency response of the whole
listening system was flat within 2 dB, 1/3-octave-band
levels, 25 16 000 Hz. Experimental sounds were
presented and responses were collected using a script
written in Matlab 6.5.
2.2 Binaural Recordings
Binaural recordings were conducted in a park in the
inner city of Stockholm (Mariatorget). The park has a
large jet and basin type fountain in the center of the
park, about 50 m from a main road (Hornsgatan).
Recordings were conducted during approximately
20 minutes at each of seven distances from the main road
(1, 19, 37, 55, 78, 105, and 128 m), once with the
fountain turned on and once when it was turned off.
Figure 1 shows an aerial photograph of the park (left) and
a noise map (right) of road-traffic noise, L
day
.Themap
also shows the recording sites numbered 1 to 7, and the
location of the fountain (ellipse). Figure 2 shows photos
taken during recordings in the park.
Fig. 1—Aerial photograph (left) and noise map
(right) of the city park. The noise map
shows road traffic noise exposure
L
day
.
The map also shows the recording sites,
circles numbered 1 to 7, and the location
of the fountain (blue ellipse). L
day
calcu-
lated using the Nordic Calculation
Method
15
.
Noise Control Eng. J. 58 (5), Sept-Oct 2010 525
2.3 Experimental Sounds
The experimental sounds consisted of 5-s sounds
taken from the binaural recordings. From each of the
14 recordings (7 distances, once with and once without
fountain sound), 6 sounds were selected, in total 84
experimental sounds. The selected sounds were
relatively steady state, and we excluded excerpts that
contained unusual sounds such as ambulance sirens or
people talking close to the microphone. Table 1 gives
mean and range of a selected set of acoustic variables
of the experimental sounds. These variables are related
to the overall level L
Aeq,5s
, peaks L
A10
, spectral
content L
Ceq,5s
L
Aeq,5s
and time variability of the
sounds L
A10
L
A90
. The levels were calculated as the
logarithm of the average of the anti log of decibel-values
from each channel of the binaural recordings
12
.
As expected, the greatest difference between record-
ings conducted with or without the fountain was found
close to the fountain, at 1 m distance to the fountain
side. At these locations, the equivalent sound pressure
level L
Aeq,5s
was 5 10 dB higher and the relative level
of low-frequency sound L
Ceq,5s
L
Aeq,5s
was substan-
tially lower with than without the sound from the fountain.
This shows that the fountain determined the equivalent
sound level close to the fountain and that a significant part
of its sound energy was in the high frequency part of the
spectrum. Peaks L
A10
and variability L
A10
L
A90
of the
sounds was not strongly influenced by the fountain, which
reflects its steady-state character.
2.4 Procedure
The experiment consisted of four listening sessions,
separated with a short pause. In each of the sessions,
the 84 experimental sounds were presented in a random
order. The sounds were assessed for road traffic
Fig. 2—Photos taken during recordings in the
park.
Table 1—Recording locations and levels of experimental sounds in Experiment 1.
Recording location Mean (range) levels of six experimental sounds [dB]
Recording
Location
a
Distance to
roadside (m)
Distance to
fountain
side (m)
Fountain
on (1) or
off (0)
L
Aeq,5s
b
L
A10
c
L
Ceq,5s
L
Aeq,5s
d
L
A10
L
A90
e
1. 1 55 1 73 (71–75) 84 (81–87) 7 (4–9) 4 (3–5)
1. 1 55 0 73 (70–76) 84 (81–87) 6 (5–8) 5 (3–7)
2. 19 36 1 68 (67–69) 83 (81–85) 11 (10–13) 3 (2–4)
2. 19 36 0 67 (65–69) 84 (79–91) 10 (9–13) 5 (3–8)
3. 37 18 1 62 (61–63) 82 (80–84) 13 (10–15) 6 (3–8)
3. 37 18 0 63 (61–64) 85 (81–88) 12 (10–14) 7 (3–11)
4. 55 1 1 66 (66–66) 78 (75–81) 7 (5–9) 4 (2–6)
4. 55 1 0 62 (61–63) 83 (79–88) 15 (13–17) 5 (3–7)
5. 78 1 1 69 (67–69) 80 (78–84) 5 (2–8) 5 (3–7)
5. 78 1 0 59 (58–61) 80 (75–85) 13 (12–15) 5 (3–7)
6. 105 27 1 60 (59–61) 77 (71–81) 12 (8–14) 4 (3–6)
6. 105 27 0 59 (57–61) 78 (75–81) 12 (10–13) 5 (4–7)
7. 128 50 1 59 (57–61) 79 (75–85) 13 (11–15) 5 (3–7)
7. 128 50 0 62 (61–63) 78 (74–82) 8 (7–10) 6 (4–10)
a
Numbered as in the right diagram of Fig. 1.
b
A-weighted equivalent continuous sound pressure level.
c
A-weighted sound pressure level exceeded 10% of the time.
d
Relative level of low-frequency sound
12
, difference between C- and A-weighted equivalent continuous sound pressure level.
e
Variability
12
, difference between levels exceeded 10% and 90% of the time.
526 Noise Control Eng. J. 58 (5), Sept-Oct 2010
loudness in two sessions and for fountain loudness in
the other two sessions. Half of the listeners started with
assessing road traffic loudness followed by fountain
loudness whereas the others assessed the sources in the
reverse order.
The participants were tested individually. They
listened to the sounds through ear phones. After each
sound presentation, the listeners entered a response on
a computer keyboard, after which the next sound was
presented. Perceived loudness was assessed with the
method of free number magnitude estimation. This
method is described in detail elsewhere
13
. Briefly, the
participants were asked to assign any numbers they like
to the sounds as long as the numbers were proportional
to the perceived loudness of the sounds. If the sound
source could not be heard, the participants were
instructed to answer “0”. A training session was
conducted before the first session. The experiment took
about 32 minutes to complete including pauses.
2.5 Participants
Seventeen university students participated in Experi-
ment 1 (9 women and 8 men, mean age=27 years). The
participant’s hearing status was measured using an
audiometer (Interacoustics Diagnostic Audiometer
AD226, Hughson-Westlake method). All participants had
hearing thresholds lower than 25 dB in their best ear for
all tested frequencies (0.125, 0.5, 1, 2, 3, 4, and 6 kHz).
3 EXPERIMENT 1: RESULTS
Visual inspection of the individual results showed a
similar trend for all listeners, and Pearson’s coefficients
of correlation between individual scales of fountain
and traffic loudness were found to be high, ranging
from 0.72–0.99 mean= 0.94 for fountain loudness and
from 0.85–0.99 mean= 0.94 for traffic loudness. It was
therefore justified to include data from all participants in
the group analyses reported below.
All magnitude estimates were brought to a common
modulus for all listeners and were then averaged
geometrically for each experimental sound and
loudness instruction
14
. This procedure excluded all
magnitude estimates equal to zero. However, if more
than 50 percent of the individual magnitude estimates
of an experimental sound were zero, then the group
scale was set to zero (i.e., inaudible). In the following,
group scales are presented on a logarithmic scale, as
recommended for data obtained by ratio scaling
methods such as magnitude estimation
13
.
Figure 3 shows the group scales for road traffic and
fountain loudness as a function of distance to the side
of the main road. Distance to the fountain side is
indicated on the upper x-axis. Six sounds from each
distance were used in the experiment (see Sec. 2.2).
Thus, each data point in Fig. 3 refers to an average of
group scale values for six sounds. Filled symbols refer
to loudness of road traffic noise, open symbols refer to
loudness of fountain sound. Triangles refer to sounds
recorded when the fountain was turned on, and circles
refer to sounds recorded with the fountain turned off.
Figure 3 shows that road-traffic loudness was
substantially reduced but not completely masked close
to the fountain side. At the other locations, road traffic
loudness was unaffected by the fountain sound. The
results also showed that the fountain sound was
completely masked 1 20 m from the main road, but that
the fountain sound was equally loud or louder than the
road traffic noise in a region 20 30 m around the
fountain (at 40 100 m from the main road).
Thus, the results suggest that the fountain sound may
have added to the quality of the city park soundscape
by reducing the loudness of the (presumably unwanted)
traffic noise. On the other hand, the results suggest that
the road traffic noise had a greater impact on fountain
sound than the other way around, because fountain
sound was completely masked close to the road,
whereas road traffic noise was only partially masked
close to the fountain.
Although the results of Experiment 1 supports the
conclusion that road traffic noise masked the fountain
sound more than the other way around, the experimen-
tal design did not allow a direct test of this asymmetry.
0 20 40 60 80 100 120 14
0
1.0
1.2
1.4
1.6
1.8
2.0
Perceived loudness
(magnitude estimates, log units)
Distance to roadside (m)
Distance to fountain side (m)
Road traffic l oudness (fountain off)
Fountain loudness
Road traffic l oudness (fountain on)
- f
0.8
36 18
1
1
27 5055
0 20 40 60 80 100 120 14
0
1.0
1.2
1.4
1.6
1.8
2.0
Perceived loudness
(magnitude estimates, log units)
Distance to roadside (m)
Distance to fountain side (m)
Road traffic l oudness (fountain off)
Road traffic l oudness (fountain off)
Fountain loudnessFountain loudness
Road traffic l oudness (fountain on)Road traffic l oudness (fountain on)
- f
0.8
36 18
1
1
27 5055
Fig. 3—Perceived loudness (log scale) of road-
traffic noise (filled symbols) and fountain
sound (open symbols) in a Stockholm city
park, as a function of distance from the
main road. Distance to the fountain side
is given on the upper x-axis. Loudness of
road traffic noise was assessed for record-
ings with the fountain turned on (tri-
angles) and turned off (circles).
Noise Control Eng. J. 58 (5), Sept-Oct 2010 527
This is because Experiment 1 lacked a comparison of
fountain loudness with and without road traffic (traffic
noise was always present, also during night). We there-
fore conducted a second experiment where levels of
traffic noise and fountain sound were manipulated
systematically. This also made it possible to assess the
amount of energetic and informational masking, by
comparing the experimental results with predictions of
Glasberg and Moore’s model of energetic masking
11
.
4 EXPERIMENT 2: METHOD
4.1 Experimental Sounds
Two 5-s experimental sounds were taken from
recordings conducted in the same city park as in
Experiment 1. The first experimental sound was taken
from a binaural recording conduced at 19 m distance
from the road, with the fountain turned off. The second
5-s sound was taken from a mono recording conducted at
1 m distance from the fountain side, during night with a
minimum of traffic on nearby roads. The two sounds were
completely dominated by one type of sound: road traffic
noise or fountain sound. In order to control for effects of
binaural level differences on masking, both sounds were
presented diotically (using the channel with the higher
sound pressure level).
Different sound levels (linear attenuation) of the
fountain and road traffic sound were used as experi-
mental sounds, either presented singularly or combined
with the other sound as masker. The masker sound was
set to 65 dB L
Aeq,5s
, which approximately corresponds to
the level of fountain sound at close distance and the level
of the road traffic noise at 20 30 m from the road (cf.
Table 1). Two sets of experimental sounds were created.
Both sets contained (a) 12 singular target sounds, from
37 to 81 dB L
Aeq,5s
in 4 dB steps, (b) 15 combined
sound composed of the masker sound at 65 dB L
Aeq,5s
mixed with target sounds from 41 69 dB L
Aeq,5s
in 2 dB
steps, and (c) 5 singular masker sounds at 65 dB L
Aeq,5s
,
in total 32 sounds. The first set was assessed for road
traffic loudness and had varying levels of road-traffic
noise (target) and a constant level of the fountain sound
(masker). The second set was assessed for fountain
loudness and had varying levels of fountain sound (target)
and a constant level of road traffic noise (masker).
Figure 4 shows 1 /3-octave-band spectra (left) and
time-histories (right) of the singular road-traffic noise
(grey line), the singular fountain sound (blue line) and
combined road traffic and fountain sound (red line). As
expected, road traffic noise had more energy in the
low-frequency part of the spectrum than the fountain
sound, as seen in the left diagram. The 1 /3-octave-band
centred at 63 Hz had the highest level for road traffic
noise whereas the band centred at 4000 Hz band had the
highest level for the fountain sound. The spectrum of the
combined sound was determined by the road traffic noise
below 1500 Hz, and by fountain sound above 2000 Hz.
The right diagram of Fig. 4 shows that the sounds were
fairly continuous over time, with a variation of less than
5dBL
pA
.
4.2 Procedure
The experiment consisted of eight listening sessions,
separated with a short pause. In each of the sessions,
one set of experimental sounds was presented in a
random order. The sounds were assessed for road traffic
loudness in four sessions and for fountain loudness in
the other four sessions. Half of the listeners started
with assessing road traffic loudness followed by
fountain loudness whereas the others assessed the
sources in the reverse order. A training session was
conducted before the first session. The scaling instruc-
tion and the equipments were the same as in Experi-
ment 1. The experiment took approximately
30 minutes to complete.
4.3 Participants
Sixteen university students participated in Experi-
ment 2 (11 women and 5 men, mean age= 27 years).
A-weighted sound
pressure level, L
pA
(dB)
Time (s)
0
10
20
30
40
50
60
70
8
0
25
50
100
200
400
800
1600
3150
6300
12500
1/3-octave-band center frequency (Hz)
1/3-octave-band sound
pressure level, L
p
(dB)
55
60
65
70
75
01234
5
Time (s)
Combined road traffic and fountain sound
Road traffic noise
Fountain sound
A-weighted sound
pressure level, L
pA
(dB)
Time (s)
0
10
20
30
40
50
60
70
8
0
25
50
100
200
400
800
1600
3150
6300
12500
1/3-octave-band center frequency (Hz)
1/3-octave-band sound
pressure level, L
p
(dB)
55
60
65
70
75
01234
5
Time (s)
Combined road traffic and fountain sound
Road traffic noise
Fountain sound
Fig. 4—1 / 3-octave-band spectra (left) and time histories (right) of three experimental sounds used in
Experiment 2: Singular fountain sound (blue line) and singular road traffic noise (grey line),
both at 65 dB L
Aeq,5s
, and the two sounds combined (red line).
528 Noise Control Eng. J. 58 (5), Sept-Oct 2010
The participant’s hearing status was measured using an
audiometer (Interacoustics Diagnostic Audiometer
AD226, Hughson-Westlake method). All participants had
hearing threshold lower than 25 dB in their best ear for all
tested frequencies (0.125, 0.5, 1, 2, 3, 4, and 6 kHz).
5 EXPERIMENT 2: RESULTS
Visual inspection of the individual results revealed
that one listener had misunderstood the instruction and
assessed overall loudness rather than source-specific
loudness. Data from this listener was therefore
excluded from all analysis. The remaining 15
individual scales showed a similar trend, and the
Pearson’s coefficients of correlation between the scales
were found to be high, 0.89–0.99 mean= 0.94 for
fountain loudness and 0.85–0.98 mean=0.94 for traffic
loudness. It was therefore justified to include data from
the remaining 15 participants in the group analyses
reported below. Group scales were calculated in the same
way as for Experiment 1 (see Sec. 3).
Figure 5 shows perceived loudness (group scale) of
road traffic noise (left panel) and fountain sound (right
panel) as a function of the sound pressure level of the
target sound. Open symbols refer to singular sounds
(target only) and filled symbols refer to the target sound
combined with 65 dB masking sound target+masker.
The dotted vertical line indicates 0 dB signal-to-noise
ratio. The curved solid line shows a second order polyno-
mial fitted to the loudness data of the singular sound (least
square fit).
For both the road traffic noise (left) and the fountain
sound (right), the loudness was reduced below 55 dB
corresponding to a signal-to-noise ratio of −10 dB or less.
At higher levels, the target sound was approximately
equally loud heard alone (open circles) as together with
the 65 dB masking sound. The degree of masking was
much smaller for road traffic loudness than for fountain
loudness, as seen by the shorter distance between filled
and open circles in the left compared to the right diagram.
That is, road traffic noise masked the fountain sound more
than the other way around.
In order to quantify the masking effect, we calcu-
lated the level difference between the target sound
heard alone and an equally loud target sound heard
together with the 65 dB masking sound. This difference
corresponds to the horizontal distance between a filled
circle (masked sound) and the fitted curve representing
the loudness of the target alone sound. For road traffic
loudness, the level differences were moderate, ranging
form 6 to 1 dB. For fountain loudness, the differences
were larger, from 15 to 0 dB.
Figure 6 shows predictions from Glasberg and
Moore’s model of partial masking
11
, plotted in the
same way as for the empirical loudness data in Fig. 5.
As for the experiment (Fig. 5), the model (Fig. 6)
predicted that road traffic noise masked fountain sound
more than vice versa. However, for both sources, the
predicted masking effect was much larger than in the
experiment, as seen by the large distance between
masked loudness (filled circles) and target alone
loudness (fitted curve). We calculated the level differ-
ence between a masked sound and an equally loud
target alone sound, in the same way as described above.
For road traffic loudness, the predicted level differ-
ences ranged between −28 and 6 dB, for fountain
loudness, it ranged between 28 and 10 dB. Thus, the
model predicted a considerably larger masking effect than
obtained in the experiment, on average 11 dB greater for
0.6
0.9
1.2
1.5
1.8
2.1
30 40 50 60 70 80 90
Road traffic noise alone
Road traffic with
65 dB fountain sound
Percieved loudness of road traffic noise
(magnitude estimate, log units)
Sound pressure level of road traffic noise, L
Ae
q,
5s
(dB)
Road traffic loudness
0.6
0.9
1.2
1.5
1.8
2.1
30 40 50 60 70 80 9
0
Sound pressure level of fountain sound, L
Aeq,5s
(dB)
Percieved loudness of fountain soun
d
(magnitude estimate, log units)
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Fountain loudness
0.6
0.9
1.2
1.5
1.8
2.1
30 40 50 60 70 80 90
Road traffic noise alone
Road traffic with
65 dB fountain sound
Road traffic noise alone
Road traffic with
65 dB fountain sound
Percieved loudness of road traffic noise
(magnitude estimate, log units)
Sound pressure level of road traffic noise, L
Ae
q,
5s
(dB)
Road traffic loudness
0.6
0.9
1.2
1.5
1.8
2.1
30 40 50 60 70 80 9
0
Sound pressure level of fountain sound, L
Aeq,5s
(dB)
Percieved loudness of fountain soun
d
(magnitude estimate, log units)
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Fountain loudness
Fig. 5—Perceived loudness (magnitude estimates, plotted on a log scale) of the target sound heard alone
or together with the masking sound, as a function of target sound pressure level. The masker
sound pressure level was always 65 dB L
Aeq,5s
(dotted vertical line, S/N=0 dB). Open circles
refer to target alone sounds and filled circles to combined target and masker sounds. Left panel:
road traffic noise as target and fountain sound as masker. Right panel: fountain sound as target
and road traffic noise as masker.
Noise Control Eng. J. 58 (5), Sept-Oct 2010 529
the road traffic noise and 12 dB greater for the fountain
sound.
6 DISCUSSION
The results of Experiment 1 showed that the fountain
sound reduced the loudness of road traffic noise close
to the fountain, and that the fountain sound was equally
loud or louder than the road traffic noise in a region
20 30 m around the fountain. This suggests that the
fountain sound added to the quality of the city park sound-
scape by reducing the loudness of the (presumably
unwanted) traffic noise. On the other hand, the results
from both experiments showed that fountain sound
masked road traffic noise less than road traffic noise
masked fountain sound. In addition, the results of Experi-
ment 2 showed that the amount of masking was consid-
erably less than expected from a model of energetic
masking. Thus, the present results illustrate possibilities as
well as limitations to the idea of masking road traffic noise
with fountain sound.
The results of Experiment 2 suggested that the level
of fountain sounds need to be at least 10 dB higher than
the road traffic noise in order to reduce its loudness. In
Experiment 1, road traffic noise was partially masked only
close to the fountain where the overall level of the sound-
scape was 5 10 dB higher with the fountain turned on
than turned off (cf. Table 1). Thus, the present results
suggest that a reduction of road traffic noise may be
achieved only in a region around the fountain where the
level of the fountain sound clearly exceeds the level of the
noise. This region would correspond to what Brown and
Rutherford called the zone of influence
5
, where the
loudness of the road traffic noise is reduced but the
noise is still audible. In neither experiment did the
fountain sound make the road traffic noise inaudible,
indicating that complete masking of road traffic noise,
a zone of exclusion
5
, might not easily be achieved in
city parks close to main roads. It would at least require
that architects and planners take into consideration how
the fountain is perceived at various places in the park.
For instance, it is probably more effective from a
soundscape perspective to place the fountain between
the road and the park, rather than in the center of the
park, as in the present case study.
The asymmetry in perceived masking between road
traffic and fountain sound found in both experiments
was not surprising, given the larger proportion
low-frequency sound in traffic noise compared to
fountain sound. It is well known that low-frequency
sounds are harder to mask than high frequency sounds
due to energetic masking
7
. However, the amount of
masking found in the present study was less than
expected from the current knowledge of energetic
masking as it is summarized by Glasberg and Moore’s
model
11
. This finding agrees with Bolin et al.
10
,who
found that existing models overestimated the ability of
natural sounds to mask noise, using sounds from
vegetation and sea waves to mask wind turbine noise.
Thus, the present results, as well as Bolin et al.
10
,
suggest that other factors than energetic masking influ-
ences masking of environmental sounds. A plausible
mechanism would be that target and maskers sounds
are confused and that part of the masking sound is
incorrectly perceived as part of the target sound (i.e.,
informational masking due to target-masker similar-
ity). This would lead to a smaller masking effect than
expected from energetic masking only. The present
results suggest that such an effect was present for both
sources, since the loudness of both the fountain sound
and the road traffic noise was underestimated by the
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Fountain loudness
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Sound pressure level of fountain sound, L
Aeq,5s
(dB)
Predicted loudness of fountain soun
d
(sone, log units)
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Road traffic loudness
Road traffic noise alone
Road traffic with
65 dB fountain sound
Pre
d
icte
dl
ou
d
ness o
f
roa
d
tra
ff
ic
noise (sone, log units)
Sound pressure level of road traffic noise, L
Aeq,5s
(dB)
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Fountain loudness
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Sound pressure level of fountain sound, L
Aeq,5s
(dB)
Predicted loudness of fountain soun
d
(sone, log units)
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Fountain loudness
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Fountain sound alone
Fountain sound with
65 dB road traffic noise
Sound pressure level of fountain sound, L
Aeq,5s
(dB)
Predicted loudness of fountain soun
d
(sone, log units)
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Road traffic loudness
Road traffic noise alone
Road traffic with
65 dB fountain sound
Pre
d
icte
dl
ou
d
ness o
f
roa
d
tra
ff
ic
noise (sone, log units)
Sound pressure level of road traffic noise, L
Aeq,5s
(dB)
-2.2
-1.6
-1.0
-0.4
0.2
0.8
1.4
2.0
30 40 50 60 70 80 90
Road traffic loudness
Road traffic noise alone
Road traffic with
65 dB fountain sound
Road traffic noise alone
Road traffic with
65 dB fountain sound
Pre
d
icte
dl
ou
d
ness o
f
roa
d
tra
ff
ic
noise (sone, log units)
Sound pressure level of road traffic noise, L
Aeq,5s
(dB)
Fig. 6—Predicted loudness (sone, plotted on a log scale) of the target sound heard alone or together with
the masking sound, as a function of target sound pressure level. The masker sound pressure level
was always 65 dB L
Aeq,5s
(dotted vertical line, S/N=0 dB). Open circles refer to target alone
sounds and filled circles to combined target and masker sounds. Left panel: road traffic noise as
target and fountain sound as masker. Right panel: fountain sound as target and road traffic noise
as masker.
530 Noise Control Eng. J. 58 (5), Sept-Oct 2010
loudness model. It may be speculated that this result
reflects a general tendency to attribute sounds to the
source that are at the focus of the perceiver’s attention,
at least in cases of uncertainty due to target-masker
similarity. If so, a strategy for soundscape improvement
might be to design wanted sounds that attract attention.
This would of course require further research into
factors that governs auditory attention in outdoor
soundscapes and how attention affects soundscape
perception.
The present result needs to be replicated, using a
larger set of wanted and unwanted environmental
sounds. The experiments were based on recordings in
an inner city park heavily exposed to road traffic noise
at close distance. It may be easier to mask noise in
locations with lower levels of noise exposure, for
example, rural areas exposed to steady state distant
road traffic noise, In such areas, the temporal variabil-
ity and overall level of the noise is lower than in city
parks, factors which may facilitate masking by natural
sounds.
The listeners in our experiments were young univer-
sity students that may not be representative of the
typical population of city park visitors. However, the
task was to assess perceived loudness, which is a basic
auditory attribute that, apart from hearing status, is not
strongly influenced by personal factors. We therefore
believe that similar results would have been obtained
with a more representative group of listeners
Finally, it should be stressed that the present experi-
ments did not measure evaluative auditory dimensions
such as overall soundscape quality or noise annoyance.
Adding wanted sounds may reduce the loudness of
unwanted sounds, but to the prize of increasing the
overall loudness of the soundscape. This may interfere
with possibilities for rest and relaxation and thereby
decrease the quality of the soundscape. An important
task for future soundscape research is therefore to
clarify in which situations the addition of sounds may
improve the overall soundscape and in which situations
it may not.
7 CONCLUSIONS
This study shows both possibilities and limitations
to the idea of masking unwanted road traffic noise with
wanted sounds from a city park fountain. Positive
effects can be achieved, but they may be less than
expected from the overall level and spectrum of the
sounds, possibly due to target-masker confusion.
8 ACKNOWLEDGMENTS
This research was sponsored by research grants from
the Swedish Research Council, the Swedish Research
Council for Environment, Agricultural Sciences and
Spatial Planning, and the Knowledge Foundation.
9 REFERENCES
1. C. Lavandier and B. Defréville, “The contribution of sound
source characteristics in the assessment of urban soundscapes”,
Acta. Acust. Acust., 92, 912–921, (2006).
2. M. E. Nilsson and B. Berglund, “Soundscape quality in subur-
ban green areas and city parks”, Acta. Acust. Acust., 92, 903–
911, (2006).
3. G. Perkins, “The delight of a city: Water”, Concrete Quality, 99,
33, (1973).
4. N. K. Booth, Basic Elements of Landscape Architectural De-
sign, Elsevier, New York, (1983).
5. A. L. Brown and S. Rutherford, “Using the sound of water in the
city”, Landscape Australia, 2, 103–107, (1994).
6. A. L. Brown and A. Muhar, “An approach to the acoustic design
of outdoor space”, J. Environ. Plann. Manage., 47, 827–842,
(2004).
7. B. C. J. Moore, “Frequency analysis and masking”, Hearing,
edited by B. C. J. Moore, Academic Press, London, pp. 161–
205, (1995).
8. N. I. Durlach, C. R. Mason, G. Kidd Jr., T. L. Arbogast, H. S.
Colburn and B. G. Shinn-Cunningham, “Note on informational
masking”, J. Acoust. Soc. Am., 113, 2984–2987, (2003).
9. C. S. Watson, “Some comments on informational masking”,
Acta. Acust. Acust., 91, 502–512, (2005).
10. K. Bolin, M. E. Nilsson and S. Khan, “The Potential of Natural
Sounds to Mask Wind Turbine Noise”, Acta Acustica united
with Acustica, 96, 131–137, (2010).
11. B. R. Glasberg and B. C. J. Moore, “Development and evalua-
tion of a model for predicting the audibility of time-varying
sounds in the presence of background sounds”, J. Audio Eng.
Soc., 53, 906–918, (2005).
12. M. E. Nilsson, “A-weighted sound pressure level as an indicator
of perceived loudness and annoyance of road-traffic sound”, J.
Sound Vibr., 302, 197–207, (2007).
13. G. A. Gescheider, Psychophysics: The Fundamentals, Third
Edition, Lawrence Erlbaum Associates, London, (1997).
14. H. L. Lane, A. C. Catania and S. S. Stevens, “Voice level: Auto-
phonic scale, perceived loudness and effects of sidetone”, J.
Acoust. Soc. Am., 33, 160–167, (1961).
15. E. P. A. Swedish, Vägtrafikbuller. Nordisk beräkningsmodell, re-
viderad 1996 [Road-traffic Noise. The Nordic Calculation
Method, revised 1996], Swedish Environmental Protection
Agency, (1996).
Noise Control Eng. J. 58 (5), Sept-Oct 2010 531
... Introducing additional background sounds in the noise-polluted sound environment would lead to even higher SPL. Despite that, certain background sounds seem to have a positive influence on the perception of the soundscape [49][50][51][52][53][54]. Relatively pleasant background sounds are shown to be associated with increased acoustic comfort [10] and decreased noise annoyance [54]. ...
... Background sounds might improve the acoustic quality of urban noisy soundscape [49,50,52,53]. For example, natural water features in urban environments were reported to reduce the loudness of road traffic noise [50,53] and of wind turbines [49]. ...
... Background sounds might improve the acoustic quality of urban noisy soundscape [49,50,52,53]. For example, natural water features in urban environments were reported to reduce the loudness of road traffic noise [50,53] and of wind turbines [49]. They were further reported to reduce annoyance from the road traffic or wind turbines [49,52]. ...
Conference Paper
Full-text available
Continuous urban densification exacerbates acoustic challenges for residents of housing complexes. They are confronted with higher noise immission from railway, road traffic, construction, as well as louder neighborhood acoustic environments. Thereby, not only noise immission indoors is associated with stress, annoyance, and sleep disturbance, but also the immediate outdoor living environment (e.g., courtyards, private gardens and playgrounds, etc.) can be acoustically unpleasant and annoying. This non-exhaustive narrative review paper elaborates on the role of a number of design parameters on improving the quality of the outdoor soundscape of housing complexes: architectural and morphological design, facade material characteristics, balconies, greenery, ground, background sounds, and several factors concerning quality of sounds (e.g., multisensory perception, holistic design, the relevance of space, context, social factors, co-creation, etc.). It mainly covers literature including both acoustical (e.g., sound pressure level and room acoustical parameters) and human/perceptual (e.g., comfort and annoyance) factors. A series of recommendations are presented here as to how the semi-enclosed outdoor spaces in the proximity of residential complexes can be acoustically improved.
... In humans, masking effects have been exploited in open-plan offices to reduce intelligibility of background speech by playing sound (Hongisto et al., 2017;. Similarly, fountain sound has been shown to reduce perceived loudness of traffic noise (Coensel et al., 2011;Nilsson et al., 2010). For non-human animals, it has also been suggested to elevate ambient noise levels in zoo exhibits in order to decrease the signal-to-noise ratio (SNR) of potentially disturbing sounds from visitors . ...
... An * indicates the best model. recognition thresholds in fi sh increase under higher background levels and perceived loudness of traffi c noise reduced with the playback of fountain sound in humans (Coensel et al., 2011;Nilsson et al., 2010), further studies to SNR using larger ranges of signal levels and SNRs are warranted. It may be most fruitful to compare the explanatory value of signal level and SNR in an experimental design and with a study species that has already revealed level dependent responses. ...
Thesis
Full-text available
Anthropogenic noise has been shown to affect marine animals in various ways, this may have fitness consequences at individual and population level. This thesis aims to increase insight into the quantification of sound-induced behavioural responses that are relevant to fitness, and into factors that modulate the responses. I addressed both knowledge gaps using captive and field studies on marine animals from multiple trophic levels. For the quantification of behavioural responses relevant to fitness, I examined the changes in time budgets of Atlantic cod in a net pen and basin in response to sound (chapter 2 and 3). To increase insight into factors that modulate sound impact, I examined the effect of various acoustic characteristics of sound stimuli and the environment on European seabass (chapter 4), the interaction between foraging shore crabs and common shrimps during noise (chapter 6), the cross-sensory interference by noise in foraging crabs (chapter 7), and habituation to repeated sound exposures by blue mussels (chapter 8). Future studies are needed to be able to link changes in time budgets to changes in energy budgets, and consequently to fitness. Additionally, studies into the factors that modulate the effects of sound are needed to fully understand the impact of sound.
... These results depend, however, on the type of music played and the preferences [80] and implications of the listeners [81]. All this research led to the conclusion that (because normally the students themselves decide when and what kind of music to listen to) music can be seen as a "wanted sound" [82], and it is hardly considered a background disturbance. ...
Article
Full-text available
The acoustic environment has been pointed out as a possible distractor during student activities in the online academic modality; however, it has not been specifically studied, nor has it been studied in relation to parameters frequently used in academic-quality evaluations. The objective of this study is to characterize the acoustic environment and relate it to students’ satisfaction with the online learning modality. For that, three artificial neural networks were calculated, using as target variables the students’ satisfaction and the noise interference with autonomous and synchronous activities, using acoustic variables as predictors. The data were obtained during the COVID-19 lockdown, through an online survey addressed to the students of the Universidad de Las Américas (Quito, Ecuador). Results show that the noise interference with comprehensive reading or with making exams and that the frequency of noises, which made the students lose track of the lesson, were relevant factors for students’ satisfaction. The perceived loudness also had a remarkable influence on engaging in autonomous and synchronous activities. The performance of the models on students’ satisfaction and on the noise interference with autonomous and synchronous activities was satisfactory given that it was built only with acoustic variables, with correlation coefficients of 0.567, 0.853, and 0.865, respectively.
... In terms of visual elements, this study found that paved ground, buildings, sky, water, natural terrain, and pedestrians and animals were effective landscape elements influencing the soundscape evaluation parameters. Unlike the sound of fountains, this study found that water sounds from rivers have little effect on the SPL in WSMCs [53]. The presence of water can still cause a sense of visual tranquility and improve the comfort of the soundscape [14], but the visual element of the water accounted for only 0.1%-7.2% in the studied WSMCs. ...
Article
Full-text available
The soundscape of waterfront space in mountainous cities (WSMC) can affect people’s physical and mental health. Taking seven WSMCs in Chongqing, China, as the study area, this study aimed to investigate the soundscape and explore the influence of spatial characteristics and visual and smell environments on the soundscape of WSMCs through a sensewalking approach. The results show that the soundscape evaluations of WSMCs are of poor quality, and traffic sounds are dominant (33%). Among spatial characteristics, the position relative to the road (including vertical and horizontal distances) had a greater impact than other spatial indicators on soundscape evaluations. Elevation was positively correlated with the A-weighted equivalent sound level (LAeq) and negatively correlated with the soundscape comfort degree (SCD). In terms of visual elements, the proportions of paved ground, pedestrians, and buildings had negative effects on the soundscape, while those of the sky, water, and natural terrain had positive effects. High visual and smell environment quality can enhance soundscape evaluations, although the smell environment had a greater impact on the SCD than the visual environment in WSMCs. Finally, this study summarizes the recommended values of spatial characteristics and visual and smell environment indicators to put forward references for the soundscape design of WSMCs.
... When the helicopter sounds cannot be heard, also a higher number of participants give negative ratings to the "artificial" sound sources (traffic, aircraft, and engine noises), but positive ratings to the others (humans, animals, wind, and other noises) (≥50% for all the sound sources). For this last condition (WOH), although most people give negative or neutral ratings to the artificial sounds, the soundscape is considered pleasant by a high percentage of participants, which indicates that, for them, these "not wanted" sounds [50] do not influence the overall rating of the soundscape. Although the landscape features did not change for the scenarios with and without the helicopter noise, for the scenarios WOH, 88.46% gave positive appraisals of the landscape quality, and for scenarios WH, only 50% did so. ...
Article
Full-text available
Heliports are facilities that play a fundamental role in security and emergency operations. Since rotorcrafts do not need much space for take-off and landing, heliports are normally immersed in the urban fabric of our cities. However, they generate high noise levels, which can cause a nuisance, especially in outdoor areas intended for the recreation of citizens. This paper studies how helicopter noise affects the perception of the soundscape appropriateness and landscape quality in the vicinity of a heliport located in an urban park, using semantic differential scales and appraisals on the noise sources. The study area was the “Parque del Bicentenario” in Quito, Ecuador. Immersive Virtual Reality (IVR) laboratory tests using 360-degree videos and spatial audio were preferred to on-site questionnaires, given the difficulty of predicting when helicopter noise events would occur. For the statistical analysis, objective acoustic and psychoacoustic parameters have also been considered. Results show that the soundscape is perceived as more pleasant and less chaotic when there is no helicopter noise. Furthermore, with the same visual stimuli, the appraisals of the landscape are much better in the scenarios without the helicopter noise. Sharpness is the psychoacoustic parameter that best explains the variance of the subjective variables evaluated.
... Por otro lado, el sonido del agua modifica el Ambiente Acústico y puede enmascarar parcial o totalmente a los ruidos indeseados, especialmente el proveniente del tráfico. La extensión del enmascaramiento depende de las frecuencias y energía emitidas por el agua cayendo o fluyendo, en relación a las características del ruido a enmascarar (Nilsson et al., 2010). A fin de cuantificar la medida en que los sonidos naturales son percibidos en relación al ruido vehicular escuchado en las ciudades, en 2018 se propuso el Índice Verde del Paisaje Sonoro (Green Soundscape Index -GSI), el que se define como el balance percibido entre la presencia de sonidos naturales y la presencia de ruido de tráfico. ...
Article
Full-text available
El paradigma del Paisaje Sonoro considera al sonido como un recurso que puede ser gestionado, lo que abre las puertas a la optimización del sonido en el territorio. Esta gestión no sólo implica mitigar el ruido, sino que también promover aquellas fuentes sonoras positivas para la sociedad, el ambiente, la salud pública y la cultura. El Paisaje Sonoro representa un sistema complejo y dinámico compuesto de una multiplicidad de elementos interrelacionados. Estos elementos competen a distintos dominios del conocimiento y responden a diferentes escalas de tiempo y espacio. Este artículo sintetiza los fundamentos del paradigma del Paisaje Sonoro, presenta un Modelo Conceptual del Paisaje Sonoro que facilita su operacionalización para la investigación y discute criterios para la gestión de paisajes sonoros saludables en áreas verdes urbanas.
... Literature review informed an initial equivalent continuous sound pressure level (L eq ) threshold below 50 dBA, as measured with slow response time during the period of interest. At times, a higher L eq may be acceptable, if the value results derive from natural sound sources (e.g., water features) and mask technological or other anthropogenic noise (Hong and Jeon, 2012;Jeon et al., 2010;Nilsson et al., 2010). To assess whether a L eq exceeds 50 dBA due to natural sound sources alone, it should be measured without the presence of human and technological sound sources. ...
Article
Urban greenspace soundscapes can contribute to the restorative effects that nature provides for the psychological and emotional health of people when certain conditions are met. The main objective of this paper is to propose practical criteria to help planners and managers in the design, development and preservation of urban greenspaces whose soundscapes may contribute to the renewal of health. Systematic literature review informed a conceptual potential Health Restoration Soundscapes (HeReS) model, based on five conditions: (1) Naturalness, (2) Sound Levels, (3) Perceived Sound Sources, (4) Soundscape Assessment, and (5) Sensescape Coherence and proposed Health Restoration Soundscapes Criteria (HeReS-C), for HeReS evaluation in urban green areas. The HeReS-C were applied in 21 sites in Argentina, Sweden, and Chile. General results are provided for all 21 sites, along with three in-depth profiles of HeReS-C applications that provide case studies across a range of resulting HeReS-C scenarios, including sites that meet the HeReS-C criteria, those that do not, and sites that could qualify in the future, if appropriate management measures are taken. HeReS-C showed to be a promising tool for the recognition of potential health-restoring soundscapes in urban greenspaces; informing their design and management to favor the well-being and health of the population.
... According to the Environmental Quality Standard for Noise (GB3096-2008; Ministry of Environmental Protection of the People's Republic of China 2008), the urban and rural sound environment is divided into five classes, and the first class for psychological restoration and recuperation was ranked by quietest areas (40 dBA night -50 dBA day ), the second class for the next quietest village community (45-55), the third class for the residential and country fair village (50-60), the fourth class for the village on manufacturing industry (55-65), and the fifth class for the village next to a main traffic line (60-70). With regard to planning based on the choice of acoustic rurality, all kinds of mechanical noise sources should be controlled and a quiet and tranquil countryside and "hi-fi" rural soundscapes should be reconstructed by masking traffic noise with water sounds (Nilsson et al. 2010). ...
Article
Full-text available
Although rurality is regarded as core terminology in rural geography and an essential characteristic of rural and rural tourism, researchers have not attached enough academic importance to the hybridity and multisensory characteristics of the rural, including its soundscapes. From the perspective of history and culture, the ancient Chinese were obsessed with the geomantic conception of the harmonious coexistence of man and nature in their rural construction, and Chinese pastoral poetry covered the harmonious soundscape symphony of natural ecology and rural community. Acoustic rurality can be defined as sustainable rural soundscapes in the changed and changing human–environment contexts comprising quiet and tranquility; wild, domestic, and social soundscapes; and the rural soundscapes as important indicators of good rural ecological environment and traditional rural heritages that can be preserved and developed through acoustic rurality-based planning. Using the practical roadmaps of China’s Beautiful Rural Construction and Rural Vitalization Strategy for reference, this study sums up the four proposed guidelines for conserving and developing acoustic rurality: noise control and protecting the quiet and tranquil countryside, conserving wildlife habitat of the rural wild soundscapes, safeguarding cultural soundscape heritages, and developing recreational soundscapes for rural tourism.
Article
Incorporating pleasant sounds into traffic noises is an important design strategy to optimize noise perception. However, as the previous studies based on the auditory masking method mainly focused on road traffic or aircraft noises, there is a lack of research on alleviating the negative perceptions due to metro noise by adding other sounds. Accordingly, this study analyzed the regulation mechanisms of four specific water sounds (fountain, stream, water-drop and waterfall sounds) on the dissatisfaction due to a specific metro noise and established the multivariate models to predict the dissatisfaction level due to combined metro-water sounds. Seventy-nine subjects participated in the experiment and were exposed to a series of acoustic samples before being asked to cast their negative perception votes. The results suggested that the dissatisfaction with metro noise could be improved by adding the four types of water sounds, among which the capability of water-drop sound was the strongest, followed by the fountain and stream sounds, and the waterfall sound was the least effective. Besides, in order to reduce the dissatisfaction level at the global sound pressure levels (SPLs) of 60 and 65dBA, the SPL of metro noise should be no more than 3 dBA higher than that of water sound, and a water signal-to-noise ratio (WSNR) of 6 dBA was most desirable. Furthermore, among the considered models (energy summation model, independent effects model and energy difference model), the independent effects model, which fitted the dissatisfaction level data moderately, yielded the relatively highest coefficients of determination after one relevant acoustic factor (WSNR Threshold) and personality traits (gender and sensitivity) were added. It is worth noting that a single metro noise and a single sample for each type of water sound were selected and their combined sounds were studied, thus, this study could be considered as a preliminary work and the results and applicability have limitations.
Article
Waterscape has been found to have a positive impact on preference in public space. This study evaluated three fountains in Harbin, China, to explore whether their dynamic visual form and corresponding sound rhythm changes would affect the waterscapes’ sound preference evaluation. In total, 150 visitors were selected to answer a questionnaire on-site regarding the fountain’s perception, including its visual and acoustic environment. This field experiment revealed that people have different preferences for the sound of waterscapes. Each waterscape was then classified and subjectively rated for its visual and auditory aspects in a laboratory experiment. The results showed that there was little difference in the rating of water rhythm when there was no visual stimulus. However, participants preferred a dynamic visual form with distinct rhythm changes to a continuous steady-state form. The higher the score of the visual form, the better the rating of the waterscape. In this study, a significant positive correlation was found between the dynamic visual form of fountains and the preference for waterscapes. When adding music to a fountain, combining the continuous steady-state fountain with light music improved the evaluation of the waterscape; furthermore, the combination of the dynamic fountain and strong rhythm music was more popular among the participants. In general, the evaluation of a waterscape is affected by its form, environment, and music.
Article
Full-text available
Throughout history, fountains, artificial waterfalls, flowing pools and other water-structures have been used primarily for their aesthetic value in the built environment. To a large extent, it is the visual attributes of water structures that have made them so popular, but they also contribute to the stimulation of other senses. The sound that moving water makes is an important component of the application of water structures in parks, gardens and meeting place of the inner city. The sound of water tumbling, or splashing, is regarded, presumably universally, as a pleasant sensation - the sound of breaking waves on a beach or the babbling stream, for example. But, of commensurate importance, the same sounds have the potential to mask unwanted sounds - road traffic, construction, aircraft, trains, amplified music or ventilation systems - which dominate most central business districts and which. equally universally, would be regarded as undesirable, if not unpleasant.
Article
Full-text available
Informational masking (IM) has a long history and is currently receiving considerable attention. Nevertheless, there is no clear and generally accepted picture of how IM should be defined, and once defined, explained. In this letter, consideration is given to the problems of defining IM and specifying research that is needed to better understand and model IM.
Article
Full-text available
According to guidelines proposed in Sweden, at least 80% of the visitors in quiet areas should perceive the sound environment as good. This was the starting point for a questionnaire study on "soundscape quality" in four suburban green areas and in four city parks. The soundscapes in the suburban areas were completely dominated by sounds from nature (e.g., bird song and sounds from water), whereas traffic noise was a main component of the city-park soundscapes. Measured equivalent sound levels (from all sources) ranged from 42 to 50 dBA in the suburban green areas, and from 49 to 60 dBA in the city parks (LAeq, 15min). "Soundscape quality" was assessed by a five-point bipolar category scale. Among the respondents, 84-100% in the suburban green areas and 53-65% in the city parks assessed the soundscape as "Good" or "Very good". Thus, all suburban green areas but none of the city parks reached the stipulated goal (at least 80%). The soundcape quality was confirmed by attribute profiling using a set of 12 adjectives. Based on the visitor's responses, it is concluded that good soundscape quality can only be achieved if the traffic noise exposure in suburban green areas and city parks during day time is below 50 dBA.
Article
Full-text available
While informational masking (IM) has been investigated for almost a half century, only recently have there been efforts to develop a principled definition of this class of interference effects among sensory stimuli. This paper briefly reviews the history of IM and discusses some recent efforts toward a definition. Some experiments with tonal patterns are then described that demonstrate close associations between the effects of IM on detection and on discrimination. It is proposed that the varieties of IM revealed in recent research may not all be reasonably attributed to a single explanatory mechanism, even a fairly complex one. At the least, IM effects associated with signal-masker similarity (S) are readily distinguished from those resulting from trial-to-trial stimulus uncertainty (U). A corresponding distinction may usefully be made in definitions and models, dealing separately with "S" and "U" types of IM.
Article
Full-text available
The aim of this research is to characterize the appraisal of urban soundscapes where sound sources are explicitly recognized. A series of three experiments is conducted in a laboratory where subjects listen to twenty 15-s sound samples representing a sound environment along a classical street in Paris. In these samples, listeners can recognize cars, mopeds, motorbikes, buses, birds and human voices. The first experiment collects ratings of the subjective descriptors "prominence, presence and proximity" of sound sources, the second and third respectively obtain assessments of the overall hedonic judgment and of the loudness of the sound samples. Physical parameters of the different sound sources are extracted from the coded LAeq curves. Multiple regressions provide a good summary of the relationship between appraisal and subjective descriptors or objective parameters. They show that, by adding the information about sound source characteristics to the perceived loudness or to the Zwicker's Loudness, the percentage of explained variance increases. To investigate the appraisal of other typical urban soundscapes such as market and park, an on-site experiment using the same procedure is carried out during an urban walk divided into sixteen 90-s sequences. Again the percentage of the explained variance of the hedonic judgement is increased by taking into account the sound source characteristics. The prediction of the scale unpleasantness can even be effective based only on objective characteristics of sound sources such as the number of sources or their time ratio of presence. These results are discussed in terms of sound "events" compared to ambient sound.
Article
A model for predicting the audibility of time-varying signals in background sounds is described. The model requires the calculation of time-varying excitation patterns for the signal and background, using the methods described elsewhere. A quantity called instantaneous partial loudness (IPL) is calculated from the excitation patterns. The estimates of IPL, which are updated every 1 ms, are used to calculate the short-term partial loudness (STPL) using a form of running average similar to an automatic gain control system. It is assumed that the audibility of the signal is monotonically related to the average value of the STPL over the duration of the signal. In experiment 1 thresholds were measured for detecting a 1-kHz sinusoid in four different samples each of white and pink "frozen" noise. The results were used to determine the average value of the STPL required for threshold. In experiment 2 the model was evaluated by measuring detection thresholds for nine signal types in six backgrounds (54 combinations), using a two-alternative forced-choice task. The backgrounds were chosen to be relatively steady (such as traffic noise). The correlation between the measured masked thresholds and those predicted by the model was 0.94. The root-meansquare difference between the thresholds obtained and those predicted was 3 dB. In experiment 3 psychometric functions were measured for the detection of five signals in five backgrounds (five pairs), using a two-alternative forced-choice task. Experiment 4 used the same signals and backgrounds, but psychometric functions were measured using a singleinterval yes-no task. The results of experiments 3 and 4 were used to construct functions relating signal detectability d' to the average value of the STPL.
Article
Wind turbine (WT) noise may cause annoyance, especially in relatively quiet areas with low ambient levels. As a compliment to conventional noise control at the source, addition of wanted sounds may reduce the loudness of WT noise by auditory masking. In order to test this, two masking experiments were conducted with two WT noises as target sounds and three natural sounds as maskers (wind in coniferous or deciduous trees and sea waves). In the first experiment, 30 listeners determined the detection thresholds of WT noise in the presence of the natural sounds using a threshold tracking method. In the second experiment, the same group of listeners matched the loudness of partially masked WT noise with the loudness of unmasked WT noise. The results showed that detection thresholds for WT-noise in the presence of natural sounds from trees and sea waves were around −8 to −12 dB S/N-ratio. Furthermore, a reduction of perceived loudness of WT-noise was found for S/N-ratios up to 2 dB. These results were compared with predictions from two models of partial masking (steady and time variant). In general, empirically determined detection thresholds and partial loudness matches were higher than predictions from the two models.
Article
Two listening experiments were conducted in order to determine whether A-weighting is a valid indicator of the perceived loudness or annoyance of road-traffic sound. Because A-weighting has been criticized for not properly integrating energy at low frequencies, experimental road-traffic sounds were selected with a wide range in low-frequency content, assessed as the difference between C- and A-weighted sound pressure levels (LC−A). In the first experiment, 30 listeners assessed the perceived loudness of the selected sounds. In the second experiment, another group of 31 listeners assessed the perceived annoyance of the same sounds. Sounds with high levels of LC−A were louder and more annoying than sounds with medium levels of LC−A, which in turn were louder and more annoying than sounds with low levels of LC−A, at similar A-weighted sound pressure levels (LA). It was estimated that the change in perceived loudness or annoyance associated with a 1 dB change in LC−A would correspond to approximately a 0.4 dB change in LA. In contrast, sounds with similar Zwicker loudness levels (LN) were approximately equal in loudness and annoyance irrespective of their LC−A. Thus, LN was found to be superior to LA as an indicator of short-term loudness and annoyance of road-traffic sounds with wide variation in low-frequency content.