Limits of mixing background sounds to foreground sound samples in
psychoacoustic laboratory experiments on noise annoyance
Eduardo Pelizzari(1,2) and Armin Taghipour(1)(1) Empa, Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Acoustics/ Noise Control,Überlandstrasse 129, 8600 Dübendorf, Switzerland, email: armin.taghipour@empa.ch(2) Western Paraná State University (UNIOESTE), Cascavel-PR, Brazil

Abstract
A variety of noise annoyance investigations are conducted as laboratory experiments. To simulate a more naturaland realistic scene, it is preferable to add background ambient sound samples to the noise samples. However,possible effects of background sounds on annoyance from foreground sounds should be either minimized orquantiﬁed. A laboratory experiment was conducted, in which background ambient sound samples were mixed
to foreground helicopter noise samples. In a partially balanced incomplete block design, three factors werevaried: noise’s sound exposure level (six categories), background sound type (ﬁve categories), and backgroundsound pressure level (four categories). Each subject received 40 of the 78 stimuli. Annoyance to each individual
20-s stimulus was rated on the ICBEN 11-point numerical scale. It was investigated whether background soundtype and/or level affected annoyance. The major predictor of annoyance was helicopter’s sound exposure level.
Stimuli containing background sounds with dominant events were associated with higher annoyance ratings
than those with less dominant background events or with no background sounds. Increasing background level
accentuated the difference between annoyance from stimuli with eventful and less eventful background sounds.
Keywords: Noise annoyance, psychoacoustic experiments, background sounds

1

INTRODUCTION

Use of background sounds is beneﬁcial or, in cases, necessary in a variety of applications in the context oflaboratory noise (annoyance) research or virtual acoustics [1]. The following is a non-exhaustive list in thisregard [1]:• Synthetically generated noise samples in the context of virtual acoustics: it is possible to generate noise
synthetically by means of emission synthesizers using physical and/or parametric approaches [2, 3, 4, 5,
6, 7]. Adding recorded or synthesized (natural) background sounds to the noise samples helps to increase
the degree of realism of the auralization.
• Virtual sound propagation simulation: when propagation ﬁlters are used to simulate farther distances [5,8], recorded background sounds would also be sent to the target distance. Whereas in this case, only thesource is aimed to be sent to the target distance, the background sounds are actually supposed to remainclose to the observer. This problem can be solved with adding similar background sounds in the observer
position [8].
• Auralization of single-channel recordings: when noise is recorded by a calibrated single microphone, aslong as the exact momentary positions of the source and the observer are recorded as well, it would
be possible to auralize the movement of the source on a multi-loudspeaker system. In this case, however, background sounds contained in the original recording (e.g., birds) would incorrectly move with theforeground noise from one loudspeaker to the other. Since the background sound should commonly be
relatively static (with respect to its location), its movement with the noise could be extremely unrealistic
and irritating. This might be solved by adding static background sounds to the moving noise which could
partially mask the (moving) inherent background sound [8].

7673• Ambient sound design: when virtual urban scenes are designed or virtual sound walks are simulated, they
typically contain one or more background sound sources [9, 10]. It is assumed that sounds of waterfeatures, birds, or natural vegetation would improve the virtual living (or urban) environment [11, 12].
• Constant present background sounds in the laboratory experiments: in a psychoacoustic experiment on
acoustic comfort, sound pleasantness, or noise annoyance, stimuli are typically played back successively(i.e., one after the other). While the subjects are sitting in a lab, it is asked to imagine they would besitting in an ofﬁce, in the garden, in a wind park, at a street corner, or in other scenarios. Thereby,
typically no sounds of the imaginary environment—but rather silence—exists in-between the stimuli. It
would be much more realistic to have a background sound present in the room for the whole duration ofan experiment, from which each stimulus then arises into the foreground [1].
• Contained background sounds in the original noise recordings: although noise recordings are ideally carried out carefully such that they are free of dominant background sounds, still some sort of backgroundsounds are present in any natural or everyday environment. Hence, the recorded foreground sound samples
also contain some background sounds. In psychoacoustic experiments on acoustic comfort, pleasantness,or noise annoyance this introduces a possible source of error or bias, which should be controlled for [1].
The examples given above show the relevance/importance of background sounds in virtual audio and psychoacoustic applications. Whereas they justify the vast usage of background sounds in the respective contexts, only
a few studies investigated the effects they could have on the perception of the respective scenes.
A number of studies indicated that background sounds (e.g., singing birds, water features, etc.) might improve
the acoustic quality of the urban soundscape in presence of annoying noise sources [14, 13, 15, 12]. De Coensel et al. [14] and Nilsson et al. [13] reported that natural water features reduce the loudness of road trafﬁcnoise. Bolin et al. [15] suggested similar effects of water sounds with respect to wind turbines noise. It was
further reported that water features might reduce annoyance from the road trafﬁc or wind turbines [15, 12].
These reports show potential effects of background sounds on the perception of foreground sounds.
This paper reports a psychoacoustic experiment in which possible effects of the background sound on the annoyance to the foreground noise were investigated.

2

METHOD

2.1 Experimental concept
Short-term annoyance reactions to helicopter noise stimuli were investigated under laboratory conditions, withor without mix background sounds [1]. The observed annoyance ratings correspond to “short-term annoyance”[16, 8] or “psychoacoustic annoyance” [17]. The term “short-term” refers to the time period during and afteran acoustic stimulus’ playback and before the next stimulus is presented [10].
Stimuli were generated from ﬁeld recordings [8] of landing helicopters and from background ambient sounds.
Three independent variables, i.e., ﬂight event’s A-weighted sound exposure level, LAE,F , background sound type(i.e., eventful vs. less eventful), and background sound’s A-weighted equivalent continuous sound pressure level,
LAeq,B , were systematically varied to study their individual and combined associations with annoyance [1].
To avoid confusions between the foreground sound (i.e., helicopter noise) and the ambient background sound,in this article, “noise” and “sound” are repeatedly used for these two categories of sounds, respectively [1].
However, it should be noted that, in general, sounds are not to be labeled or prejudged as “noise” per se [18].
2.2 Listening test facility
The experiment was conducted in AuraLab, a listening test facility of the Empa (Swiss Federal Laboratories
for Materials Science and Technology), which has a separate listening and control room allowing for audiovisual supervision to comply with ethical requirements [10, 8]. AuraLab satisﬁes room acoustical requirements

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Water stream (L)Birds and vegetation (L)50

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Figure 1. LAF,B of the processed background signals as a function of time. E and L refer to eventful and lesseventful signals, respectively. LAeq,B = 41 dB(A) for all examples shown here.
for high-quality audio reproduction in terms of its background noise and reverberation time. The stimuli wereplayed back through one loudspeaker (KH 120 A, Georg Neumann GmbH, Berlin, Germany) at a distance of
2 m from the listening spot and 0° elevation (subject’s ear level) as well as two subwoofers (KH 805, Georg
Neumann GmbH, Berlin, Germany). The carpeted ﬂoor was covered with additional absorbers.
2.3 Stimuli
2.3.1 Recordings
The helicopter noise samples originated from ﬁeld recordings of helicopter landings at Grenchen Airport, Switzerland (ICAO code: LSZG) [8]. Single-channel audio recordings were performed by means of a series of microphones (B&K 4188, Brül & Kjær, Naerum, Denmark, and Nor 1227, Norsonic AS, Tranby, Norway) placed
4 m above the ground in the eastern side of the airport, on the left and right sides of the extension of the
runway [8]. The six recordings selected were from helicopter types A109, A119, AS35, and EC20, all of which
are categorized as light-weight civil helicopters (weight: 1.7-3.2 tons). Helicopter recordings were done at the
sampling frequency of 44.1 kHz and with 16 bit depth [1].
Single-channel recordings of ambient sound were done by means of a microphone (B&K 4006, Brül & Kjær,Naerum, Denmark) placed 2 m above the ground in and around the city of Dübendorf, Switzerland. Backgroundsound recordings were carried out at the sampling frequency of 48 kHz and 24 bit depth [1].
2.3.2 Signal processing and mixing
In addition to the six chosen helicopter noise samples, four background sound extracts were selected: twosounds with dominant events – i.e., a chiming church bell and singing birds (and vegetation) – and sounds withless dominant events – i.e., water stream and birds (and vegetation). Eventfulness in the context of this paper
is a measure of signal dynamics and refers to several single dominant events with relatively high energy whicharise from a rather low energy background [1]. On the contrary, less eventful sounds are sounds whose momentary sound pressure level do not vary extensively from their A-weighted equivalent continuous sound pressurelevel, LAeq,B [19]. The categorization of background sounds into eventful or less eventful was carried out qualitatively, as well as quantitatively (i.e., by means of intermittency ratio, IR [19] and “L10 − L90 ”). Figure 1 shows
LAF,B of the processed background sound signals as a function of time.

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A109, 78 dB(A)AS35, 76 dB(A)A119, 74 dB(A)EC20, 72 dB(A)EC20, 70 dB(A)A119, 68 dB(A)LAS (dB)

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Figure 2. LAS,F as a function of time for the six ﬂight events (no added background sounds). Helicopter type
and LAE,F of each individual ﬂight event is indicated in the box.
The helicopter as well as the background signals underwent the following processing steps to prepare themfor playback in AuraLab [1]. In a ﬁrst stage of processing, the recordings were calibrated, high-pass ﬁltered( fc = 20 Hz), and low-pass ﬁltered ( fc = 10 kHz). The duration of each stimulus was set to 20 s. Whilebackground signals were available at a sampling rate of 48 kHz, helicopter signals were upsampled from 44.1
to 48 kHz, which is a requirement of the playback system in AuraLab. Foreground helicopter signals andbackground signals were then mixed with 16 bit depth [1].
Background and helicopter signals were gated by squared cosine ramps of 0.5 and 4 s, respectively [1]. That is,the background sound was present during the stimulus duration of 20 s and the helicopter sound arose from andfaded out into the background sound. The sound pressure levels of the helicopter noise signals (LAE,F ) and thebackground signals (LAeq,B ) were modiﬁed to reach the target levels [1]. Beside bass management, which wasdone by a digital signal processor and crossover ﬁlters, most of the processing was carried out with MATLAB
R2016b (MathWorks, Natick, USA).
Figure 2 shows LAS,F as a function of time for the six processed ﬂight events (without any mixed backgroundsounds).
It should be noted that the focus of this experiment was on conditions in which the helicopter noise and theambient sound were clearly in foreground and background, respectively, i.e., LAE,F >> LAeq,B . As a consequence,
the following limits were set for the stimuli (and the experimental conditions) [1]:• LAE,S − LAE,F < 1 dB(A), whereby S stands for the (mixed) signal/stimulus;• LASmax,S − LASmax,F < 1 dB(A);• LAeq,S − LAeq,F < 1 dB(A).
2.4 Experimental design
A partially balanced incomplete block (factorial) design [20] was used with three independent variables [1]:LAE,F [six levels: 68, 70, 72, 74, 76 or 78 dB(A)], LAeq,B [four levels: 6 (i.e., background level of AuraLab
in case of no background sound), 34, 41, or 48 dB(A)], and background sounds [ﬁve levels: no backgroundsound, water stream (L), birds and vegetation (L), birds and vegetation (E), and church bell (E)]. In total, 78
stimuli were prepared for the experiment:
6 × 3 × 4 + 6 (stimuli without background sounds) = 78.

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Figure 3. Mean annoyance ratings and their 95% conﬁdence intervals as a function of helicopters’ sound exposure level LAE,F . Note that only a portion (2-8) of the annoyance scale (0-10) is shown here.
A-weighted sound exposure levels of the stimuli (i.e., mixed ﬂight and background), LAE,S , were between 68.0
to 78.1 dB(A) (mean LAE,S = 73.1 dB(A)). Furthermore, 20 ≤ LAE,F − LAeq,B ≤ 72 dB(A) and 0.0 ≤ LAE,S −LAE,F ≤ 0.8 dB(A) [1]. The partially balanced incomplete block design consisted of 32 blocks (i.e., subjects),
each containing 40 stimuli (i.e., a repeated-measures design).
2.5 Experimental sessions
The experiment was carried out individually for each subject and as a focused listening test. After reading thestudy information and signing a consent form, the subjects answered the ﬁrst part of the questionnaire about
their hearing and well-being. They were then introduced to the listening test and the test software. Subjects
rated their perceived annoyance they associated with each stimulus during or directly after its playback. Afterthe listening test, the subjects ﬁlled out the remaining part of the questionnaire about their demographic data
[1].
2.6 Listening test software and the annoyance scale
The listening test software (developed at the Empa) guided the subjects through the test and recorded theirannoyance ratings [1]. The subjects listened to four orienting and three training sounds before starting the main
listening test, in which, for each subject, their 40 stimuli were presented in a random order. They were playedback once only, with a 1.5-s break between stimuli.
Short-term annoyance was rated on the ICBEN 11-point scale [21], asking the following question [1]: “Whenyou imagine that this is the sound situation in your garden, what number from 0 to 10 represents best how
much you would be bothered, disturbed or annoyed by it?”
2.7 Subjects
Thirty-two self-declared normal hearing subjects participated in the main experiment: 13 females and 19 males,
aged between 21 and 50 yr (median 27.5 yr) [1].

3

RESULTS

In total, 1280 annoyance ratings were collected (32 subjects × 40 stimuli per subject). The effects of the independent design variables on the perceived annoyance was analyzed by linear mixed-effect models (not reported
in detail here) [1]. The main predictor of perceived annoyance was the ﬂight event’s LAE,F (p < 0.001). Figure 3 shows mean annoyance (and 95% conﬁdence intervals) across subjects and for each LAE,F , averaged overbackground sound types and levels [1].

7677Figure 4. Mean annoyance ratings and their 95% conﬁdence intervals as a function of background sound (above)and background sound type (below). Note that only a portion (2-8) of the annoyance scale (0-10) is shown here.
Background type (i.e., no, L, or E) was a further signiﬁcant predictor of annoyance (p < 0.05). Stimuli with
eventful background sounds were more annoying than those with less eventful background sounds. Figure 4
shows mean annoyance (and 95% conﬁdence intervals) across subjects and for each background sounds (above)or type (below), averaged over LAE,F and LAeq,B [1].
Background level (LAeq,B ) showed only in interaction with background type a signiﬁcant effect on annoyance(p < 0.05). That is, with increasing LAeq,B , annoyance from stimuli with eventful background and less eventful
sounds increased and decreased, respectively. No difference could be observed between annoyance from thestimuli with less eventful and those with eventful background sounds at a background level of 34 dB(A). Figure 5 shows mean annoyance (and 95% conﬁdence intervals) across subjects as a function of LAeq,B ; i.e., main
effect (above) and the signiﬁcant interaction with background type (below) [1].

4

CONCLUSION

A laboratory experiment was carried out to quantify the effects of background sounds (mixed with foregroundnoise) on the perceived annoyance from the foreground noise. Annoyance was found to depend on the noiselevel, LAE,F , and background type: annoyance increased with increasing LAE,F and for stimuli with eventful
background sounds. Furthermore, background type and LAeq,B interacted signiﬁcantly in predicting annoyance:
the difference between annoyance for stimuli containing eventful or less eventful background sounds grow withincreasing LAeq,B . For this experiment – i.e., when LAE,F >> LAeq,B or LAE,S − LAE,F < 1 dB(A) –, on average,
no difference was found between annoyance from stimuli with no background sounds and those with less eventful background sounds. For applications in psychoacoustic laboratory experiments and in order to ensure theexperimental validity (with respect to the foreground aircraft noise), the results suggest to use low-level water
stream, birds, and vegetation sounds which exhibit a low degree of eventfulness.

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Figure 5. Mean annoyance ratings and their 95% conﬁdence intervals as a function of LAeq,B (above). Theinteraction between background type and level (LAeq,B ) is shown below, whereby circle (• ), square () andcross (× ) stand for no, less eventful, and eventful background, respectively. Note that only a portion (2-8) of
the annoyance scale (0-10) is shown here.

ACKNOWLEDGEMENTS
The authors would like to express their gratitude to the participants of the experiment. They are thankful to
Reto Pieren for preparing the listening test software.

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