Cognitive load influences the evaluation of complex acoustical scenarios
Jochen STEFFENS(1) , Franz MÜLLER(1) , Melanie SCHULZ(1) , Samuel GIBSON(1) .
(1) Technische Universität Berlin, Audio Communication Group, Germany, jochen.steffens@tu-berlin.de

Abstract
Sound evaluations depend on sound characteristics as well as on situational and person-related factors. Aim of
the study was to investigate the effects of temporal dynamics of a sound, a person’s cognitive load, personality
traits (noise sensitivity, extraversion) and their interactions on the overall retrospective evaluation of complex
acoustical scenarios. In the course of a laboratory experiment, 62 participants were presented eight two-minutesound examples, whereby the position and valence of the peaks were varied. Task of an experimental group
was to perform the so-called Stroop test of color-to-word interference during the sound presentation, and to
retrospectively rate the sounds in terms of loudness and pleasantness. A control group only rated the sounds
during and after listening to them. Results revealed that, on average, participants in the “inattentive” experimental group rated the sounds as 6.6% less loud and 6.7% more pleasant compared to the participants of the“attentive” control group. Peak position and valence also showed main effects but did not interact with the effect of the treatment. Moreover, personality traits did not have a significant main or moderating effect on soundevaluations. Findings highlight the important role of cognitive load and attention on the evaluation of complex
acoustical scenarios.

Keywords: Sound evaluations; Attention; Cognitive load; Retrospective judgments; Personality

1

INTRODUCTION

Human evaluations of our acoustical environment depend on multiple factors, such as features of the sound,
psychological characteristics of the listener or the context in which the evaluation takes place. While researchon the influence of sound properties on perception and evaluation was widely investigated in psychoacousticalresearch [1, 2], the role of the listener received less attention. Also, it is widely unknown how sound andlistener characteristics interact within the evaluation process.
1.1 Listener state – Influences of attention and cognitive load
One of the crucial factors influencing sound evaluations is the current attention of the listener. Attention canbe described as the process of selecting information that is important for current action and perceptual goals
and suppressing irrelevant information. The focus of attention can either be directed deliberately (for example,
on a certain speaker) or steered automatically in response to a salient sensory input (focusing on the cause of
the stimulus). In our study, we follow a cognitive load theory of attention in which the perception or rejectionof an (acoustical) stimulus is assumed to depend on the level of cognitive load (defined as the used amount ofworking memory resources) associated with a certain distracting task [3].
Opposed to many psychoacoustical experiments, the listener’s attention in a real-life situation is not always focused on the acoustical environment, especially when it comes to non-speech sounds. This might lead to biases
when predicting annoyance reactions in mundane life by results from laboratory studies. Empirical evidence
suggests that sounds from household appliances are perceived as more pleasant in everyday-like environments
in which the participants’ attention is not solely focused on the acoustical stimulus, compared to experiments
where only sounds of the devices are presented [4]. This is corroborated by early studies of attention on vision
which demonstrated that unattended information typically goes unnoticed [5].

7751

1.2 Listener traits – Influences of personality
Cognitive and emotional processes (such as those involved in sound evaluations) can be further related to various
stable personality traits and information processing styles which might explain differences in sound evaluations
across individuals. Presumably the most important trait in the context of this paper is noise sensitivity which
covers attitudes toward different kinds of environmental sounds [6]. Furthermore, the Big Five personality trait
Extraversion has repeatedly been connected to effects of background sounds and music on the execution ofcomprehension and problem solving tasks [7]. Finally, several traits such as Neuroticism and the information
processing style have be shown to interact with situational variables (e.g., company of others) when it comes tosound evaluations [8].
1.3 Sound characteristics – Influences of the temporal dynamics of a sound
When discussing the role of attention / inattention on sound perception and evaluation, one must consider
that, as mentioned above, certain sounds are capable of modulating the listener’s attention due to their salient
characteristics (e.g., loudness, temporal and spectral fluctuations). The important role of peaks (i.e., salient
events) on overall loudness and pleasantness judgments of time-varying environmental sounds have already been
demonstrated in various studies [8, 9]. Furthermore, it has been shown that later sound events play a more
important role in predicting retrospective sound evaluations than other sections (recency effect; [10]). The factthat retrospective judgments can be predicted only by the unweighted combination of peak and the end wasestablished by Kahneman and colleagues as the so-called ’peak-end rule’ [11]. In this context, Steffens, Steele& Guastavino (2017) observed that a weighted combination of peak and end can explain a large proportion ofvariance in daily retrospective judgments of environmental sounds [8].
1.4 Sound and listener characteristics and their interaction – The current study
One major aim of the current study was to investigate the influence of inattention in the course of increased
cognitive load caused by a distracting task on pleasantness judgments of environmental sounds. Based on theliterature, we hypothesized that inattentive participants would rate sounds as significantly more pleasant and lessloud than attentive participants (H1). With regard to the temporal position of salient events (peaks), we assumed
that the later a negative valence peak (peak levels higher than level values of the rest of the sound) is positioned
in a sound scenario, the louder and more unpleasant the sound will be judged, regardless the attentional stateof the participant (H2a). Analogously, we expected that the later peaks with positive valence occur in a soundscenario, the lower the overall unpleasantness and loudness would be rated (H2b).
Concerning the role of personality, we assumed that participants scoring high on Extraversion and executing atask while listening would judge test sounds as less loud and more pleasant than participants scoring low on
Extraversion (H3), due to a lower interference of the task execution [7]. Finally, potential interactions between
sound and listener characteristics were explored without formulating specific hypotheses.

2

METHOD

2.1 Participants
The study involved 63 participants aged between 20 and 63 years (27% female; mean age: 29.5, SD = 7.9).
Twenty participants were contacted via the TU Berlin mailing list of active study participants and received 10 e
as compensation. The remaining 43 participants were students of the TU Berlin who could acquire credit points
for participating. Requirements for participation were normal hearing, sufficient knowledge of German and nocolor blindness. The data set of one participant was excluded from the evaluation due to the fundamentally
incorrect execution of the task.

7752

2.2 Stimuli
Nine different two-minute sound scenarios taken from the sound database General Series 6000 were used forthe study. Six of the scenarios, referred to as test sounds, consisted of a constant background sound (base)interrupted by another twenty-second sound event (peak). The sounds were divided by “peak types” into groupsof three. One group contained sounds with low peaks (peak level lower than background sound), the othersounds with high peaks (peak level higher than background sound). The peaks were located after 10 seconds(early), 50 seconds (middle), or 90 seconds (late) for each condition (see Figure 1). In addition, a training
sound and two filler sounds were compiled. The latter were used to distract the participants from the regularstructure of the sounds during the sequential presentation. The structure and composition of the sounds aredescribed in Table 1.
2.3 Experiment setup and calibration
The sounds and tasks were presented to the participants using a laptop computer with Matlab software, anexternal audio interface (Focusrite Scarlett 6i6) and circumaural headphones (DT 770 Pro). For the calibrationof the system, the loudest of the test sounds, the jackhammer sound, was used as the reference sound. Using
an audio coupler, the volume of the sound was adjusted by matching the volume of the reference sound to thatof a nearby construction site (ca. 50 m distance) of 85dB(A). After several test runs, the volume of the soundswith low peak was reduced to 75 dB(A) in order to make the acoustical stress caused by the significantly longer
jackhammer sound tolerable for the participants (see Figure 1).
2.4 Experimental design
Participants were randomly assigned to an inattentive (experimental) and an attentive (control) group. Participants in the attentive group performed a listening task that drew their attention directly to the presented sounds.
Participants of the inattentive group conducted the Stroop Color-Word Interference Test (see Section 2.4.1) during the presentation of the test sounds in order to constantly distract them from the acoustical stimuli. Testand filler sounds were successively presented to both groups in a randomized order; only the filler sounds werealways placed in the third and sixth position. Filler sounds were used to distract the participants from the regular structure of the test sounds (peak type and peak position) in order to reduce anticipation errors and were
excluded from the data analysis. After the presentation of each sound, the participants had to rate the loudness
and pleasantness of the sounds via two sliders with 101 steps, ranging from "very quiet" to "very loud" and"very pleasant" to "very unpleasant".
At the end of the test, participants completed questionnaires including noise sensitivity [12], Extraversion [13],as well as the two information processing styles ’need for cognition’ and ’faith in intuition’ (German version of
the Rational-Experiential Inventory; [14]). Need for cognition describes the tendency for systematic processingof information and indicates how much people enjoy cognitively strenuous activities, such as solving puzzles.
Faith in intuition indicates how much people rely on intuitive decision-making.
2.4.1 Stroop Color-Word Interference Test (experimental group)
The Stroop Color-Word Interference Test is a concentration task in which a list of differently colored words ispresented to a participant [15]. The words in the list describe different colors. However, the word information
does not match the hue of the word. The task of the participant is either to read the words or to name theircoloring. In the present study, we used the Stroop Test to distract the participants during the presentation of thetest sounds and to ensure a constant cognitive load.
The computer-implemented Stroop Test was used in a slightly modified form. The participants were presented
with lists of 15 words. These lists repeatedly contained the words blue, green, yellow and red in random order.
Although the order was random, it was ensured that a color did not occur several times in succession. The

7753

(a) low peak – early(b) low peak – middle(c) low peak – late(d) high peak – early(e) high peak – middle(f) high peak – lateFigure 1. Level-Time-Diagram of the used test sounds.
limitation was put in place to prevent the occurrence of easily recognizable patterns during the test and, thus,
to prevent fluctuations in test performance. Four buttons were positioned below the word list. Each button waslabeled with one of the colors in black lettering. The task of the test was to assign the coloring of the current
word (indicated by a grey frame) as quickly and conscientiously as possible by pressing the corresponding
button. After each assignment, the frame indicated the next word in the sequence. After assigning the lastword in the list, a new list was generated and the frame was reset to the first position. The test was paused
at the end of each two-minute test sound, and the participants were asked to evaluate the overall loudness andpleasantness of the acoustical scenario.
In addition to the evaluation criteria, the number of correct assignments as well as the response time between theassignments were recorded (not reported in this paper). It was assumed that the performance of the participants(number of correct answers and response time) could improve over the course of the test. This could haveaffected the cognitive load and thus the subsequent assessment of the sounds. In order to keep the performanceas constant as possible, each participant completed a training sequence under supervision. This training sequence
consisted of the Stroop Test accompanied by the training sound. Due to the rather simple task, a training periodof two minutes was considered appropriate in order to reduce possible learning effects to a minimum while also
keeping the cognitive load right before the test at a low level.
2.4.2 Listening Task (control group)
During the presentation of the sounds, participants in the control group were asked to continuously adjust aslider between “very quiet” and “very loud” to reflect the perceived loudness of the test sounds. The evaluationof overall loudness and pleasantness took place after each two-minute test sound. Contrary to the procedureused in the Stroop test, the purpose of the listening task was to draw the attention of the test participants tothe test sounds.

7754

Table 1. Description of the sound scenarios used in the study
Sound

Peak type

Peak position

Base

Peak

Base/Peak level [dBA]

1
2
3
4
5
6
7
8
9

low
low
low
high
high
high
/
/
high

early
middlelate
early
middlelate//
middleJackhammer
Jackhammer
Jackhammer
Noise + Birdsong
Noise + Birdsong
Noise + Birdsong
Japanese Speech
Café + Music
Birdsong + Train Rattle

Noise + Birdsong
Noise + Birdsong
Noise + Birdsong
Jackhammer
Jackhammer
Jackhammer//
Lawn Mower

75 / 60
75 / 60
75 / 60
66 / 85
66 / 85
66 / 85
75 / 65 / 60 - 70 / 80

Note: Sounds 7-9 only functioned as training or filler sounds and were not used for further analyses.

2.5 Data analysis
Data processing and analysis was performed using IBM SPSS 25.0. Before the main analyses, the relationshipbetween the variables “loudness” and “pleasantness” was examined. Due to their high correlation (r = –.717;
p < .001), both variables where collapsed into one factor unpleasantness by means of a Principal Component
Analysis. This factor was scaled in a way that 100% unpleasantness corresponded to the ratings “very loud”
and “very unpleasant”, 0% to “very soft” and “very pleasant” and 50% to a neutral rating. Hypotheses were
tested by means of several linear mixed-effects models including a random intercept for each participant andusing restricted maximum likelihood estimates of variance components and Type III Analysis of Variance via
Satterthwaite’s degrees of freedom method.

3

Results

Before testing the hypotheses, a null model including only a random intercept for each participant was computed
to obtain the Interclass Correlation Coefficient (ICC). This analysis showed that 27.4% of the overall varianceof the judgments can be explained through person-related differences (ICCtotal = .274, ICCexp. = .154; ICC control= .356). The ICCs for both groups revealed that sound evaluations in the attentive group varied more than twice
as much across persons (35.6%) than they did in the inattentive group (15.4%).
In the next step, several linear-mixed effects were computed to test the hypotheses formulated in Section
1.4. Results confirmed our first hypothesis (H1) that participants in the inattentive group would perceive
the test sounds as less loud and unpleasant than participants in the attentive group, F (1, 60) = 7.17; p = .010,
R2 marginal = .039. Figure 2 depicts the means and 95 % confidence intervals for the factor unpleasantness forboth test groups (each with i = 31 observations) and grouped by peak type and peak position. When analyzing
the two items loudness and pleasantness separately, results further revealed that participants in the inattentive
group rated the test sounds 6.6% as less loud and 6.7% more pleasant than the inattentive group.
Concerning H2a, results confirmed our assumption that the peak position had a significant effect on the unpleasantness ratings for the high peak scenarios, F(2,122) = 12.50, p < .001, R2 marginal = .069. As expected, the laterhigh peaks occurred in a sound, the more unpleasant the respective sound scenario was evaluated by the participants. As illustrated by Figure 2, unpleasantness ratings increased over the peak positions "early”, "middle” and"late” from 55.2% over 64.5% to 68.5% (early vs. late: p = .001; middle vs. early: p = .007) for the inattentive
group and from 65.7% over 67.7% to 74.6% (early vs. late: p = .031) for the attentive group. This means thatthe differences in the ratings across the different peak positions were slightly larger for the inattentive groupthan for the attentive group, even though this difference was not significant (p = .248).

7755

100
low peakhigh peak

unpleasantness [%]

80

60

40

20
inattentive groupattentive group

0

early

middle

late

early

middlelatepeak type/peak position
Figure 2. Means and 95% confidence intervals for the factor unpleasantness. The data was divided into inattentive (red) and attentive group (blue) sets and grouped by peak type and peak position.
Also, regarding the low peak scenarios, no significant differences between peak positions (H2b) were observed,
F (2, 122) = 0.88, p = .417.
Moreover, Hypothesis 3 expected an influence of the personality trait Extraversion on the perceived unpleasantness of the sounds in the inattentive group. A linear mixed-effects model, however, revealed that Extraversion
did not predict unpleasantness ratings, F (1, 29) = 0.033, p = .857. This is also the case when repeating thisanalysis for both test groups, F (1, 60) = 0.586, p = .488. Accordingly, analyses revealed no significant linear relationships between unpleasantness ratings in both groups and the other personality traits measured in the study(noise sensitivity, need for cognition, faith in intuition). Finally, no significant interaction effects between personality traits on the one hand and the condition and the peak position on the other hand predicting soundevaluations were obtained.

4

Discussion

This study investigated the role of (in-) attention and cognitive load and potential interactions with sound andlistener characteristics on sound evaluations. Results confirmed our assumption that participants whose attention
was directed to sounds presented in an experiment rated them as louder (6.6%) and less pleasant (6.7%) thanthose distracted by an additional task. This finding is in line with the literature [4, 5] and highlights the needfor taking into account attentional processes when investigating sound evaluations. In addition, it suggests that
results from psychoacoustical studies in which participants’ attention is focused on test sounds might introduce
a bias when predicting human loudness perception and annoyance reactions in mundane life.
Our study further replicated previous findings on the role of recency effects for negative sound events (highpeaks). The recency effect suggests that is not only relevant whether but also when a certain sound event7756

occurs, emphasizing the role of long-term memory processes in sound evaluations. It is worth mentioning that,in our experiment, the recency effect affected both the attentional and the inattentional group in the similar way.
This finding indicates that, despite the shifted focus of attention and the resulting constant differences in overall
unpleasantness judgments, participants in both groups seemed to rely on similar information when forming
these judgments. Contrary to our hypothesis, however, a recency effect was not observed for evaluations ofsounds with low (positive) peaks. This finding might be explained by a negativity bias meaning that negative
information is processed more thoroughly than positive information [16, 17]. We therefore assume that highpeaks have a higher likelihood to be memorized and recalled in the course of a retrospective judgment than low
peaks.
In our study, personality traits were not related to sound evaluations, neither as main effect nor as a moderator.
This contradicts findings from several studies showing significant but small correlations between the degree ofnoise sensitivity and loudness and unpleasantness ratings (e.g., [6]). However, in our study, a rather young
sample reporting comparatively low mean noise sensitivity values conducted the study (M = 22.4%, SD = 3.9%;
not reported in the results section). As noise sensitivity typically increases with age [18], the study should be
replicated with a sample including a higher percentage of elderly participants to obtain significant relationships
between personality and sound evaluations. Regarding the null effect of Extraversion in the inattentional group,
our studies showed that introverts were in fact more affected in their test performance than extraverts (notreported in the results section), but that this was not related to the sound evaluation.

5

Conclusion

In our study, we demonstrated than (in-) attention and cognitive load of a listener significantly affects loudness
and pleasantness ratings of complex sound scenarios. These findings have strong implications for research on
noise effects and psychoacoustical metrics. For example, results obtained in focused laboratory studies mighttend to overestimate actual loudness and unpleasantness judgments in real-life where the focus of people’s attention is not solely focused on the acoustical environment. Amongst others, this might be relevant for practitioners in sound engineering and design when determining tolerance thresholds for acoustical product characteristics(e.g., the loudness of a washing machine).

REFERENCES[1] Fastl, H., & Zwicker, E. (2007). Psychoacoustics: Facts and models (3.th ed.). Berlin: Springer.
[2] Genuit, K., & Fiebig, A. (2006). Psychoacoustics and its Benefit for the Soundscape Approach. Acta Acustica United with Acustica, 92(1), 952–958.
[3] Lavie, N., Hirst, A., Fockert, J. W. de, & Viding, E. (2004). Load theory of selective attention and cognitive
control. Journal of Experimental Psychology. General, 133(3), 339–354.
[4] Steffens, J. (2013). Realism and ecological validity of sound quality experiments on household appliances.
In J. Kang, Chourmouziadou, K. Sakantamis, B. Wang, & Y. Hao (Eds.), Soundscape of European Cities andLandscapes: (e-book) (pp. 132–135).
[5] Neisser, U., & Becklen, R. (1975). Selective looking: Attending to visually specified events. Cognitive
Psychology, 7(4), 480–494.
[6] Ellermeier, W., Eigenstetter, M., & Zimmer, K. (2001). Psychoacoustic correlates of individual noise sensitivity. The Journal of the Acoustical Society of America, 109(4), 1464–1473.
[7] Furnham, A., & Strbac, L. (2002). Music is as distracting as noise: the differential distraction of backgroundmusic and noise on the cognitive test performance of introverts and extraverts. Ergonomics, 45(3), 203–217.

7757

[8] Steffens, J., Steele, D., & Guastavino, C. (2017). Situational and person-related factors influencing momentary and retrospective soundscape evaluations in day-to-day life. The Journal of the Acoustical Society ofAmerica, 141(3), 1414–1425.
[9] Fiebig, A., & Sottek, R. (2015). Contribution of Peak Events to Overall Loudness. Acta Acustica United with
Acustica, 101(6), 1116–1129.
[10] Västfjäll, D. (2004). The “end effect” in retrospective sound quality evaluation. Acoust. Sci. & Tech., 25(2),170–172.
[11] Kahneman, D., Fredrickson, B. L., Schreiber, C. A., & Redelmeier, D. A. (1993). When more pain ispreferred to less: adding a better end. Psychological Science, 4(6), 401–405.
[12] Zimmer, K., & Ellermeier, W. (1997). Eine deutsche Version der Lärmempfindlichkeitsskala von Weinstein.
Zeitschrift Für Lärmbekämpfung, 44, 107–110.
[13] Körner, A., Geyer, M., Roth, M., Drapeau, M., Schmutzer, G., Albani, C., . . . Brähler, E. (2008). Persönlichkeitsdiagnostik mit dem Neo-Fünf-Faktoren-Inventar: Die 30-Item-Kurzversion (NEO-FFI-30). PPmP
- Psychotherapie · Psychosomatik · Medizinische Psychologie, 58(6), 238–245.
[14] Keller, J., Bohner, G., & Erb, H.-P. (2000). Intuitive und heuristische Urteilsbildung – verschiedene
Prozesse? Präsentation einer deutschen Fassung des "Rational-Experiential Inventory" sowie neuer Selbstberichtskalen zur Heuristiknutzung. Zeitschrift Für Sozialpsychologie, 31(2), 87–101.
[15] Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology,
18(6), 643.
[16] Baumeister, R. F., Bratslavsky, E., Finkenauer, C., & Vohs, K. D. (2001). Bad is stronger than good.
Review of General Psychology, 5(4), 323–370.
[17] Rozin, P., & Royzman, E. B. (2001). Negativity Bias, Negativity Dominance, and Contagion. Personality
and Social Psychology Review, 5(4), 296–320.
[18] Schreckenberg, D., Griefahn, B., & Meis, M. (2010). The associations between noise sensitivity, reported
physical and mental health, perceived environmental quality, and noise annoyance. Noise & Health, 12(46),7–16.

7758