PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Estimation of psychoacoustic indices and annoying auditory
sensations from sound pressure levels of urban road traffic
Catherine MARQUIS-FAVRE1, Pierre-Augustin VALLIN2, Laure-Anne GILLE3, Wolfgang ELLERMEIER4
1,2,3

4

Univ Lyon, ENTPE, France

Technische Universität Darmstadt, Germany

ABSTRACTThe day-evening-night noise level (LDEN) is often used as an index of noise annoyance. However, various
other acoustical and psychoacoustical indices have been shown to improve noise annoyance models incomparison with models solely based on LDEN. The difficulty is to determine such indices in the field, sincethat requires numerous in-field recordings and tedious calculations. Alternatively, it might be possible to infer
such indices from the equivalent sound pressure level (LAeq) of the noise sources used in the production ofEuropean noise maps. In the current study, such alternative is assessed from a perceptual point of view. A
listening test was carried out with 30 participants in order to assess annoying auditory sensations evoked byroad traffic noise at different distances from the main street in urban environments. For each auditory
sensation, i) the relationship between the calculated psychoacoustic index and the rated sensation magnitude,
as well as ii) the relationship between the auditory sensation and the LAeq of the noise sample were determined.
These two relationships permitted to reliably estimate psychoacoustic index values from the LAeq of the roadtraffic noise.
Keywords: psychoacoustic index, annoying auditory sensations, estimation of psychoacoustic indices fromsound pressure level of sources

1. INTRODUCTION
In urban areas, noise annoyance is a major source of concern. Road traffic is the most annoying
noise source (e.g. 1, 2). European cities of more than 100,000 inhabitants manage noise exposureusing strategic noise maps (3). These maps are based on LDEN, the day-evening-night level, andrepresent noise exposure to transportation noise sources. This index is also used in exposure-effectrelationships to estimate the percentage of people annoyed by a transportation noise source (1).
However, it does not cover some acoustical features known to be particularly annoying, i.e. spectral
content, irregular amplitude variation or modulation (e.g. 4-7).
It is also well known that non-acoustical factors, such as noise sensitivity, influence noise
annoyance (e.g. 8). Noise annoyance models, considering noise sensitivity and psychoacoustic indicescharacterizing different annoying acoustical features, have been proposed based on laboratory
research (e.g. for road traffic noise (5), railway noise (6)). However, it might be difficult to apply suchmodels to the field, since most psychoacoustical indices cannot be predicted or measured for a large
number of urban locations.
To overcome this difficulty, a methodology was proposed to estimate psychoacoustic index values
from the A-weighted equivalent sound pressure level (LAeq ) or LDEN of the noise sources (9). The
estimation was numerically obtained from a set of sound recordings carried out in urban areas exposed
to urban road traffic noise and aircraft noise. Based on recent psychoacoustic annoyance models andthe estimation of psychoacoustic index values from the LDEN specified in noise maps, noise annoyance
ratings were predicted for two French cities (9). The comparison of the predicted annoyance ratings1

catherine.marquisfavre@entpe.fr
pierreaugustin.vallin@ entpe.fr
3
laureannegille@gmail.com
4ellermeier@psychologie.tu-darmstadt.de27979

with annoyance ratings collected from a socio-acoustic survey showed an improvement of annoyanceprediction due to the psychoacoustic index-based annoyance models in comparison with models solely
based on LDEN. In the current study, the estimation of psychoacoustic index values from the noise
source LAeq is investigated from a perceptual point of view by investigating the variation of annoying
auditory sensations as a function of the noise source LAeq . A listening test was carried out underlaboratory conditions to assess sensations evoked by urban road traffic noise at different distancesfrom the main street in urban environments. For each auditory sensation studied, i) the relationshipbetween the rated auditory sensation magnitude and the LAeq of the noise sample, as well as ii) the
relationship between the calculated psychoa coustic index and the rated sensation magnitude were
determined. These two relationships permitted to estimate psychoacoustic index values from the LAeqof the urban road traffic noise.

2. THE EXPERIMENT
Different types of urban ground transportation noises were under consideration in the experiment:road traffic noises, powered-two-wheeler pass-by noises and railway pass-by noises. The experimentis presented in the following. First results related to urban road traffic noises will be presented in thispaper.
2.1 Stimuli
The urban ground transportation noises were grouped into 3 series of stimuli.
For the series of railway noises, two train pass-by noises and two tramway pass-by noises,
stereophonically recorded at 10 m from the tracks (6), were selected.
The series of powered-two-wheeler noises consisted of two motorcycles, one at constant speed,
and one accelerating, stereophonically recorded at 3 m from the source (10).
For the series of urban road traffic noises, three traffic noise sequences were constructed by joining
different single vehicle pass-by recordings, which stemmed from the perceptual typology of urban
road vehicle pass-by noises proposed by Morel et al. (10). They were recorded at 3 m from the source.
The three road traffic noise sequences included a light vehicle, a powered-two-wheeler and a heavy
vehicle, in various orders and with various driving conditions.
Each recorded single pass-by was specifically selected for containing acoustical features related toannoying auditory sensations, such as high-frequency content for train pass-by noises (e.g. squealing
noise (6)) or for road vehicle pass-by noises (e.g. breaking noise (7)) and strong modulation
components for road vehicle pass-by noises (7).
The 3 urban road traffic noises and the 2 powered-two-wheeler noises were processed using acomputer software to simulate sound propagation in an urban environment at distances of 10 m, 13 m,
18 m, 24 m, 32 m, 42 m, 56 m and 75 m, both for propagation in a U-shaped street and in an open
street. The software used, Code_TYMPAN (11), and the corresponding simulation process had been
selected and evaluated for this purpose from a perceptual point of view (12). The simulation process
consisted of applying third-octave attenuations to the recordings to account for atmosphericabsorption, reflections on the ground, and on nearby buildings of a U-shaped street. In the current
study, the simple geometrical spreading was also considered: the sound pressure level logarithmicallydecreases with distance. For each series of urban road transportation noises, this led to the constructionof 24 attenuation transfer functions (8 distances and 3 types of propagation (U-shaped street, open
street, geometrical spreading)) to be applied to each initial sound recording.
For the series of urban road traffic noises, there were 75 stimuli (3 compositions x (8 distances x
3 propagation types + 1 initial sound recording)). Their equivalent sound pressure level ranged from33.6 to 65.2 dB(A), with stimulus durations between 16 and 18 s.
The series of powered-two-wheelers was composed of 50 stimuli (2 motorcycles x (8 distances x
3 propagation types + 1 initial sound recording)). Their equivalent sound pressure level ranged from
38.3 to 66.2 dB(A) and their duration was comprised between 4 and 6 s.
For the urban railway noises (train or tramway), the initial sound recording distance was 10 m, so
only 7 distances were simulated, from 13 to 75 meters, with the three different types of propagation(U-shaped street, open street, geometrical spreading). This led to a series of 88 railway stimuli (4trains x (7 distances x 3 propagation types + 1 initial sound recording)). Their equivalent soundpressure levels ranged from 45.5 to 71.2 dB(A) and their duration from 8 to 17.6 s .

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2.2 Apparatus
The experiment took place in a quiet room, with a background noise of 23.8 dB(A). The
stereophonic stimuli were reproduced through a pair of active loudspeakers (Dynaudio BM5A) andone active subwoofer (Dynaudio BM9S). The loudspeakers were positioned at a height of 1.20 m,
forming an equilateral triangle with the participant’s interaural axis, according to Bech and Zacharov’s(13) recommendations. The subwoofer was placed on the floor between both loudspeakers. The
participants were facing a computer screen displaying the experimental interface. A computer washandling the interface and the reproduction of noises through a high-quality soundcard (LynxTwo
studio interface). The reproduced stimuli were recorded at the participant’s head position using botha Cortex Manikin MK2/NCF1 and an omnidirectional microphone in order to compute acoustical andpsychoacoustical indices.
2.3 Participants
Thirty-two listeners took part in the experiment (15 men, 17 women, mean age: 33 years, SD: 11.1).
They were paid for their participation, and they all declared normal hearing abilities.
2.4 Procedure
Stimuli were played back in random order. For each stimulus, the participants were asked to rate anumber of auditory sensations related to different acoustical features.
For the urban railway noises, the acoustical features queried were i) high-pitched content (e.g. due
to squealing noise (6)), ii) the presence of temporal amplitude variation, and iii) overall sound intensity.
For powered-two-wheelers, the acoustical features were i) high-frequency modulation (e.g. likethe “buzzing of a wasp” for some scooter noises (7)) and ii) overall sound intensity.
For the urban road traffic noise series, the acoustical features were i) a high-pitched content (e.g.
due to breaking noise (7)), ii) low-frequency modulation (e.g. in some accelerating vehicle noises (7)),iii) the presence of temporal amplitude variation, and iv) overall sound intensity.
A continuous scale ranging from 0 (“not present at all”) to 10 (“extremely present”) was used by
the participants to rate these sensation magnitudes. Two preliminary phases allowed the participants
to familiarize themselves with the task. For each series of stimuli, a practice phase allowed theparticipants to listen to reference transportation noises that were representative of each acousticalfeature studied. A subsequent training phase then allowed the participants to rate the sensation
magnitudes related to the acoustical features of a small number of stimuli, with the possibility to listen
to them alternately with the reference transportation noises. The reference noises were notsubsequently used in the experiment proper. Participants took breaks between each series of stimuli.
The experiment lasted 99 minutes on average (45 min for the railway noises, 15 min for the
powered-two-wheeler noises, 39 min for road traffic noise).

3.

RESULTS

3.1 Methodology for relationship determination
For each series of stimuli, and for the auditory sensation related to each acoustical feature, theanalysis consisted of:- Assessing the variation of the rated auditory sensation magnitude as a function of the A-weighted
equivalent sound pressure L Aeq of the source, and fitting a regression model. This expressed the rated
sensation magnitude Sensa as a function F of the LAeq of the noise source:
Sensa=F(LAeq)(1)- Obtaining a relationship between the psychoacoustic index Ind calculated from the stimuli of thestudied series and the corresponding rated sensation magnitude Sensa. This yielded the psychoacoustic
index Ind as a function G of the rated sensation magnitude:
Ind=G(Sensa)(2)- Proposing a relationship between each psychoacoustic index and the LAeq of the noise source fromthe two previous relationships. This new relationship permits to estimate the psychoacoustic index
values from the LAeq of the noise source. This estimated index value, denoted by Est_Ind, might bewritten as:

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Est_Ind=G[F(LAeq )](3)
The goodness-of-fit of this last relationship was assessed by a correlation analysis between theestimated index values Est-Ind and the index values Ind calculated from the stimuli used in theexperiment.
3.2

Urban road traffic noises: sensations related to high-pitched content, temporalamplitude variation and overall sound intensity
In this conference paper, results are presented for the series of urban road traffic noises, and 3 rated
sensations related to high-pitched content, temporal amplitude variation and overall sound intensity.
For conciseness, the sensation related to high-pitched content will be denoted by high-pitched and thesensation related to temporal amplitude variation will be denoted by fluctuation. Finally, the third
sensation studied, related to sound intensity, is loudness.
Figure 1 displays an example of the variation of the rated high-pitched sensation magnitude as afunction of the level of the urban road traffic noise LAeq . Due to the observed trend, a linear regression
between this rated sensation magnitude and LAeq was computed.

Figure 1 – Linear regression between high-pitched sensation magnitude (0-10) and LAeq (dBA)

Table 1 displays the regression equations obtained between the rated magnitudes of the threesensations and the level of the urban road traffic noise, LAeq (cf. Eq. (1)).
Table 1 – Relationships between rated sensation magnitudes and the urban road traffic A-weighted equivalentsound pressure level (LAeq). SensaLoudness: loudness; SensaHigh-pitched: sensation related to high-pitched content;
SensaFluctuation: sensation related to temporal amplitude variation.
Sensation

Equation of relationships

Loudnessܵ݁݊‫ܽݏ‬௅௢௨ௗ௡௘௦௦ ൌ ͲǤʹ͹Ͳ ή ͳͲ଴Ǥ଴ଶଷହή௅ಲ೐೜High-pitchedܵ݁݊‫ܽݏ‬ு௜௚௛ି௣௜௧௖௛௘ௗ ൌ ͲǤͲͺͺͺ ή ‫ܮ‬஺௘௤ െ ͲǤͺͻ͹Fluctuationܵ݁݊‫ܽݏ‬ி௟௨௖௧௨௔௧௜௢௡ ൌ ͲǤ͹͸Ͳ ή ͳͲ଴Ǥ଴ଵସή௅ಲ೐೜

Table 2 shows the relationships between the psychoacoustical indices and the rated sensations (cf.
Eq. (2)).
The first index is the loudness index N. The two other indices are TETC16-24 and σ’(N) to
respectively account for high-pitched content (7) and temporal amplitude variation (5) of urban road7982

traffic noise. They are defined as followsଶସ(4)ܶ‫ܥܶܧ‬ଵ଺ିଶସ ൌ ͳͲ ݈‫݃݋‬ଵ଴ ቆන ͳͲ௅ሺ௭ሻȀଵ଴ ݀‫ݖ‬ቇଵହ

TETC16-24 corresponds to the Total Energy of Tonal Components between critical bands 16 and 24
Barks. The variable L(z) is the maximal level of the tonal components in a given critical band z.
்ଶߪԢሺܰሻ ൌ ඨͳൗܶ න ቀ݀ܰൗ݀‫ݐ‬ቁ ݀‫ݐ‬(5)

଴σ’(N) stands for the temporal derivative of loudness N. Due to the mathematical expression, theindex accounts for both regular and irregular amplitude variations.

Table 2 – Relationships between indices and the rated sensations. N: loudness index (sone); TETC16-24: Total
Energy of Tonal Components between critical bands 16 and 24 Barks (dB); σ’(N): temporal derivative of
loudness N (sone/s); SensaLoudness: loudness; SensaHigh-pitched: sensation related to high-pitched content;
SensaFluctuation: sensation related to temporal amplitude variation.
Index

Equation of relationshipsNܰ ൌ ͲǤ͸͹͸ ή ܵ݁݊‫ܽݏ‬௅௢௨ௗ௡௘௦௦ െ ͲǤ͵͸ʹ

TETC16-24

ܶ‫ܥܶܧ‬ଵ଺ିଶସ ൌ ͳͺǤͻ ή ܵ݁݊‫ܽݏ‬ு௜௚௛ି௣௜௧௖௛௘ௗ ଴Ǥ଻ଷ଻σ’(N)ߪ′ሺܰሻ ൌ ʹǤʹͻ ή ܵ݁݊‫ܽݏ‬ி௟௨௖௧௨௔௧௜௢௡ ଵǤହ଻Finally, Table 3 presents the relationships obtained by applying Eq. (3) using both Eq. (1) and (2).
For these final results, the quality of the fit is indicated by the correlation coefficient r between theindex values estimated from the LAeq of the noise sources and the psychoacoustical index values
calculated from the experimental stimuli directly.
Table 3 – Relationships between psychoacoustical indices and the A-weighted equivalent sound pressure level ofthe urban road traffic noise (LAeq). N: loudness index (sone); TETC16-24: Total Energy of Tonal Components

between critical bands 16 and 24 Barks (dB); σ’(N): temporal derivative of loudness N (sone/s); r: thecorrelation coefficient between index values estimated from LAeq and index values calculated from the stimuli.
Index
N

3.3

Equation of relationships
଴Ǥ଴ଶଷହή௅ಲ೐೜ܰ ൌ ͲǤ͸͹͸ ή ሺͲǤʹ͹Ͳ ή ͳͲሻ െ ͲǤ͵͸ʹr
0.99

TETC16-24

ܶ‫ܥܶܧ‬ଵ଺ିଶସ ൌ ͳͺǤͻ ή ሺͲǤͲͺͺͺ ή ‫ܮ‬஺௘௤ െ ͲǤͺͻ͹ሻ଴Ǥ଻ଷ଻

0.87

σ’(N)

ߪ′ሺܰሻ ൌ ʹǤʹͻ ή ሺͲǤ͹͸Ͳ ή ͳͲ଴Ǥ଴ଵସή௅ಲ೐೜ ሻଵǤହ଻

0.99

Comparison between the rated sensation magnitude and the corresponding index

value
In the present paper, we restrict ourselves to performing this comparison for overall loudness.
Figure 2 presents the loudness index estimated from LAeq versus the loudness rating obtained in thelistening test. The significant correlation coefficient between the two sets of data is equal to 0.85.
If one considers the correlation coefficient between the loudness index N calculated from thestimuli and the loudness rating obtained in the listening test, a similar correlation is obtained andequal to 0.84 (cf. figure 3).

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Estimated loudness index (sone)

6
5
4
3
2
1
0

0

2

4

6

8

10

Loudness rating
Figure 2 – Comparison between the loudness index estimated from the LAeq of the stimuli and the rated loudness
magnitude (r=0.85; p<0.05)
8

loudness index (sone)

7
6
5
4
3
2

1
0
0

2

4

6

8

10

Loudness rating

Figure 3 – Comparison between the loudness index N and the rated loudness magnitude (r=0.84; p<0.05)

These relationships underscore the validity of estimating the loudness index from the A-weighted
sound pressure level of the urban road traffic noise excerpts.
In reference (9), it was proposed to estimate loudness index values from the LAeq of urban roadtraffic noise. The determination was carried out numerically from urban road traffic noise excerpts
recorded in field.
Using data of the current experiment, it was possible to assess this numerical determination froma perceptual point of view. For doing this, the relationship from (9) was used to estimate loudness
index values from the LAeq of the experimental stimuli. Then a comparison was carried out between
the thus estimated loudness index values and the loudness ratings gathered during the current
experiment (see Figure 4).

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Estimated loudness index (sone)

14
12
10
8
6

4
2
0

0

2

4

6

8

10

Loudness rating
Figure 4 - Comparison between the estimated loudness index [based on (9)] and the loudness ratings (r=0.84;
p<0.05)This yielded a moderately high and significant correlation coefficient amounting 0.84. It indicates thatthe numerical methodology proposed in (9) to estimate loudness index values from the LAeq of urban roadtraffic noise seems to be valid from a perceptual point of view and equivalent to the one determined in thecurrent study based on a listening test.

DISCUSSION AND CONCLUSIONS
Studies carried out in field highlighted the need for additional acoustical indices to bettercharacterize annoyance, and in particular the use of psychoacoustic indices (e.g. (14-15)). But many
psychoacoustic indices cannot be predicted or measured in a large urban environment . From excerpts
of urban road traffic noise and of aircraft noise, a methodology (9) was proposed to estimate
psychoacoustic index values from the equivalent sound pressure level, or LDEN, of the noise sources.
The methodology led to estimated values which allowed enhancement of annoyance prediction frommodels using psychoacoustic index values in comparison with models solely based on LDEN. The
current study proposed to estimate such index values from a perceptual point of view. This was
accomplished by carrying out listening tests using different urban ground transportation noises(powered-two-wheeler noises, road traffic noises and railwa y noises). First results obtained for threeauditory sensations evoked by urban road traffic noises indicate that the perceptual methodology toestimate different psychoacoustic index values from the sound pressure level of the sources seems to
be a valid approach, since it yielded strong relationships 1) between the thus estimated index values
and the index values calculated from the stimuli, and 2) between the estimated index values and thesensation magnitude ratings. More specifically, a comparison between the estimated loudness values
obtained from the methodology proposed in (9) and the loudness ratings gathered during the current
experiment resulted in a strong correlation and thus indicates the perceptual relevance of the numericalmethodology proposed in (9) to estimate loudness indices from in-field sound pressure levels of urban
road traffic noises.
The current study presented first results. These results indicated the perceptual relevance of theestimation of psychoacoustic index values from sound pressure levels of the sources. A further
research perspective might be to investigate the estimation of psychoacoustic indices using various
in-field recordings accounting for different transportation noise situations.

ACKNOWLEDGEMENTS
This work was performed within the framework of the LABEX CeLyA (ANR-10-LABX-0060) of
Université de Lyon, within the program « Investissements d’Avenir » (ANR-16-IDEX-0005) operated

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by the French National Research Agency (ANR).

REFERENCES
1. Miedema H.M.E., Oudshoorn C.G.M. Annoyance from transportation noise: relationships with exposure metrics
dnl and denl and their confidence intervals. Environmental Health Perspectives 2001;109(4):409-416.
2. Gille L.-A., Marquis-Favre C., Morel J. Testing of the european union exposure- response relationships andannoyance equivalents model for annoyance due to transportation noises: The need of revised exposureresponse relationships and annoyance equivalents model. Environment International 2016;94:83-94.
3. European Commission Directive 2015/996 of 19 May 2015 establishing common noise assessment methods
according to Directive 2002/ 49/ EC of the European Parliament and of the Council 2015. p. 823.
4. Kaczmarek T., Preis A. Annoyance of time-varying road-traffic noise. Archives of Acoustics 2010;35(3):383393.
5. Gille L.-A., Marquis-Favre C., Weber R. Noise sensitivity and loudness derivative index for urban road traffic
noise annoyance computation. J. Acoust. Soc. Am. 2016;140 (6):4307-4317.
6. Vallin P.-A., Marquis-Favre C., Bleuse J., Gille L.-A. Railway noise annoyance modeling: Accounting for noise
sensitivity and different acoustical features. J. Acoust. Soc. Am. 2018;144 (6):3381-3390.
7. Klein A., Marquis-Favre C., Weber R., Trollé A. Spectral and modulation indices for annoyance-relevant
features of single urban road vehicle pass-by noises. J. Acoust. Soc. Am. 2015;137(3):1238-1250.
8. Nguyen T. L., Yano T., Yokoshima S., Morihara T. Structural equation model of road traffic noise annoyance invietnam.Proc Inter-noise 2014.
9. Gille L.-A., Marquis-Favre C. Estimation of field psychoacoustic indices and predictive annoyance models forroad traffic noise combined with aircraft noise. J. Acoust. Soc. Am. 2019;145(4):2294-2304.
10. Morel J., Marquis-Favre C., Dubois D., Pierrette M. Road traffic in urban areas: a perceptual and cognitive
typology of pass-by noises. Acta Acustica united with Acustica 2012;98(1):166-178.
11. Code_TYMPAN, open source, www.code-tympan.org (Last viewed February 22, 2018).
12. Vallin P.-A., Marquis-Favre C., Gille L.-A., Ellermeier W. Selection of a sound propagation model for noise
annoyance prediction: a perceptual approach (L). J. Acoust. Soc. Am. 2018;143(3):1283-1286.
13. Bech S.and N. Zacharov, Perceptual audio evaluation - Theory, method and application. Wiley edition;2006.
14. P. Lercher, B. D. Coensel, L. Dekonink, and D. Botteldooren,“Community response to multiple sound sources:
Integrating acoustic and contextual approaches in the analysis,” Int. J. Environ. Res. Public Health14(6), 663(2017).
15. M. Paviotti and K. Vogiatzis, “On the outdoor annoyance from scooter and motorbike noise in the urban
environment,” Sci. Total Env. 430, 223–230 (2012).

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