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Restaurant acoustics -Verbal communication in eating establishments

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A well-known but also very complicated problem in room acoustics is the ambient noise when many people are gathered for a reception or in a restaurant, a bar, a canteen or a similar place. In such social gatherings, people want to speak with each other, but for the same reason the place can be very noisy, and verbal communication can be difficult or even impossible, especially for people with reduced hearing capacity. The noise depends on at least the following parameters; the volume, the reverberation time, the number of people, and the type of gathering. Verbal communication in a noisy environment is a complicated feedback situation, which implies two interesting phenomena: the Lombard effect and the cocktail-party effect. Solutions are presented both as a simplified model assuming a diffuse sound field and as an advanced computer simulation model. The concept 'Acoustic Capacity' of a facility is defined as the maximum number of persons in order to achieve a sufficient quality of verbal communication. In order to avoid poor acoustics in restaurants and similar places, it is necessary to design with bigger volume and more absorption material than usual in current building design practice.
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Acoustics in Practice, Volume 7, Year 2019, No. 1
Restaurant acoustics – Verbal communication
in eating establishments
Jens Holger Rindel
Multiconsult, Post Box 265 Skøyen, N-0213 Oslo, Norway
E-mail: jehr@multiconsult.no
PACS codes: 43.55.Hy, 43.72.Dv
ABSTRACT
A well-known but also very complicated problem in room
acoustics is the ambient noise when many people are
gathered for a reception or in a restaurant, a bar, a canteen
or a similar place. In such social gatherings, people want
to speak with each other, but for the same reason the place
can be very noisy, and verbal communication can be
difcult or even impossible, especially for people with
reduced hearing capacity. The noise depends on at least the
following parameters; the volume, the reverberation time,
the number of people, and the type of gathering. Verbal
communication in a noisy environment is a complicated
feed-back situation, which implies two interesting
phenomena: the Lombard effect and the cocktail-party
effect. Solutions are presented both as a simplied model
assuming a diffuse sound eld and as an advanced
computer simulation model. The concept ‘Acoustic
Capacity’ of a facility is dened as the maximum number
of persons in order to achieve a sufcient quality of verbal
communication. In order to avoid poor acoustics in
restaurants and similar places, it is necessary to design
with bigger volume and more absorption material than
usual in current building design practice.
Keywords: Speech-noise interaction, Lombard effect,
Cocktail-party effect, Restaurants, Universal design,
Acoustic capacity
Editor in Chief
Miguel Ausejo
Editorial Assistant
Francesco Aletta
Edited by
European Acoustics Association (EAA)
secretary@european-acoustics.net ofce@european-acoustics.net
www.euracoustics.org
c/o. Sociedad Española de Acústica (SEA)
Serrano, 144, ES-28006 Madrid, Spain
Legal Deposit: M-21922-2013 • ISSN: 2308-1813
Key title: Acoustics in practice • Abbreviated key title: Acoust. pract.
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Acoustics in Practice®
International e-Journal of the
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Vol. 7 January 2019 No. 1
1. INTRODUCTION
Noise from people speaking in restaurants and at
social gatherings is often a nuisance because it can be
very loud, and a conversation may only be possible
with a raised voice level and in a short distance.
Because of the noise and the difculties associated
with a conversation, the visitors may leave the place
with a feeling of exhaustion or headache. Elderly
people or those with reduced hearing ability may nd
verbal communication impossible.
In many countries, there is a growing awareness of
the concept called universal design, which means
accessibility for all in public buildings [2]. This is not
limited to the physical access to a building, but includes
also the acoustical conditions, which should be suitable
for everybody. A recent investigation in Norway had the
aim to throw light on the problems due to the acoustical
conditions in various kinds of rooms and spaces for
people with impaired hearing or vision [3]. It was found
that the acoustical problems were particularly
pronounced in canteens, restaurants and cafés and 52 %
of people with impaired hearing were severely or much
disturbed by noise in these places. The data in Table 1
show that 51 % of the people with impaired hearing report
“often/always” difculties having a conversation in these
places. If “sometimes” is included, the percentage
Copyright note: This paper is based on a plenary paper presented at the EuroNoise 2015 conference [1]. The paper is extended with more
examples, gures and discussion of applications in building regulations. The organizing committee of EuroNoise 2015 has granted copyright
permission for the reuse of this material.
RestauRant acoustics – VeRbal communication in eating establishments
2Acoustics in Practice, Volume 7, Year 2019, No. 1
increases to 88 %. For the people with impaired vision
(but normal hearing) the percentage having difculties
with conversations in the same kind of places “often/
always” and “sometimes” is 51 %.
In a noisy party, everyone raises the voice to be heard
better, which again leads to a higher ambient noise
level. This effect is the Lombard effect. The average
relationship between speech level and ambient noise
level (the Lombard slope) is mentioned in International
Standard ISO 9921 [4] and the possible range of the
slope is given in a graph. Lazarus [5, 6] made a review
of a large number of investigations, and he found that
the Lombard slope could vary in the range 0.5 to 0.7
(unit dB/dB). Already in 1962 Webster & Klumpp found
that the Lombard slope was 0.5 [7]. The same result
was reported in 1971 by Gardner [8] based on several
cases of dining rooms and social-hour type of
assembly. Bronkhorst [9] made a review paper and he
conrmed the Lombard slope of 0.5 with reference to a
study by Lane and Tranel [10].
In 1959 MacLean [11] presented a simple formula for
the signal-to-noise ratio of conversation in a party with
“well-mannered guests” (only one talker at any time in
each group of people). Based on this he could show
that there is a maximum number of guests compatible
with a quiet party. When this number is exceeded the
party becomes a loud one.
Tang et al. [12] suggested a prediction model for noise
in an occupied room with repeated iterations by
assuming a raised voice level due to the ambient noise,
which again increases due to the raised voice level.
Measurements in a canteen were also reported, with
number of occupants varying from very few and up to
around 300 while the measured A-weighted sound
pressure level (SPL) varied from 57 dB to 75 dB. They
applied the absorption of 0.44 m2 per person, but the
absorption per person was found to have very little
inuence on the predicted noise level.
Kang [13] used a computer model and the radiosity
method to predict sound pressure levels in dining
spaces. A constant sound power from all speakers was
assumed. A parametric study was carried out to
examine the basic characteristics of conversation
intelligibility in dining spaces and to study the effect of
increasing sound absorption, area per person, ceiling
height etc.
Navarro & Pimentel [14] reported the relationship
between number of people and the measured sound
pressure level due to the noise from speech in two
large food courts. In one foot court the measured
A-weighted SPL was up to 74 dB with around 345
people. In the other foot court with around 540 people
was measured up to 80 dB. Attempts to explain the
results by a simplied analytical model showed some
similarities with the measured results assuming raised
vocal effort and an average group size of either 2 or 4
people per talker.
Hodgson et al. [15] measured noise levels in ten eating
establishments and reported A-weighted SPL between
45 dB and 82 dB. They also described an iterative
model for predicting the noise levels including the
Lombard effect. Using an optimization technique they
found the best estimates for some unknown parameters
in the model, e.g. that sound absorption per person
varied between 0.1 m2 and 1 m2, the Lombard slope
was on average 0.69, and the group size was around 3.
Astol & Filippi [16] reported measurements in four
Italian restaurants with volumes between 99 m3 and
191 m3 and seating capacity between 29 and 88.
Measured A-weighted SPL was between 67 dB and 76
dB, depending on the number of persons in the
restaurant. Attempts were made to evaluate speech
intelligibility and speech privacy.
To & Chung [17] did measurements of noise levels in
twelve Hong Kong restaurants having volumes from
Table 1. Statistics of replies to the question: How often is it difcult to have a conversation in
canteens, restaurants and cafés due to noise from speech? Data from [3].
Hearing impaired Visually impaired
Number Percent Number Percent
Often / always 129 51 % 49 23 %
Sometimes 92 37 % 59 28 %
Seldom 22 9 % 34 16 %
Never 8 3 % 70 33 %
Total 251 100 % 212 100 %
No reply 20 38
N 271 250
RestauRant acoustics – VeRbal communication in eating establishments
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Acoustics in Practice, Volume 7, Year 2019, No. 1
455 m3 to 12 000 m3. They found that the main
parameter for the noise level was the occupancy
density, and an empirical model for the noise level was
suggested. The mean values of measured A-weighted
SPL were 68.9 dB, 72.7 dB and 76.5 dB for low,
medium, and high occupancy density, respectively.
Rindel [18] derived a simple theoretical model for the
ambient noise level taking the Lombard effect into
account. The main parameters were volume per
person, reverberation time and group size. By
validation with measured data, he conrmed the
Lombard slope of 0.5 and the group size between 3
and 4 for typical restaurants. Based on this model,
Rindel suggested the acoustic capacity of a room as a
simple measure of the acoustical properties [19].
De Ruiter [20] looked at the noise level as function of
sound absorption per person in several eating
establishments and showed good agreement with
Rindel’s formula [18]. He suggested the required
amount of sound absorption in a restaurant to be
minimum 3.5 m2 per person.
Nielsen et al [21] investigated the relation between
objective acoustic parameters and subjective
evaluation of acoustical comfort in ve restaurants. A
very high correlation was found between the difculty
to hear and understand other guests at the table and
the seating density (number of people per square
meter). An equally high correlated parameter was the
number of people divided by the calculated acoustic
capacity of the space.
2. SPEAKING IN NOISE, THE LOMBARD EFFECT
The vocal effort is characterized by the A-weighted
SPL of the direct sound in front of a speaker in a
distance of 1 m from the mouth. Vocal effort is ranged
and labelled in steps of 6 dB, see Table 2. Thus normal
vocal effort corresponds to a SPL around 60 dB in the
distance of 1 m. Speech at very high vocal effort, i.e.
levels above 75 dB, may be more difcult to understand
than speech at lower vocal effort. The dynamic range
of the human voice is remarkable. By shouting, the
SPL can reach 84 dB to 90 dB, and in private
communication (whispering or soft speech) typical
levels are 35 dB to 50 dB.
The Lombard effect is named after the French
otolaryngologist Étienne Lombard (1869 1920), see
Figure 1. He was the rst one to observe and report
that persons with normal hearing raised their voice
when subjected to noise [22]. However, the Lombard
effect is not particular for humans, but has also been
found in other mammals and birds [23]. The Lombard
effect starts at a noise level around 45 dB and a speech
level of 55 dB [6, 7]. In more quiet surroundings, the
vocal effort is not inuenced by the ambient noise.
Assuming a linear relationship for noise levels above
45 dB, the speech level in a distance of 1 m can be
expressed in the equation:
LS,A,1m =55 +c(LN,A 45), (dB) (1)
where LN,A is the A-weighted SPL of the noise and c is
the Lombard slope. The frequency spectrum of speech
depends on the vocal effort [24]. As seen in Figure 2,
the spectrum changes towards the high frequencies
when vocal effort increases.
Table 2. Description of vocal effort at various speech levels (A-weighted
SPL in a distance of 1 m in front of the mouth). Adapted from Lazarus [5]
Table 3.
LSA,1m dB Vocal effort
36 Whispering
42 Soft
48 Relaxed
54 Relaxed, normal
60 Normal, raised
66 Raised
72 Loud
78 Very loud
84 Shouting
90 Maximal shout
96 Maximal shout (individual)
Figure 1. Etienne Lombard (1869 – 1920). The discoverer of the Lombard effect
(Photo, Paul Berger).
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4Acoustics in Practice, Volume 7, Year 2019, No. 1
3. HEARING IN NOISE, THE COCKTAIL
PARTY EFFECT
Listening to voices at a social gathering is a very
interesting situation that challenges our hearing
system. Due to the ability of a normal hearing person to
localize a sound source in the surrounding 3D space, it
is possible to focus on one out of many voices, and to
catch what one person says, while the other voices are
suppressed as background noise.
This so-called “cocktail party effect” was rst reported
1953 by Cherry [25] as a result of laboratory
experiments. The test subjects had two different
messages applied to the two ears through headphones,
and he reported no difculty in listening to either
speech at will and “rejecting” the unwanted one. The
phenomenon was further analysed by MacLean [11].
An overview of later research in the cocktail party effect
is found in the review paper by Bronkhorst [9].
4. PREDICTION MODELS
4.1. A simple prediction model for the speech noise level
A calculation model for the ambient noise level was derived
by Rindel [13] applying simple assumptions concerning
sound radiation and a diffuse sound eld in the room. The
prediction model was veried by comparison with
measured data for a varying number of persons between
50 and 540 in two large foot courts and in a canteen [14,
15]. In the comparison with these data it became clear that
the Lombard slope had to be 0.5; this was the only value
that made a reasonable good t between the experimental
data and the simple prediction model.
The suggested simple prediction model can be
expressed in the equation:
LN,A =93 20lg
A
NS
=93 20lg
Ag
N
, (dB) (2)
where A is the equivalent absorption area (in m2) and
NS is the number of simultaneously speaking persons.
This relationship is shown in Figure 3. The group size g
is introduced in the second equation. Since only the
total number of people N present in the room is known,
it is convenient to introduce the group size, dened as
the average number of people per speaking person,
g = N / NS. The interesting consequence of Equation 2
is that the ambient noise level increases by 6 dB for
each doubling of number of individuals present. The
same result was found by Gardner [8].
If the room has the volume V (m3), the reverberation
time in unoccupied state is T (s), and assuming a
diffuse sound eld, the Sabine equation gives the
following estimate of the equivalent absorption area
including the contribution to the absorption from N
persons:
A=0.16V
T
+ApN, (m2) (3)
where Ap is the sound absorption per person in m2.
This depends on the clothing and typical values are
from 0.2 m2 to 0.5 m2. The contribution of absorption
from persons is negligible if the ambient noise level is
sufciently low. Below 73 dB, it follows from Equation
(2) that the room has a total absorption area per person
around 10/g, i.e. approximately 3 m2 with a typical
group size of 3.5. Thus, the absorption from the
persons’ clothing should be taken into account when
the noise exceeds 73 dB.
It is obvious that noise from speech where many people
are gathered cannot be predicted with a high accuracy,
simply because there are unknown parameters related
to individual differences and how much people actually
Figure 2. Speech spectra for different levels of vocal effort. Values at 250 Hz to
8 kHz are calculated from ANSI 3.5 [24]. Values at 63 Hz and 125 Hz from [27].
Figure 3. A-weighted SPL of ambient noise and of speech in a distance of 1 m in
front of the mouth, both as functions of the sound absorption area per speaking
person. (Figure courtesy of EuroNoise 2015 [1]).
RestauRant acoustics – VeRbal communication in eating establishments
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Acoustics in Practice, Volume 7, Year 2019, No. 1
want to talk. This may depend on the type of gathering,
which can be more or less lively, how well people know
each other, age of the people, consumption of alcohol,
and other social circumstances.
With the suggested prediction model, Equation (2), it is
possible to calculate the expected noise level from the
volume, reverberation time and number of people
gathered in the room. The uncertainty is mainly related
to the group size, and from the cases that have been
studied it appears that a group size of 3 to 4 is typical
for most eating establishments and a value of g = 3.5 is
recommended for the noise prediction in restaurants.
The accuracy of the prediction depends on how close
the assumed group size is to the actual group size. If
the actual group size varies between 2.5 and 5, it
means a total variation of 6 dB. This in turn means that
the prediction method may have an uncertainty of ± 3
dB. The prediction model is based on statistical
conditions meaning that it may not apply to small
rooms with a capacity less than, say 30 persons.
4.2. A prediction model for the quality of vocal
communication
The quality of vocal communication is related to the
signal-to-noise ratio, dened as the difference between
the A-weighted SPL of the direct sound from a speaking
person in a certain distance r and the ambient noise in
the room. Thus, the SNR in the distance of 1 m is the
difference between the two curves shown in Figure 3.
The signal-to noise ratio is not inuenced by the
Lombard effect, because we can assume that on
average all speaking persons in the room use the same
vocal effort. The increase in vocal effort due to ambient
noise is the same for the speaker we are listening to
and for all the other speaking persons in the room. The
signal-to-noise ratio in the distance r can be calculated
from the absorption area per person (A/N) and the
group size g:
SNR =LS,A LN,A =10lg Q A g
16
π
r2N
, (dB) (4)
where Q is the directivity of a speaking person (Q = 2 is
assumed in front of the mouth). This formula applies to
A-weighted ambient noise levels between 45 dB and
85 dB, or a range of speech levels between 55 dB and
75 dB. The corresponding SNR range is from – 10 dB
to +10 dB.
A result very similar to Equation (4) was derived by
Pierce [26] pp 276-277. He assumed that people were
grouped as shown in Figure 4 and that one and only
one person was speaking in each group. The distance
between the groups was assumed sufciently large, so
sound from other groups could be considered in a
reverberant sound eld.
For the evaluation of the acoustics, we can apply the
quality of verbal communication, which is related to
SNR, see Lazarus [6]. Thus a SNR between 3 dB and
9 dB is characterized as “good”, the range between 0
dB and 3 dB is “satisfactory”, and SNR below -3 dB is
“insufcient”, see Table 3. It is suggested to focus on
the border between sufcient and insufcient, i.e.
SNR = 3 dB, as a minimum requirement for acoustical
design of restaurants. Figure 5 shows how the SNR in
a distance of 1 m depends on the volume and
reverberation time, and the importance of sufcient
volume per person is obvious.
These considerations may be valid for normal hearing
people. However, ISO 9921 [4, Section 5.1] states
that “people with a slight hearing disorder (in general
the elderly) or non-native listeners require a higher
signal-to-noise ratio (approximately 3 dB)”. This
improvement is relative to that required for normal-
hearing listeners, and thus for this group of people a
SNR 0 dB should be applied to represent “sufcient”
conditions, and SNR 3 dB to represent “satisfactory”
conditions.
Figure 4. Social gathering. People have conversations in groups, and r is the
distance between speaker and listener. Reproduced from Pierce, A.D. Acoustics.
An Introduction to Its Physical Principles and Applications. 2nd Edition. Acoustical
Society of America, New York, 1989. [26] p. 277 with permission from the
Acoustical Society of America.
Table 3. Quality of verbal communication, dependent on the signal-to-
noise ratio. Adapted from Lazarus [6] Table 2.
Quality of verbal communication SNR dB
Very bad < 9
Insufcient (9; 3)
Sufcient (3; 0)
Satisfactory (0; 3)
Good (3; 9)
Very good > 9
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6Acoustics in Practice, Volume 7, Year 2019, No. 1
The quality of communication can be improved if the
listener can come closer to the speaking person.
Reducing the distance from 1 m to 0.7 m means a 3 dB
better SNR, and coming as close as 0.5 m yields another
3 dB improvement. This is the obvious solution for
maintaining communication in a too noisy environment,
but it does not change the noise level, which makes the
environment unpleasant for a longer stay.
4.3. A computer model for arbitrary spaces
In some cases, the space is highly irregular and volume
is not well dened. Then it may be necessary to replace
the simple prediction Equation (2) by a computer
simulation. Instead of assumptions of the room volume
and reverberation time, the room geometry is modelled
and appropriate absorption data are assigned to the
surfaces according to the materials.
The relation between the sound power level of a point
source and the SPL in a receiver point is the transfer
function of the room. The principle in the computer model
is to calculate a transfer function from a surface source
that covers the total area with speaking persons to a
receiver grid covering the same area. The calculations
are made in eight frequency bands from 63 Hz to 8 kHz
and the surface source should have the spectrum of
speech, preferably corresponding to the vocal effort that
is assumed, see Figure 2. The median value of the
A-weighted SPL in the receiver grid is used together with
the total sound power emitted from the surface source to
calculate the surface transfer function. This is the
response of the room to the speech noise with the chosen
location of the sources and receivers. The surface transfer
function is independent of the level of sound power of the
source. Assuming a certain number of people and a
group size (e.g. 3.5), the ambient noise can be calculated.
Further details about this method are found in [27].
5. CASES
5.1. Canteen
This case is based on measured data reported by Tang
et al. [12] and is quoted from Rindel [18] with permission
from Elsevier (License number 4238680339894). The
noise level was measured continuously in a canteen
for 2.5 h during lunch time, where the number of people
increased in the rst hour from nil to around 250 (see
Figure 6, measurement A). During the later 1.5 h the
number of people gradually decreased, but the noise
level did not decrease as much as could be expected
(see Figure 6, measurement B). At the end of the
measurement period, around 50 people were left, but
the noise level was about 5 dB higher than with the
same number of people at the beginning. The canteen
had a volume of 1 235 m3 and the unoccupied
reverberation time 0.47 s at mid frequencies. The
measured results are compared with the prediction
model, Equation (2) using the sound absorption per
person Ap = 0.2 m2, and different values of the group
size. The best overall agreement with the prediction
model is obtained with a group size of 3.5. However, in
Measurement A between 150 and 250 people, a very
good agreement is obtained with a group size of 4,
indicating that people are not talking so much in the
beginning of the lunch, whereas the later part of the
lunch represented by Measurement B matches better
with a group size of 3, i.e. more people talking. Thus, it
is clear that the group size should not be considered
constant, but varies according to the social character of
the gathering.
5.2. Reception at a conference
In connection with an acoustical meeting in Krakow,
September 2014, a welcome party and a farewell
Figure 5. Quality of verbal communication as function of room volume per person
and reverberation time. (Figure courtesy of EuroNoise 2015 [1]).
Figure 6. Measured and predicted noise level for a canteen as a function of the
number of people present. Measurement A: rst period with increasing number
of people; Measurement B: second period with decreasing number of people.
Measured data from Tang et al. [12]. The parameter on the predicted curves
is the group size, g.
RestauRant acoustics – VeRbal communication in eating establishments
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Acoustics in Practice, Volume 7, Year 2019, No. 1
reception were held in the main building of AGH
University of Science and Technology. The main foyer
is a high room with volume approximately above
8 000 m3 and reverberation time around 4 s at mid
frequencies, see Figure 7A. At the welcome party, the
room was crowded and very noisy due to speech from
several hundreds of people and additional background
music (voice and piano). It was extremely difcult to
have a conversation during this gathering. The SPL
was not measured at that time, but at the farewell
reception in the same room, the sound level was
measured, and within a period of 15 minutes the LA,eq
was 77 dB. Just before the reception, there was a
closing ceremony with 260 participants, so it is
assumed that the number of people attending the
farewell party was around 250, or a little less, see
Figure 7B. Using Equations (2) and (3) with
Ap = 0.35 m2 yields 78 dB, i.e. very close to the
measured level. With the same equations, and
estimating the number of people at the welcome party
to be between 500 and 1000, the SPL would have
been around 82 dB to 85 dB, see Table 4.
5.3. Banquet in several large rooms
In May 2011 a banquet was held at the Technical
University of Denmark on the annual celebration with
hundreds of people dining in several, separate rooms.
During the evening, the sound level was monitored in
three rooms with very different acoustical conditions.
The results were compared with those obtained with the
prediction method using a computer model, see Table 5.
The number of seats in the three halls was 480, 530 and
360, respectively. Hall A was a very long, wide corridor
with ceiling height 3.6 m. The surfaces are stone,
concrete and glass and the mid-frequency reverberation
time (with tables, but without people) was 2.5 s. Only a
part of this hall was used for the banquet. Hall B was a
canteen with ceiling height 3.0 m and mid-frequency
reverberation time 0.8 s. The geometry was complicated
and the volume not well dened. Hall C was a nearly
square hall with glass walls, the ceiling height is 4.35 m
and mid-frequency reverberation time 1.0 s. Photos
from the latter is seen in Figure 8.
Table 4. Calculated and measured ambient noise during social gatherings
in the AGH hall.
Volume V, m38 265
Reverberation time, T, s 3.9
Number of people N250 500 1 000
Calculated LN,A, dB 78 82 85
Measured LA,eq,15 min , dB 77 – –
(a)
Figure 7. The hall in the main building of AGH University of Science and Technology, Krakow. (a) The empty hall; (b) A photo from the farewell reception.
(b)
Table 5. Measured and calculated ambient noise during a banquet in
three halls.
Hall A Hall B Hall C
Volume V, m3N/A N/A 1 605
Reverberation time, s 2.5 0.8 1.0
Number of people N480 530 380
Measured LA,eq,2 h , dB 87 83 83
Calculated (simulation) LN,A, dB 88 83 83
Calculated (simple) LN,A, dB 82
RestauRant acoustics – VeRbal communication in eating establishments
8Acoustics in Practice, Volume 7, Year 2019, No. 1
The sound was monitored between 19:00 and 22:00,
using three measurement positions under the ceiling in
each hall. During the rst half hour, the noise increases
signicantly (15 dB to 20 dB) but after that the level is
relatively stable for several hours. An example from
Hall C is seen in Figure 9. The results in Table 5 are
averaged over two hours between 20:00 and 22:00.
The predicted noise levels in the three different halls
deviate 1 dB or less from the measured noise levels.
Assumed group size was 3.5.
6. ACOUSTIC CAPACITY AND QUALITY
OF VERBAL COMMUNICATION
6.1. The concept of acoustic capacity
The above ndings can be used for a room with known
absorption area to estimate the maximum number of
persons in order to keep a certain quality of verbal
communication. So, it is suggested to introduce the
concept of acoustic capacity for an eating establishment,
dened as the maximum number of persons in a room
allowing sufcient quality of verbal communication
between persons (in a distance of 1 m).
Sufcient quality of verbal communication requires that
the ambient noise level is no more than 71 dB, which
means that the average SNR in a distance of 1 m is at
least –3 dB, see Table 3. A simplied approximation
derived from Equation (2) yields that the number of
persons corresponding to 71 dB, i.e. the acoustic
capacity:
Nmax V
20T (5)
where V is the volume in m3 and T is the reverberation
time in seconds in furnished but unoccupied state at mid
Figure 8. Hall C used for the banquet at the Technical University of Denmark. (a) The hall with tables and chairs before the banquet; (b) Same hall during the banquet.
(a) (b)
Figure 9. Measured A-weighted SPL in Hall C during the banquet.
RestauRant acoustics – VeRbal communication in eating establishments
9
Acoustics in Practice, Volume 7, Year 2019, No. 1
frequencies (500 Hz to 1000 Hz). Here is used group
size g = 3.5 and absorption per person Ap = 0.35 m2.
Figure 10 shows the ambient noise level as function of
the number of persons relative to the acoustic capacity.
When a restaurant is fully occupied, it is typical that the
acoustic capacity is exceeded by a factor of 2 or more.
This means that the quality of verbal communication is
insufcient in a standard distance of 1 m. However,
other distances may apply, but this depends on the
size of the tables.
6.2. Table size and distance of communication
Table 6 gives the SNR as function of ambient noise
level and distance of communication. The most
important cells in the table are those with SNR = 3 dB,
because this is the limit for sufcient quality of verbal
communication. In the distance r = 1.0 m the
corresponding ambient noise level is 71 dB.
Examples of tables in a restaurant are shown
schematically in Figure 11. Sitting at a long table you
can have a conversation with the person next to you
(r = 0.5 m) or across the table (r = 0.7 m to 1.0 m)
where distance depends on the width of the table. The
round table for 10 people is very common in a banquet,
and having a conversation across the table (r = 2 m) is
often quite impossible, as this would require a noise
level of maximum 59 dB. However, conversations may
be possible between three persons (r = 1.0 m and
r = 0.5 m). If the noise level goes up to 77 dB, it is only
possible to speak with the person sitting next to you.
Similarly, we get the typical distances of conversation
for the other tables in Figure 11; round table with six
people (r = 1.4 m), square table with four people
(r = 1.0 m), and a small table with two people (r = 0.7
Figure 10. Ambient noise level as a function of the number of people relative to the
acoustic capacity of the room. The corresponding quality of verbal communication
in a distance of 1 m is also indicated. (Figure courtesy of EuroNoise 2015 [1]).
Figure 11. Examples of tables with indication of distances of verbal
communication. (a) Long table, typical distances 1.0 m and 0.5 m; (b) Round table
for ten, typical distances 2.0 m, 1.0 m and 0.5 m; (c) Round table for six, typical
distance 1.4 m; (d) Square table for four, typical distance 1.0 m; (e) Square table
for two, typical distance 0.7 m.
Table 6. Quality of verbal communication in terms of calculated SNR as function of distance
and ambient noise level.
SNR (dB) - quality of verbal communication
Distance Ambient noise level, LN,A, dB
r, m 53 59 65 71 77 83 89
0.35 15 12 9 63 0 –3
0.5 12 9 63 0 –3 –6
0.7 9 63 0 –3 –6 –9
1.0 6 3 0 –3 –6 –9 –12
1.4 3 0–3 –6 –9 –12 –15
2.0 0 –3 –6 –9 –12 –15 –18
RestauRant acoustics – VeRbal communication in eating establishments
10 Acoustics in Practice, Volume 7, Year 2019, No. 1
m). These distances are of course approximate and
rounded to match the examples shown in Table 6.
6.3. Background music
Background music is typically instrumental music
played at a low level. It is not meant to be in the focus
of an audience, but rather to ll the gaps of silence,
that might occur. When used in restaurants and at
social gatherings it should be played at a sufciently
low sound level, so it is not disturbing for normal vocal
communication. Background music can have a
masking effect, which contributes to a feeling of
privacy in the meaning that a private conversation is
not easily overheard by other people in the room.
Thus, it may happen that people stop talking if
the background music is stopped. Recommended
maximum SPL of background music is around 60 dB
to 65 dB.
Foreground music is played at higher levels than
background music, and is meant to be noticed and
enjoyed as entertainment [28]. The audience is not
supposed to talk during the music. Recommended
maximum SPL of foreground music is in the range of
75 dB to 90 dB.
In a restaurant or at a social gathering the music
contributes to the ambient noise level, which means an
increase of vocal effort in conversations. Thus, the
Lombard effect applies to the total noise level due to
music and speech. Solving the problem leads to the
following equation for the total noise level
LN,Total =10lg EM+0.5EN1+1+4EM
EN
, (dB) (6)
where the average SPL of the music is 10 lg(EM) and
the SPL of ambient noise from speech without music is
10 lg(EN). The latter is the SPL given in Equation (2).
From this result, it is straightforward to estimate the
vocal effort, Equation (1) and the SNR with background
music or other background noise.
Figure 12 shows the SNR as function of the ambient
noise level without music, but with the sound level of
the background music as a parameter. If the level of
the music does not exceed 65 dB the quality of vocal
communication can be sufcient (SNR > –3 dB), but of
course only when the room is not too crowded (actually
if N < 0.7 · Nmax). For a satisfactory quality of verbal
communication, the background music should not
exceed 60 dB.
7. SUGGESTED ACOUSTICAL
REQUIREMENTS FOR RESTAURANTS
The adaptation of the universal design concept [2]
means that it is necessary to dene acoustical
requirements for restaurants, canteens and other
public eating facilities. The key parameters that control
the acoustical conditions are volume V, reverberation
time T and number of people N, i.e. number of seats.
The graphical presentation in Figure 13 is based on
Equation (4), which yields the SNR as function of
V/(N T) and the distance of verbal communication r.
In the reference distance r = 1.0 m we have V/(N
T) = 20 for the borderline between sufcient and
insufcient quality of vocal communication, so this
might be taken as basis for the acoustical requirement.
However, this might be too strict because a restaurant
is seldom fully occupied. An 80 % occupancy may be
considered a more realistic basis for the requirement.
Then the required reverberation time yields:
T1
0.80 ×20
V
N
0.063 V
N
, (s) (7)
This shows that the requirement must be related to the
volume per person, which means that it is necessary to
know the maximum number of seats in the room. In
some cases, this maximum number has to be accepted
by the re authorities, and an emergency escape plan
that states the allowed maximum number of guests
must be mounted clearly visible in the room. In other
cases, the intended maximum number of occupants is
provided on the architect’s drawing. In order to full the
acoustical requirement there are three possibilities to
consider:
Figure 12. The inuence of background music on the quality of verbal
communication. The curves represent levels of music from 50 dB to 75 dB
in steps of 5 dB. (Figure courtesy of EuroNoise 2015 [1]).
RestauRant acoustics – VeRbal communication in eating establishments
11
Acoustics in Practice, Volume 7, Year 2019, No. 1
1. The volume should be as big as possible. Some
acoustically good restaurants have a high ceiling. This
is something to consider in the early stage of planning.
2. Sound absorbing materials must be applied on
surfaces where it is possible. The ceiling is obvious,
but often parts of the walls must also be included. A
thick carpet can also add more sound absorption,
but in many cases, this is not an option.
3. The seating plan should not be too crowded. The
easy solution is to make a seating plan with a
number of seats that does not exceed the acoustic
capacity by more than 25 %.
Some countries use sound classication for buildings,
e.g. four classes A, B, C, and D where class A is best,
class C is minimum requirements for new buildings, and
class D is applicable for older buildings. Table 7 contains
suggested requirements for the reverberation time in
restaurants in four classes. These sound classes are
indicated in Figure 13. Table 7 also shows the quality of
verbal communication in terms of SNR in a distance of
1 m for different percentages of occupancy. For instance,
100 % occupancy in class A gives SNR = 0 dB, which is
the borderline between satisfactory and sufcient. The
same is obtained in class C with 40 % occupancy.
8. CONCLUSIONS
For the characterization of the acoustical conditions in
restaurants and similar environments, the quality of verbal
communication is applied in addition to the ambient noise
level. A signal-to-noise ratio of -3 dB for a speaker in a
distance of 1 m corresponding to an ambient noise level of
71 dB is suggested as a realistic basis for design criteria.
This leads to a combined requirement for the reverberation
time and the volume; the volume per person should be at
least T ×20 m3, where T is the reverberation time. Thus,
the reverberation time should be as short as possible, but
still a sufcient volume is a physical necessity for
satisfactory acoustical conditions. It should be noted that
for hearing impaired people and non-native speakers, the
acoustical needs are stronger and a better SNR is needed
for an acceptable quality of verbal communication.
It is obvious that the acoustical problems depend strongly
on the number of people present in the room. So, in
addition to the design guide for the acoustical treatment
of rooms, it is suggested to introduce the acoustic
capacity of a room. This is a simple way to indicate which
number of persons should be accepted in order to obtain
sufcient quality of verbal communication. In other
words, if the number of people in the room exceeds the
acoustic capacity, the ambient noise level may exceed
71 dB and the quality of verbal communication in a
distance of 1 m is insufcient.
Figure 13. Quality of verbal communication at function of distance and
the parameter V/(N T). Suggested acoustical requirements in four sound classes
are shown with dotted lines.
Table 7. Suggested minimum requirement reverberation time in restaurants in four sound classes. The SNR in a distance of 1 m is shown as a function of the
occupancy (number of people in percentage of the total number of seats).
Sound class Class A Class B Class C Class D
Reverberation time / volume per person
(s/m3)0.025 0.040 0.063 0.100
Occupancy SNR (dB) in 1 m distance
100 % 0–2 –4 –6
80 % 1–1 –3 –5
63 % 2 0 –2 –4
50 % 3 1 –1 –3
40 % 4 2 0 –2
32 % 5 3 1 –1
25 % 6420
RestauRant acoustics – VeRbal communication in eating establishments
12 Acoustics in Practice, Volume 7, Year 2019, No. 1
Both a simple prediction model and an advanced
computer-based model for the ambient noise due to
speech have been described. The models consider the
Lombard effect, and have been veried for several test
cases. In the design stage when alternative solutions
for the acoustic design of a restaurant or similar facility
are considered, the acoustic capacity may be a good
parameter to present to architects, in addition to the
calculated reverberation time or ambient noise level.
This has already been used successfully in several
projects, and it is clear that the maximum number of
persons to allow sufcient acoustical conditions is
much easier to understand for non-acousticians than
noise levels or reverberation times.
For the owners of restaurants it may be interesting to
know that the perception of food and drink is inuenced
by the ambient noise in the room, see Appendix A.
However, the results go in opposite directions. In a ne
restaurant the noise should be kept at a low level in
order to maintain the taste qualities in the food. But for
the owner of a bar, where the guests mainly come for
drinks, a noisy environment means that more drinks
are consumed in a shorter time. So, the quality of
verbal communication might be less important in bars
and a higher noise level (and thus a higher level of
arousal) acceptable or maybe even wanted.
When music is played in restaurants or at social gatherings,
it is important to distinguish between background music
and foreground music. While foreground music is meant to
catch the attention, background music should not interfere
too much with verbal communication, and a maximum
sound level of 60 dB is suggested.
ACKNOWLEDGEMENTS
Measurements in case 5.2 were made by Andrzej
Kłosak from Krakow University of Technology, Poland.
The measurements in case 5.3 were made by Anders
Chr. Gade, Gade & Mortensen Akustik A/S, Denmark.
APPENDIX A. DRINKING AND EATING IN
NOISY ENVIRONMENTS
It is a widespread assumption that the noise level of a
party increases with the amount of alcohol consumed.
However, no proof of this is found in the scientic
literature. Never the less there is no doubt that a
relation exists between noise and alcohol consumption.
Guéguen et al. [29] studied the drinking behaviour in
bars as function of the sound level of music, either at
“usual” level, 72 dB to 75 dB, or at a typical level of
“foreground” music, 88 dB to 91 dB. With the high
sound level, signicantly more drinks were consumed,
the mean value for 60 persons being 3.7 versus 2.6
drinks at the usual level. The authors have suggested
an “arousal” hypothesis to explain the ndings; the high
sound level leads to higher arousal, which stimulates to
drink faster and to order more drinks. In a later follow-
up study [30] it was conrmed that the average time
spent to drink a glass of beer decreased from (14.5 ±
4.9) minutes with usual level of music (72 dB) to (11.5 ±
2.9) minutes with high level of music (88 dB).
Stafford et al. [31] have found that music and other
forms of distraction leads to increase in alcohol
consumption. In addition, they found that sweetness
perception of alcohol was signicantly higher in the
music compared to no music and other distraction
conditions. The study gives support to the general
distraction theory that noise disrupts taste and smell.
The effect of noise on food perception was studied by
Woods et al. [32]. Test persons were exposed to white
noise at levels of 45 dB to 55 dB (Quiet) and 75 dB to
85 dB (Loud), in addition to a no-noise condition. The
ratings of sweetness and saltiness were inuenced by
the noise, and the food was reported to taste less
intense in the noisy condition. This might be interesting
news for owners of good restaurants, and it certainly
gives a new twist to the discussion of the importance of
good acoustics in restaurants.
Fiegel et al. [33] have found that background music
can alter food perception, and that the effect depends
on the music genre (classical, jazz, hip-hop, rock).
They used the same SPL of the music in all cases,
namely 75 dB. Especially in the presence of jazz
stimulus, avour pleasantness and overall impression
of the food stimuli increased.
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... For restaurants where patrons socialize in small groups, the acoustic design calls for a less reverberant space with an appropriate density and layout of seats and consideration of other expected noise sources, such as an open kitchen or continuous background music. Investigations focused on how restaurant sound levels change in time with occupancy [89] are helping to validate proposed restaurant noise prediction models [90]. In hospitals where patients are recovering from health issues, the acoustic environment must support as much uninterrupted sleep as possible. ...
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