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Restaurant Acoustics – the Science behind Verbal Communication in Eating Establishments

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Abstract and Figures

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 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 simplified model assuming a diffuse sound field and as an advanced computer simulation model. The concept ‘Acoustic Capacity’ of a facility is introduced, 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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Article 1
Restaurant acoustics – the science behind verbal 2
communication in eating establishments 3
Jens Holger Rindel 4
Multiconsult, Post Box 265 Skøyen, N-0213 Oslo, Norway; jehr@multiconsult.no 5
Correspondence: jehr@multiconsult.no; Tel.: +47-9801 5949 6
Featured Application: The research results may be used for the acoustical design of restaurants and 7
other rooms for social gathering. 8
Abstract: A well-known but also very complicated problem in room acoustics is the ambient noise 9
when many people are gathered for a reception or in a restaurant, a bar, a canteen or a similar place. 10
In such social gatherings, people want to speak with each other, but for the same reason the place 11
can be very noisy, and verbal communication can be difficult or even impossible, especially for 12
people with reduced hearing capacity. The noise depends on at least the following parameters; the 13
volume, the reverberation time, the number of people, and the type gathering. Verbal 14
communication in a noisy environment is a complicated feed-back situation, which implies two 15
interesting phenomena; the Lombard effect and the cocktail-party effect. Solutions are presented 16
both as a simplified model assuming a diffuse sound field and as an advanced computer simulation 17
model. The concept ‘Acoustic Capacity’ of a facility is introduced, defined as the maximum number 18
of persons in order to achieve a sufficient quality of verbal communication. In order to avoid poor 19
acoustics in restaurants and similar places, it is necessary to design with bigger volume and more 20
absorption material than usual in current building design practice. 21
Keywords: Verbal communication; Lombard effect; Cocktail party effect; Noise; Acoustic capacity; 22
Universal design 23
24
25
26
27
This paper is based on a plenary paper presented at the EuroNoise 2015 conference [1], but 28
extended and with more figures and added discussion of possible applications. The organizing 29
committee of EuroNoise 2015 has granted copyright permission for the reuse of this material. 30
1. Introduction 31
Noise from people speaking in restaurants and at social gatherings is often a nuisance because 32
it can be very loud, and a conversation may only be possible with a raised voice level and in a short 33
distance. Because of the noise and the difficulties associated with a conversation, the visitors may 34
leave the place with a feeling of exhaustion or headache. Elderly people or those with reduced 35
hearing ability may find verbal communication impossible. 36
In many countries, there is a growing awareness of the concept called universal design, which 37
means accessibility for all in public buildings [2]. This is not limited to the physical access to a 38
building, but includes also the acoustical conditions, which should be suitable for everybody. A 39
recent investigation in Norway had the aim to throw light on the problems due to the acoustical 40
conditions in various kinds of rooms and spaces for people with impaired hearing or vision [3]. It 41
was found that the acoustical problems were particularly pronounced in canteens, restaurants and 42
cafés and 52 % of people with impaired hearing were severely or much disturbed by noise in these 43
places. The data in Table 1 show that 51 % of the people with impaired hearing report “often/always” 44
difficulties having a conversation in these places. If “sometimes” is included, the percentage increases 45
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to 88 %. For the people with impaired vision (but normal hearing) the percentage having difficulties 46
with conversations in the same kind of places “often/always” and “sometimes” is 51 %. 47
Table 1. Statistics of replies to the question: How often is it difficult to have a conversation in canteens, 48
restaurants and cafés due to noise from speech? Data from [3]. 49
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
50
In a noisy party, everyone raises the voice to be heard better, which again leads to a higher 51
ambient noise level. This effect is the Lombard effect. The average relationship between speech level 52
and ambient noise level (the Lombard slope) is mentioned in International Standard ISO 9921 [4] and 53
the possible range of the slope is given in a graph. Lazarus [5, 6] made a review of a large number of 54
investigations, and he found that the Lombard slope could vary in the range 0.5 to 0.7 (unit dB/dB). 55
Already in 1962 Webster & Klumpp found that the Lombard slope was 0.5 [7]. The same result was 56
reported in 1971 by Gardner [8] based on several cases of dining rooms and social-hour type of 57
assembly. Bronkhorst [9] made a review paper and he confirmed the Lombard slope of 0.5 with 58
reference to a study by Lane and Tranel [10]. 59
MacLean [11] presented in 1959 a simple formula for the signal-to-noise ratio of conversation in 60
a party with “well-mannered guests” (only one talker at any time in each group of people). Based on 61
this he could show that there is a maximum number of guests compatible with a quiet party. When 62
this number is exceeded the party becomes a loud one. 63
Tang et al. [12] suggested a prediction model for noise in an occupied room with repeated 64
iterations by assuming a raised voice level due to the ambient noise, which again increases due to the 65
raised voice level. Measurements in a canteen were also reported, with number of occupants varying 66
from very few and up to around 300 while the measured A-weighted sound pressure level (SPL) 67
varied from 57 dB to 75 dB. They applied the absorption of 0.44 m2 per person, but the absorption per 68
person was found to have very little influence on the predicted noise level. 69
Kang [13] used a computer model and the radiosity method to predict sound pressure levels in 70
dining spaces. A constant sound power from all speakers was assumed. A parametric study was 71
carried out to examine the basic characteristics of conversation intelligibility in dining spaces and to 72
study the effect of increasing sound absorption, area per person, ceiling height etc. 73
Navarro & Pimentel [14] reported the relationship between number of people and the measured 74
sound pressure level due to the noise from speech in two large food courts. In one foot court the 75
measured A-weighted SPL was up to 74 dB with around 345 people. In the other foot court with 76
around 540 people was measured up to 80 dB. Attempts to explain the results by a simplified 77
analytical model showed some similarities with the measured results assuming raised vocal effort 78
and an average group size of either 2 or 4 people per talker. 79
Hodgson et al. [15] measured noise levels in ten eating establishments and reported A-weighted 80
SPL between 45 dB and 82 dB. They also described an iterative model for predicting the noise levels 81
including the Lombard effect. Using an optimization technique they found the best estimates for 82
some unknown parameters in the model, e.g. that sound absorption per person varied between 0.1 83
m2 and 1 m2, the Lombard slope was on average 0.69, and the group size was around 3. 84
Astolfi & Filippi [16] reported measurements in four Italian restaurants with volumes between 85
99 m3 and 191 m3 and seating capacity between 29 and 88. Measured A-weighted SPL was between 86
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67 dB and 76 dB, depending on the number of persons in the restaurant. Attempts were made to 87
evaluate speech intelligibility and speech privacy. 88
To & Chung [17] did measurements of noise levels in twelve Hong Kong restaurants having 89
volumes from 455 m3 to 12 000 m3. They found that the main parameter for the noise level was the 90
occupancy density, and an empirical model for the noise level was suggested. The mean values of 91
measured A-weighted SPL were 68.9 dB, 72.7 dB and 76.5 dB for low, medium, and high occupancy 92
density, respectively. 93
Rindel [18] derived a simple theoretical model for the ambient noise level taking the Lombard 94
effect into account. The main parameters were volume per person, reverberation time and group size. 95
By validation with measured data, he confirmed the Lombard slope of 0.5 and the group size between 96
3 and 4 for typical restaurants. Based on this model, Rindel suggested the acoustic capacity of a room 97
as a simple measure of the acoustical properties [19]. 98
de Ruiter [20] looked at the noise level as function of sound absorption per person in several 99
eating establishments and showed good agreement with Rindel’s formula [18]. He suggested the 100
required amount of sound absorption in a restaurant to be minimum 3.5 m2 per person. 101
Nielsen et al [21] investigated the relation between objective acoustic parameters and subjective 102
evaluation of acoustical comfort in five restaurants. A very high correlation was found between the 103
difficulty to hear and understand other guests at the table and the seating density (number of people 104
per square meter). An equally high correlated parameter was the number of people divided by the 105
calculated acoustic capacity of the space. 106
2. Speaking in noise, the Lombard effect 107
The vocal effort is characterized by the A-weighted SPL of the direct sound in front of a speaker 108
in a distance of 1 m from the mouth. Vocal effort is ranged and labelled in steps of 6 dB, see Table 2. 109
Thus normal vocal effort corresponds to a SPL around 60 dB in the distance of 1 m. Speech at very 110
high vocal effort, i.e. levels above 75 dB, may be more difficult to understand than speech at lower 111
vocal effort. The dynamic range of the human voice is remarkable. By shouting, the SPL can reach 84 112
dB to 90 dB, and in private communication (whispering or soft speech) typical levels are 35 dB to 50 113
dB. 114
Table 2. Description of vocal effort at various speech levels (A-weighted SPL in a distance of 1 m in 115
front of the mouth). Adapted from Lazarus [5] Table 3. 116
LSA,1m Vocal effort
dB
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)
The Lombard effect is named after the French otolaryngologist Étienne Lombard (1869 – 1920), 117
see Figure 1. He was the first one to observe and report that persons with normal hearing raised their 118
voice when subjected to noise [22]. However, the Lombard effect is not particular for humans, but 119
has also been found in other mammals and birds [23]. 120
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121
Figure 1. Etienne Lombard (1869 – 1920). The discoverer of the Lombard effect (Photo, Paul Berger).
122
The Lombard effect starts at a noise level around 45 dB and a speech level of 55 dB [6, 7]. In more
123
quiet surroundings, the vocal effort is not influenced by the ambient noise. The increase of the speech
124
level as a function of the ambient noise level is described by the rate c. Assuming a linear relationship
125
for noise levels above 45 dB, the speech level in a distance of 1 m can be expressed in the equation:
126
(dB) , )45(55
AN,m1A,S,
+= LcL
(1)
where L
N,A
is the A-weighted SPL and c is the Lombard slope. The frequency spectrum of speech
127
depends on the vocal effort [24]. As seen in Figure 2, the spectrum becomes more dominated by high
128
frequencies when vocal effort increases.
129
130
131
Figure 2. Speech spectra for different levels of vocal effort. Values at 250 Hz to 8 kHz are calculated
132
from ANSI 3.5 [24]. Values at 63 Hz and 125 Hz from [27].
133
134
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3. Hearing in noise, the cocktail party effect
135
Listening to voices at a social gathering is a very interesting situation that challenges our hearing
136
system. Due to the ability of a normal hearing person to localize a sound source in the surrounding
137
3D space, it is possible to focus on one out of many voices, and to catch what one person says, while
138
the other voices are suppressed as background noise.
139
This so-called “cocktail party effect” was first reported 1953 by Cherry [25] as a result of
140
laboratory experiments. The test subjects had two different messages applied to the two ears through
141
headphones, and he reported no difficulty in listening to either speech at will and “rejecting” the
142
unwanted one. The phenomenon was further analyzed by MacLean [11]. An overview of later
143
research in the cocktail party effect is found in the review paper by Bronkhorst [9].
144
4. Prediction models
145
4.1. A simple prediction model for the speech noise level
146
A calculation model for the ambient noise level was derived by Rindel [13] applying simple
147
assumptions concerning sound radiation and a diffuse sound field in the room. The prediction model
148
was verified by comparison with measured data for a varying number of persons between 50 and
149
540 in two large foot courts and in a canteen [14, 15]. In the comparison with these data it became
150
clear that the Lombard slope c had to be 0.5; this was the only value that made a reasonable good fit
151
between the experimental data and the simple prediction model. The suggested prediction model can
152
be expressed in the equation:
153
(dB) , lg2093lg2093
S
AN,
=
=
N
gA
N
A
L
(2)
where A is the equivalent absorption area (in m
2
) and N
S
is the number of simultaneously speaking
154
persons. This is shown in Figure 3. The group size g is introduced in the second equation. Since only
155
the total number of people N present in the room is known, it is convenient to introduce the group
156
size, defined as the average number of people per speaking person, g = N / N
S
. The interesting
157
consequence of formula 2 is that the ambient noise level increases by 6 dB for each doubling of
158
number of individuals present. The same result was found by Gardner [8].
159
160
Figure 3. A-weighted SPL of ambient noise and of speech in a distance of 1 m in front of the mouth,
161
both as functions of the sound absorption area per speaking person. (Figure courtesy of Euronoise
162
2015, Rindel [1]).
163
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If the room has the volume V (m3), the reverberation time in unoccupied state is T (s), and 164
assuming a diffuse sound field, the Sabine equation gives the following estimate of the equivalent 165
absorption area including the contribution to the absorption from N persons: 166
)(m ,
16,0 2
NA
T
V
Ap+
= (3)
where Ap is the sound absorption per person in m2. This depends on the clothing and typical values 167
are from 0.2 m2 to 0.5 m2. The contribution of absorption from persons is negligible if the ambient 168
noise level is sufficiently low. Below 73 dB, it follows from formula 2 that the room has a total 169
absorption area per person around 10/g, i.e. approximately 3 m2 with a typical group size of 3.5. Thus, 170
the absorption from the persons’ clothing should be taken into account when the noise exceeds 73 171
dB. 172
It is obvious that noise from speech where many people are gathered cannot be predicted with 173
a high accuracy, simply because there are unknown parameters related to individual differences and 174
how much people actually want to talk. This may depend on the type of gathering, which can be 175
more or less lively, how well people know each other, age of the people, consumption of alcohol, and 176
other social circumstances. 177
With the suggested prediction model (formula 2) it is possible to calculate the expected noise 178
level from the volume, reverberation time and number of people gathered in the room. The 179
uncertainty is mainly related to the group size, and from the cases that have been studied it appears 180
that a group size of 3 to 4 is typical for most eating establishments and a value of g = 3.5 is 181
recommended for the noise prediction in restaurants. 182
The accuracy of the prediction depends on how close the assumed group size is to the actual 183
group size. If the actual group size varies between 2.5 and 5, it means a total variation of 6 dB. This 184
in turn means that the prediction method may have an uncertainty of ± 3 dB. The prediction model 185
is based on statistical conditions meaning that it may not apply to small rooms with a capacity less 186
than, say 50 persons. 187
4.2. A prediction model for the quality of vocal communication 188
The quality of vocal communication is related to the signal-to-noise ratio, defined as the 189
difference between the A-weighted SPL of the direct sound from a speaking person in a certain 190
distance r and the ambient noise in the room. Thus, the SNR in the distance of 1 m is the difference 191
between the two curves shown in Figure 3. 192
The signal-to noise ratio is not influenced by the Lombard effect, because we can assume that on 193
average all speaking persons in the room use the same vocal effort. The increase in vocal effort due 194
to ambient noise is the same for the speaker we are listening to and for all the other speaking persons 195
in the room. The signal-to-noise ratio in the distance r can be calculated from the absorption area per 196
person (A/N) and the group size g: 197
(dB) ,
16
lg10SNR 2
AN,AS,
==
Nr
gAQ
LL
π
(4)
where Q is the directivity of a speaking person (Q = 2 is assumed in front of the mouth). This formula
198
applies to A-weighted ambient noise levels between 45 dB and 85 dB, or a range of speech levels 199
between 55 dB and 75 dB. The corresponding SNR range is from – 10 dB to +10 dB. 200
A result very similar to Equation 4 was derived by Pierce [26] pp 276-277. He assumed that 201
people were grouped as shown in Figure 4, and that one and only one person was speaking in each 202
group. The distance between the groups was assumed sufficiently large, so sound from other groups 203
could be considered in a reverberant sound field. 204
For the evaluation of the acoustics, we can apply the quality of verbal communication, which is 205
related to SNR, see Lazarus [6]. Thus a SNR between 3 dB and 9 dB is characterized as “good”, the 206
range between 0 dB and 3 dB is “satisfactory”, and SNR below -3 dB is “insufficient”, see Table 3. It 207
is suggested to focus on the border between sufficient and insufficient, i.e. SNR = -3 dB, as a minimum 208
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requirement for acoustical design of restaurants. Figure 5 shows how the SNR in a distance of 1 m
209
depends on the volume and reverberation time, and the importance of sufficient volume per person
210
is obvious.
211
212
Figure 4. Social gathering. People have conversations in groups, and r is the distance between speaker
213
and listener. Reproduced from A.D. Pierce: Acoustics, 1989 [26] p. 277 with permission from the
214
Acoustical Society of America.
215
Table 3. Quality of verbal communication, dependent on the signal-to-noise ratio. Adapted from
216
Lazarus [6] Table 2.
217
Quality of verbal communication SNR
dB
Very bad < -9
Insufficient (-9; -3)
Sufficient (-3; 0)
Satisfactory (0; 3)
Good (3; 9)
Very good > 9
218
219
Figure 5. Quality of verbal communication as function of room volume per person and reverberation
220
time. (Figure courtesy of Euronoise 2015, Rindel [1]).
221
These considerations may be valid for normal hearing people. However, ISO 9921 [4] section 5.1
222
states that “people with a slight hearing disorder (in general the elderly) or non-native listeners
223
require a higher signal-to-noise ratio (approximately 3 dB)”. This improvement is relative to that
224
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required for normal hearing listeners, and thus for this group of people a SNR 0 dB should be
225
applied to represent “sufficient” conditions, and SNR 3 dB to represent “satisfactory” conditions.
226
The SNR and thus the quality of communication can be improved if the listener can come closer
227
to the speaking person. Reducing the distance from 1 m to 0.7 m means a 3 dB better SNR, and coming
228
as close as 0.5 m yields another 3 dB improvement. So, this is the obvious solution for maintaining
229
communication in a too noisy environment, but it doesn’t change the noise level.
230
4.3 A computer model for arbitrary spaces
231
In some cases the space is highly irregular and volume is not well defined. Then it may be
232
necessary to replace the simple prediction (Formula 2) by a computer simulation. Instead of
233
assumptions of the room volume and reverberation time, the room geometry is modelled and
234
appropriate absorption data are assigned to the surfaces according to the materials.
235
The relation between the sound power level of a point source and the SPL in a receiver point is
236
the transfer function of the room. The principle in the computer model is to calculate a transfer
237
function from a surface source that covers the total area with speaking persons to a receiver grid
238
covering the same area. The calculations are made in eight frequency bands from 63 Hz to 8 kHz and
239
the surface source should have the spectrum of speech, preferably corresponding to the vocal effort
240
that is assumed, see Figure 2. The median value of the A-weighted SPL in the receiver grid is used
241
together with the total sound power emitted from the surface source to calculate the surface transfer
242
function. This is the response of the room to the speech noise with the chosen location of the sources
243
and receivers. The surface transfer function is independent of the level of sound power of the source.
244
Assuming a certain number of people and a group size (e.g. 3.5), the ambient noise can be calculated.
245
For further details about this method are found in [27].
246
5. Cases
247
5.1. Canteen
248
This case is based on measured data reported by Tang et al. [12]. The following text has
249
previously been published in [18] and is reused with permission from Elsevier (License number
250
4238680339894). The noise level was measured continuously in a canteen for 2.5 h during lunch time,
251
where the number of people increased in the first hour from nil to around 250 (Measurement A in
252
Fig. 6).
253
254
Figure 6. Measured and predicted noise level for a canteen as a function of the number of people
255
present. Measurement A: first period with increasing number of people; Measurement B: second
256
period with decreasing number of people. Measured data from Tang et al. [12]. The parameter on the
257
predicted curves is the group size, g. (Adapted from Rindel [18] Figure 3).
258
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In the later 1.5 h the number of people gradually decreased, but the noise level did not decrease
259
as much as could be expected, and at the end of the measurements around 50 people were left, but
260
the noise level was about 5 dB higher than with the same number of people at the beginning. The
261
canteen had a volume of 1 235 m
3
and the unoccupied reverberation time 0.47 s at mid frequencies.
262
The measured results are compared with the prediction model (Equation 2) using the sound
263
absorption per person A
p
= 0.2 m
2
, and different values of the group size g. The best overall agreement
264
with the prediction model is obtained with a group size of 3.5. However, in Measurement A between
265
150 and 250 people, a very good agreement is obtained with a group size of 4, indicating that people
266
are not talking so much in the beginning of the lunch, whereas the later part of the lunch represented
267
by Measurement B matches better with a group size of 3, i.e. more people talking. Thus it is clear that
268
the group size g should not be considered constant, but varies according to the social character of the
269
gathering.
270
5.2.Reception at a conference
271
In connection with an acoustical meeting in Krakow, September 2014, a welcome party and a
272
farewell reception were held in the main building of AGH University of Science and Technology. The
273
main foyer is a high room with volume approximately above 8000 m
3
and reverberation time around
274
4 s at mid frequencies, see Figure 7A. At the welcome party, the room was crowded and very noisy
275
due to speech from several hundreds of people and additional background music (voice and piano).
276
It was extremely difficult to have a conversation during this gathering. The SPL was not measured at
277
that time, but at the farewell reception in the same room, the sound level was measured, and within
278
a period of 15 minutes the L
A,eq
was 77 dB. Just before the reception there was a closing ceremony
279
with 260 participants, so it is assumed that the number of people attending the farewell party was
280
around 250, or a little less, see Figure 7B. Using equation (2) and (3) with A
p
= 0.35 m
2
yields 78 dB,
281
i.e. very close to the measured level. With the same equation, and estimating the number of people
282
at the welcome party to be between 500 and 1000, the SPL would have been around 82 dB to 85 dB,
283
see Table 4.
284
Table 4. Calculated and measured ambient noise during social gatherings in the AGH hall.
285
Volume V
,
m
3
8 265
Reverberation time, T, s 3.9
Number of people N 250 500 1000
Calculated L
N,A
,
dB 78 82 85
Measured L
A,eq,15 min
, dB 77 - -
286
287
288
Figure 7. The hall in the main building of AGH University of Science and Technology, Krakow. (a)
289
The empty hall; (b) A photo from the farewell reception.
290
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5.3 Banquet in several large rooms
291
A banquet was held May 2011 at the Technical University of Denmark on the annual celebration
292
with hundreds of people dining in several, separate rooms. During the evening, the sound level was
293
monitored in three rooms with very different acoustical conditions. The results were compared with
294
those obtained with the prediction method using a computer model, see Table 5.
295
Table 5. Measured and calculated ambient noise during a banquet in three halls.
296
Hall A Hall B Hall C
Volume V, m
3
N/A N/A 1 605
Reverberation time, s 2.5 0.8 1.0
Number of people N 480 530 380
Measured L
A,eq,2 h
, dB 87 83 83
Calculated (simulation) L
N,A
, dB 88 83 83
Calculated (simple) L
N,A
,
dB --82
297
The number of seats in the three halls was 480, 530 and 360, respectively. Hall A was a very long,
298
wide corridor with ceiling height 3.6 m. The surfaces are stone, concrete and glass and the mid-
299
frequency reverberation time (with tables, but without people) was 2.5 s. Only a part of this hall was
300
used for the banquet. Hall B was a canteen with ceiling height 3.0 m and mid-frequency reverberation
301
time 0.8 s. The geometry was complicated and the volume not well defined. Hall C was a nearly
302
square hall with glass walls, the ceiling height is 4.35 m and mid-frequency reverberation time 1.0 s.
303
Photos from the latter is seen in Figure 8.
304
The sound was monitored between 19:00 and 22:00, using three measurement positions under
305
the ceiling in each hall. During the first half hour, the noise increases significantly (15 dB to 20 dB)
306
but after that the level is relatively stable for several hours. An example from Hall C is seen in Figure
307
9. The results in Table 5 are averaged over two hours between 20:00 and 22:00. The predicted noise
308
levels in the three different halls deviate 1 dB or less from the measured noise levels. Assumed group
309
size was 3.5.
310
311
312
Figure 8. Hall C used for the banquet at the Technical University of Denmark. (a) The hall with tables
313
and chairs before the banquet; (b) Same hall during the banquet.
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315
Figure 9. Measured A-weighted SPL in Hall C during the banquet.
316
6. Acoustic capacity and quality of verbal communication
317
6.1 The concept of acoustic capacity
318
The above findings can be used for a room with known absorption area to estimate the
319
maximum number of persons in order to keep a certain quality of verbal communication. So, it is
320
suggested to introduce the concept acoustic capacity for an eating establishment, defined as the
321
maximum number of persons in a room allowing sufficient quality of verbal communication between
322
persons (in a distance of 1 m).
323
Sufficient quality of verbal communication requires that the ambient noise level is no more than
324
71 dB, which means that the average SNR in a distance of 1 m is at least -3 dB, see Table 3. A simplified
325
approximation derived from Equation 2 yields that the number of persons corresponding to 71 dB,
326
i.e. the acoustic capacity:
327
T
V
N
20
max
(5)
where V is the volume in m
3
and T is the reverberation time in seconds in furnished but unoccupied
328
state at mid frequencies (500 Hz to 1000 Hz). Here is used group size g = 3.5 and absorption per person
329
A
p
= 0.35 m
2
.
330
Figure 10. Ambient noise level as a function of the number of people relative to the acoustic capacity
331
of the room. The corresponding quality of verbal communication in a distance of 1 m is also indicated.
332
(Figure courtesy of Euronoise 2015, Rindel [1]).
333
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Figure 10 shows the ambient noise level as function of the number of persons relative to the
334
acoustic capacity. When a restaurant is fully occupied, it is typical that the acoustic capacity is
335
exceeded by a factor of 2 or more. This means that the quality of verbal communication is insufficient
336
in a standard distance of 1 m. However, other distances may apply, but this depends on the size of
337
the tables
338
6.2. Table size and distance of communication
339
Table 6 gives the SNR as function of ambient noise level and distance of communication. The
340
most important cells in the table are those with SNR = -3 dB, because this is the limit for sufficient
341
quality of verbal communication. In the distance r = 1.0 m the corresponding ambient noise level is
342
71 dB.
343
Examples of tables in a restaurant are shown schematically in Figure 11. Sitting at a long table
344
you can have a conversation with the person next to you (r = 0.5 m) or across the table (r = 0.7 m to
345
1.0 m) where distance depends on the width of the table. The round table for 10 people is very
346
common in a banquet, and having a conversation across the table (r = 2 m) is mostly quite impossible,
347
as this would require a noise level of maximum 59 dB. However, conversations may be possible
348
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
349
to speak with the person sitting next to you. Similarly we get the typical distances of conversation for
350
the other tables in Figure 11; round table with six people (r = 1.4 m), square table with four people (r
351
= 1.0 m), and small table with two people (r = 0.7 m). These distances are of course approximate and
352
rounded to match the examples shown in Table 6.
353
354
355
Figure 11. Examples of tables with indication of distances of verbal communication. (a) Long table,
356
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)
357
Round table for six, typical distance 1.4 m; (d) Square table for four, typical distance 1.0 m; (e) Square
358
table for two, typical distance 0.7 m
359
Table 6. Quality of verbal communication in terms of calculated SNR as function of distance and
360
ambient noise level.
361
SNR (dB) - quality of verbal communication
Distance Ambient noise level, L
N,A
, dB
r, m 53 59 65 71 77 83 89
0.35 15 12 9 6 3 0 -3
0.5 12 9 6 3 0 -3 -6
0.7 9 6 3 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
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6.3. Background music
362
Background music is typically instrumental music played at a low level. It is not meant to be in
363
the focus of an audience, but rather to fill the gaps of silence, that might occur. When used in
364
restaurants and at social gatherings it should be played at a sufficiently low sound level, so it is not
365
disturbing for normal vocal communication. Background music can have a masking effect, which
366
contributes to a feeling of privacy in the meaning that a private conversation is not easily overheard
367
by other people in the room. Thus, it may happen that people stop talking if the background music
368
is stopped. Recommended maximum SPL of background music is around 60 dB to 65 dB.
369
Foreground music is played at higher levels than background music, and is meant to be noticed
370
and enjoyed as entertainment [28]. The audience is not supposed to talk during the music.
371
Recommended maximum SPL of foreground music is in the range 75 dB to 90 dB.
372
In a restaurant or at a social gathering the music contributes to the ambient noise level, which
373
means an increase of vocal effort in conversations. Thus, the Lombard effect applies to the total noise
374
level due to music and speech. Solving the problem leads to the following equation for the total noise
375
level
376
(dB) ,
4
115.0lg10
N
M
NMTota lN,
+++=
E
E
EEL
(6)
where the average SPL of the music is 10 lg(E
M
) and the SPL of ambient noise from speech without
377
music is 10 lg(E
N
). The latter is the SPL given in eq. (2). From this result, it is straightforward to
378
estimate the vocal effort (1) and the SNR with background music or other background noise.
379
Figure 12 shows the SNR as function of the ambient noise level without music, but with the
380
sound level of the background music as a parameter. If the level of the music does not exceed 65 dB
381
the quality of vocal communication can be sufficient (SNR > -3 dB), but of course only when the room
382
is not too crowded (actually if N < 0.7 · N
max
). For a satisfactory quality of verbal communication,
383
the background music should not exceed 60 dB.
384
385
386
Figure 12. The influence of background music on the quality of verbal communication. The curves
387
represent levels of music from 50 dB to 75 dB in steps of 5 dB. (Figure courtesy of Euronoise 2015,
388
Rindel [1]).
389
7. Suggested acoustical requirements for restaurants
390
The adaptation of the universal design concept [2] means that it is necessary to define acoustical
391
requirements for restaurants, canteens and other public eating facilities. The key parameters that
392
control the acoustical conditions are volume V, reverberation time T and number of people N, i.e.
393
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number of seats. The graphical presentation in Figure 13 is based on Equation 4, which yields the
394
SNR as function of V/(NT) and the distance of verbal communication r.
395
In the reference distance r = 1.0 m we have V/(NT) = 20 for the borderline between sufficient and
396
insufficient quality of vocal communication, so this might be taken as basis for the acoustical
397
requirement. However, this might be too strict because a restaurant is seldom fully occupied. An 80
398
% occupancy may be considered a more realistic basis for the requirement. Then the required
399
reverberation time yields:
400
(s) ,063.0
2080.0
1
N
V
N
V
T
(7)
The requirement must be related to the volume per person, which means that it is necessary to
401
know the maximum number of seats in the room. In some cases this maximum number has to be
402
accepted by the fire authorities, and an emergency escape plan that states the allowed maximum
403
number of guests must be mounted clearly visible in the room. In order to fulfill the acoustical
404
requirement there are three possibilities to consider:
405
1. The volume should be as big as possible. Some acoustically good restaurants have a high
406
ceiling. This is something to consider in the early stage of planning.
407
2. Sound absorbing materials must be applied on surfaces where it is possible. The ceiling
408
is obvious, but often parts of the walls must also be included. A thick carpet can also
409
add more sound absorption, but in many cases this is not an option.
410
3. The seating plan should not be too crowded. The easy solution is to make a seating plan
411
with a number of seats that does not exceed the acoustic capacity by more than 25 %.
412
413
414
Figure 13. Quality of verbal communication at function of distance and the parameter V/(NT).
415
Suggested acoustical requirements in four sound classes are shown with dotted lines.
416
Some countries use sound classification for buildings, e.g. four classes A, B, C, and D where class
417
A is best, class C is minimum requirements for new buildings, and class D is applicable for older
418
buildings. Table 7 contains suggested requirements for the reverberation time in restaurants in four
419
classes. These sound classes are indicated in Figure 13. Table 7 also shows the quality of verbal
420
communication in terms of SNR in a distance of 1 m for different percentages of occupancy. For
421
instance, 100 % occupancy in class A gives SNR = 0 dB, which is the borderline between satisfactory
422
and sufficient. The same is obtained in class C with 40 % occupancy.
423
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Table 7. Suggested minimum requirement reverberation time in restaurants in four sound classes. 424
The SNR in a distance of 1 m is shown as a function of the occupancy (number of people in percentage 425
of the total number of seats). 426
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 % 6 4 2 0
427
8. Conclusions 428
For the characterization of the acoustical conditions in restaurants and similar environments, the 429
quality of verbal communication is applied in addition to the ambient noise level. A signal-to-noise 430
ratio of -3 dB for a speaker in a distance of 1 m corresponding to an ambient noise level of 71 dB is 431
suggested as a realistic basis for design criteria. This leads to a combined requirement for the 432
reverberation time and the volume; the volume per person should be at least T ·20 m3, where T is the 433
reverberation time. Thus, the reverberation time should be as short as possible, but still a sufficient 434
volume is a physical necessity for satisfactory acoustical conditions. It should be noted that for 435
hearing impaired people and non-native speakers the acoustical needs are stronger and a better SNR 436
is needed for an acceptable quality of verbal communication. 437
It is obvious that the acoustical problems depend strongly on the number of people present in 438
the room. So, in addition to the design guide for the acoustical treatment of rooms, it is suggested to 439
introduce the acoustic capacity of a room. This is a simple way to indicate which number of persons 440
should be accepted in order to obtain sufficient quality of verbal communication. In other words, if 441
the number of people in the room exceeds the acoustic capacity, the ambient noise level may exceed 442
71 dB and the quality of verbal communication in a distance of 1 m is insufficient. 443
Both a simple prediction model and an advanced computer-based model for the ambient noise 444
due to speech have been derived. The models take the Lombard effect into account, and have been 445
verified for several test cases. In the design stage when alternative solutions for the acoustic design 446
of a restaurant or similar facility are considered, the acoustic capacity may be a good parameter to 447
present to architects, in addition to the calculated reverberation time or ambient noise level. This 448
has already been used successfully in several projects, and it is clear that the maximum number of 449
persons to allow sufficient acoustical conditions is much easier to understand for non-acousticians 450
than noise levels or reverberation times. 451
For the owners of restaurants it may be interesting to know that the perception of food and drink 452
is influenced by the ambient noise in the room, see Appendix A. However, the results go in opposite 453
directions. In a fine restaurant the noise should be kept at a low level in order to maintain the taste 454
qualities in the food. But for the owner of a bar, where the guests mainly come for drinks, a noisy 455
environment means that more drinks are consumed in a shorter time. So, the quality of verbal 456
communication might be less important in bars and a higher noise level (and thus a higher level of 457
arousal) acceptable or maybe even wanted. 458
When music is played in restaurants or at social gatherings, it is important to distinguish 459
between background music and foreground music. While foreground music is meant to catch the 460
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attention, background music should not interfere too much with verbal communication, and a 461
maximum sound level of 60 dB is suggested. 462
Acknowledgements 463
Measurements in case 5.2 were made by Andrzej Kłosa k fr om Kr akow Univ ers ity o f Tec hno logy , 464
Poland. The measurements in case 5.3 were made by Anders Chr. Gade, Gade & Mortensen Akustik 465
A/S, Denmark. 466
Appendix A. Drinking and eating in noisy environments 467
It is a widespread assumption that the noise level of a party increases with the amount of alcohol 468
consumed. However, no proof of this is found in the scientific literature. Never the less there is no 469
doubt that a relation exists between noise and alcohol consumption. Guéguen et al. [29] studied the 470
drinking behavior in bars as function of the sound level of music, either at “usual” level, 72 dB to 75 471
dB, or at a typical level of “foreground” music, 88 dB to 91 dB. With the high sound level, significantly 472
more drinks were consumed, the mean value for 60 persons being 3.7 versus 2.6 drinks at the usual 473
level. The authors have suggested an “arousal” hypothesis to explain the findings; the high sound 474
level leads to higher arousal, which stimulates to drink faster and to order more drinks. In a later 475
follow-up study [30] it was confirmed that the average time spent to drink a glass of beer decreased 476
from 14.5 ± 4.9 minutes with usual level of music (72 dB) to 11.5 ± 2.9 minutes with high level of music 477
(88 dB). 478
Stafford et al. [31] have found that music and other forms of distraction leads to increase in 479
alcohol consumption. In addition they found that sweetness perception of alcohol was significantly 480
higher in the music compared to no music and other distraction conditions. The study gives support 481
to the general distraction theory that noise disrupts taste and smell. 482
The effect of noise on food perception was studied by Woods et al. [32]. Test persons were 483
exposed to white noise at levels of 45 dB to 55 dB (Quiet) and 75 dB to 85 dB (Loud), in addition to a 484
no-noise condition. The ratings of sweetness and saltiness were influenced by the noise, and the food 485
was reported to taste less intense in the noisy condition. This might be interesting news for owners 486
of good restaurants, and it certainly gives a new twist to the discussion of the importance of good 487
acoustics in restaurants. 488
Fiegel et al. [33] have found that background music can alter food perception, and that the effect 489
depends on the music genre (classical, jazz, hip-hop, rock). They used the same SPL of the music in 490
all cases, namely 75 dB. Especially in the presence of jazz stimulus, flavor pleasantness and overall 491
impression of the food stimuli increased. 492
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Conference Paper
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Noise from many people speaking in eating establishments and other social gatherings is a well known and wide spread problem. The problem is particularly difficult to handle because the sound sources are individual and dynamic, i.e. the speech level increases when the ambient noise level goes up. However, a simple prediction model has been derived that allows estimating the ambient noise due to speech from a large group of people, the main uncertainty being the so-called group size, i.e. the average number of people per speaking person. As a measure of the acoustical quality is suggested the average signal-to-noise ratio when listening to a person speaking to you in a distance of 1 m and the ambient noise is that from other people speaking in the room. The Acoustical Capacity is defined as the number of people that would create a signal-to-noise ratio of -3 dB, which is considered the lower limit for "sufficient" quality of verbal communication under certain preconditions. The Acoustical Capacity is calculated from volume and reverberation time by a very simple equation. The acoustical quality of an eating establishment may be characterized by the ratio between the Acoustical Capacity and the total capacity.
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