8/12/2019 Concert hall Acoustic
1/97
8/12/2019 Concert hall Acoustic
2/97
8/12/2019 Concert hall Acoustic
3/97
The normalized ACF is defined by
p() = p() /p(0) (2)
As a manner shown in Figure 1b, the value of e isobtained by fitting a straight line for extrapolation ofdelay time at 10 dB, if the initial envelope of ACFdecays exponentially. Therefore, four orthogonal andtemporal factors that can be extracted from the ACFare p(0),1,1,and e.
Auditory-Temporal Window
In analysis of the running ACF, of particular interestis so called an auditory-temporal window, 2T inEquation (1), that must be determined. Since the initial
part of ACF within the effective duration eof the ACFcontains the most important information of the signal,thus the recommended signal duration (2T)r is givenby
(2T)r K1(e)min[s] (3)
where (e)min is the minimum value of e obtained byanalyzing the running ACF, K1 being the constantaround 30 [7]. The running step (Rs) is selected asK2(2T)r, K2 being selected, say, in the range of 1/4 3/4.
Factors extracted from the IACF
The IACF is given by
where pl ,r(t) = p(t)l,r*s(t), p(t)l,r being the soundpressure at the left- and right-ear entrances. Thenormalized IACF is given by
lr() = lr()/[ll(0)rr(0)]
1/2
(5)
where ll(0) and rr(0) are autocorrelation functions( = 0) or sound energies arriving at the left- and right-ear entrance, respectively. Spatial factors extractedfrom the IACF are defined in Figure 2 [2].In analyzing the running IACF, 2T is selected byEquation (3) also. For the purpose of spatial design forsound fields, however, longer values of (2T)rmay beuseful, because it is essentially time independent.
PRIMARY SENSATIONS
Loudness
Let us now consider primary sensations. Loudness sLis given by
sL= f[p(0), 1, 1, e, D] (6)
where D is the duration of sound signal as isrepresented by musical notes. It is worth noticing that
the value of 1corresponds to pitch of sound and/or themissing fundamental as discussed below. Since thesampling frequency of the sound wave is more than thetwice of the maximum audio frequency, the value10log (0)/ (0)ref is far more accurate than the Leqwhich is measured by the sound level meter.
Scale values of loudness within the critical bandwere obtained in paired-comparison tests (with filterswith the slope of 1080 or 2068 dB/octave) under thecondition of a constant p(0) [2,4]. Obviously, when
sound signal has the similar repetitive feature, ebecomes a great value, as like a pure tone, then the
greater loudness results. Thus a plot of loudness versusbandwidth is not flat in the critical band. Thiscontradicts previous results of the frequency rangecentered on 1 kHz [5].
Pitch
The second primary sensation applying the ACF isthe pitch or the missing fundamental of the noise. It isgiven by
sP= f[p(0), 1, 1,e,D] (7)
(4)lr() = 12T
p'l(t)p'r(t+)dt
-T
+T
FIGURE 2.Definition of independent factors IACC,
IACCand WIACCextracted from the normalizedIACF.
SESSIONS
8/12/2019 Concert hall Acoustic
4/97
When a sound signal contains only a number ofharmonics without the fundamental frequency, we hearthe fundamental as a pitch. This phenomenon is wellexplained by the delay time of the first peak in the
ACF fine structure, 1[6,7]. According to experimentalresults on the pitch perceived when listening tobandpass noises without any fundamental frequency,the pitch spis expressed by equation (7) as well, underthe condition of a constant (0). The strength of thepitch sensation is described by the magnitude of thefirst peak of the ACF, 1. For a signal of short duration,factor D must be taken into account.
Timbre
The third primary sensation, timbre that includes
pitch, loudness, and duration, might be expressed by
sT= f[p(0),e, 1, 1, D] (8)
It is worth noticing that the intelligibility of singlesyllables as a function of the delay time of singlereflection is well be calculated by the four orthogonalfactors extracted from the running ACF analyzed forthe piece between consonant and vowel sounds [7]. Arecent investigation, clearly show that timbre ordissimilarity judgment is an overall subjective responsesimilar for the subjective preference of sound fields inconcert hall.
Duration
The forth-primitive sensation, which is introducedhere, is the perception of signal duration, which isgiven by [12,13]
sD= f[p(0), 1, 1,e, D] (9)
One of experimental results has been expressed inrelation to 1, 1, and D [8]. Table 1 indicatessummarization of primary sensations in relation tofactors extracted from the ACF and physical signalduration D.
SPATIAL SENSATIONS
Directional Sensation
If ll(0) rr(0), then the perceived direction of anoise source in the horizontal plane is assumed to bedescribed as
Factors Primitive Sensations
Loudness Pitch Timbrea) Duration
ACF p(o) X x X X
1 X X X X1 x X X X
e X x X xD xb) xb) Xb) X
X and x : Major and minor factors influencing the correspondingresponse, respectively.
a). Timbre in relation to all of temporal and spatial factors is underinvestigation.b). It is suggested that loudness, pitch and timbre should beexamined in relation to the signal duration.
s = f[LL, IACC, IACC, WIACC] (10)
where
LL = 10 log [p(0)/(0)ref] (11)
And p(0) = [ll(0)rr(0)]1/2, and ll(0) and rr(0)
being ACFs at = 0 (sound energies), of the signals
arriving at the left and right ear-entrances. In fourorthogonal factors in Equation (10), the interauraldelay time, IACC, is a significant factor in determiningthe perceived horizontal direction of the source. Awell-defined direction is perceived when thenormalized interaural crosscorrelation function has onesharp maximum, a high value of the IACC and anarrow value of the WIACC, due to high frequencycomponents. On the other hand, subjective diffusenessor no spatial directional impression corresponds to alow value of IACC (< 0.15) [9].
Of particular interest is that, for the perception of asound source located in the median plane, the temporal
factors extracted from the ACF of sound signalarriving at the ear-entrances may act as cues . It hasbeen shown that three factors, e, 1, and 1 as afunction of the incident angle greatly differ, but fewdifferences may be found in the head-related transferfunctions [10].
A remarkable finding is that there are neuralactivities at the inferior colliculus corresponding to theIACC and sound energies for sound signals thatarriving at the two-ear entrance [11]. Also, it isdiscovered that the LL and the IACC are dominantlyassociated with the right cerebral hemisphere, and the
Table 1. Primary sensations in relation to factors extractedfrom the autocorrelation function and the interauralcrosscorrelation function.
SESSIONS
8/12/2019 Concert hall Acoustic
5/97
8/12/2019 Concert hall Acoustic
6/97
The Preferred Acoustic Parameters
for a Javanese Gamelan Performance Hall
J. Sarwonoa,b
and Y.W. Lama
aSchool of Acoustics and Electronic Engineering, University of Salford, Brindley Building,
Meadow Road Site, Salford M7 9NU, UK. E-mail: [email protected] Physics Department, ITB, Jl. Ganesa 10 Bandung 40132, Indonesia.
This paper discusses the application of a method based on human subjective preference to the acoustic design of a Javanesegamelan performance hall. Some important distinctions between Javanese gamelan ensembles and Western classical orchestraare the tuning system, orchestral blending process, and technique of playing. The results of subjective preference test using therank order method showed that the subjects preferred 30 ms for ITDG, 600 ms for RT, and the smallest value of IACC. These
results, except for the IACC, agree with the acoustic parameters from the room responses measured in a traditional pendopo inIndonesia, which is not a common concert hall but an open-sided hall.
INTRODUCTION
Javanese gamelan is one of the Indonesian
traditional music ensembles. There are several
important differences between the gamelan and the
Western symphony orchestra including tuning systems,
orchestral blending systems, and playing technique.
According to Ando[1],by using human preference
approach through a psychoacoustic test, four
orthogonal factors for designing concert hall can be
determined. Those four factors are the listening level
(LL), the initial time delay gap (ITDG), the subsequent
reverberation time (RT), and the Inter-Aural Cross-
Correlation (IACC). So far, this theory has mostly been
applied for designing concert halls for Western
classical music.
This paper will discuss an application of the
approach to design the preferred acoustic conditions
for performing Javanese gamelan in an enclosed hall.
Three preferred parameters, ITDG, RT and IACC will
be discussed in this paper. Measurement data from a
pendopo, an open-sided hall where Javanese gamelan
usually played, in Indonesia will be provided as
comparison.
METHOD AND EXPERIMENT SETUP
The research combines three major methods, acomputer based analysis and simulation, in situ
measurements and subjective preference test in an-
echoic chamber. A computer-based analysis has been
used to obtain the most appropriate gendhing for the
whole subjective preference test, while computersimulation process was mainly used for preparing the
test samples. In situ measurements were conducted in a
pendopo in Indonesia to provide comparison for the
subjective preference tests.
All the subjective preference tests were carried out
in an anechoic chamber, using a configuration of 7loudspeakers to simulate several sound field conditions
to be judged by listeners. All the listeners were
university students with several nationalities, inclusiveall genders. The subjective preference test has been
carried out using the rank order method.
A studio recordinggendhingfrom the closingpart of
Kebogiro Glendeng, with minimum e= 27.59 ms (2T= 2 s, interval 100 ms), was used in the subjective
preference test. The duration of the stimulus was 9.3 s.
All stimuli were stored in a PC, which was also
functioned as stimuli player. Seven identical
loudspeakers were used to produce the sound. All
loudspeakers were placed at distance of 1.35 m fromthe listener. The horizontal angles of the loudspeakers
were 0o, 45
o, 67.5
o, and 135
o. The vertical angles
of the loudspeakers were 0o, except the rear
loudspeakers for the ITDG and RT tests, which were
elevated 6o, relative to the subject's ears. The detail
configuration is shown in Table 1.
Table 1. Detail of Test Configuration
Test
Direct
Sound
Refl. Reverb. Refl.
Amplitude
Reverb.
Amplitude
Stimuli Listening
Level
Subject
ITDG 0o 45o 67.5o, 135o 1 dB -3 dB 15, 30, 50, 80, 160 ms 73 dBA 6
RT 0o 45o 67.5o, 135o -1 dB 2 dB 0, 0.45, 0.6, 1.2, 2.5, 4.5 s 73 dBA 17
IACC 0o 45o 67.5o,135o vary vary 0.3, 0.4, 0.5, 0.75, 1 73 dBA 10
SESSIONS
8/12/2019 Concert hall Acoustic
7/97
RESULTS AND DISCUSSION
It was shown that there was a low value preference
for ITDG (Figure 1) as well as for RT (Figure 2), withthe most preferred value of 30 ms and 600 ms,
respectively. This means that the subjects preferred
good clarity with an intimate sound field for listening
to Javanesegamelanin an enclosed hall. These results
agree with the ITDG and RT of pendopo Puro
Mangkunegaran[2], as shown in Figure 3. It shows the
ITDG and RT of thependopoat 5 measurement points,
including the centre of the hall (centre), the audience
area (10, 11, 15), and the VIP area (king).
Figure 4 shows that the lower the IACC the higher
the subjective preference. This shows that a
spaciousness and enveloping sound field is preferred
for listening to Javanese gamelan in an enclosed hall.
However, this is not in agreement with the measured
IACC of pendopo Puro Mangkunegaran, (IACC = 1)
as it is an open-sided hall.
CONCLUSION
The preferred parameters for Javanese gamelan
performance hall were 30 ms for ITDG, 600 ms for
RT, and the smallest value of IACC. These agree with
the acoustic parameters, except for the IACC, from the
room responses measured in a traditional pendopo in
Indonesia, which is not a common concert hall but an
open-sided hall.
REFERENCES
1. Ando Y, "Architectural Acoustics", Springer Verlag,New York, 1998.
2. Sarwono, J. and Lam, Y.W., "The Acoustics of aPendopo: A Typical Open-sided Hall for Javanese
Gamelan Music Performance", in proceeding of IoA,
2000, Volume 22 Pt 2, pp. 305 - 313.
FIGURE 1.Preference for ITDG
FIGURE 2.Preference for RT
FIGURE 3. ITDG and RT of PendopoMangkunegaran
FIGURE 4. Preference for IACC
0
1
2
3
4
5
15 30 50 80 160
ITDG (ms)
RankOrder
1
2
3
4
5
6
0 450 600 1200 2500 4500
RT (ms)
RankOrder
0
100
200
300
400
500
600
700
800
900
1000
centre 10 11 15 king
Measurement points
RT(ms)
0
5
10
15
20
25
30
35
ITDG(s)
RT ITDG
0
1
2
3
4
5
0.3 0.4 0.5 0.75 1
IACC
RankOrder
SESSIONS
8/12/2019 Concert hall Acoustic
8/97
The Application of Neural Network Analysis to Auditorium
Acoustics
F. Fricke
Department of Architectural and Design Science, University of Sydney, NSW 2006, Australia.
Neural network analysis (NNA) is a relatively new research and design tool that has been used in many fields from structuralengineering to finance. So far very little use of the technique has been made in architectural acoustics. In this paper the NNAtechnique is outlined and examples of its use in auditorium acoustics are given to demonstrate its potential. These include the
prediction of reverberation time and sound levels in auditoria and the acoustic quality of halls using both acoustic and physicalparameters as inputs. The advantages and limitations of neural network analysis are also outlined.
INTRODUCTION
There are at least two approaches to the study of
concert hall and auditorium acoustics. One is academic
and the other design oriented. The academic approach is
directed at finding out what it is that makes concert halls
good and what influences opinions about the acoustics of
halls. It is also about measuring and calculating various
acoustic quantities in halls and trying to apply results of
perception experiments, carried out in anechoic rooms,
to more complex situations such as that which exist in
concert halls. In the second approach the architect or
designer wishes to define the acoustics of a space in
terms of its size, shape and surface finishes.While the approaches of Beranek [1], Ando [2] and
others shows great understanding of the academic
requirements these approaches do not give designers the
tools they want. These tools are simple rules of thumb
that ensure excellent acoustics. Such simple rules almost
certainly do not exist but more complex ones possibly
do. For instance, the most basic rule of thumb used
seems to be the volume per seat even though the volume
per seat varies between good halls (Boston Symphony
Hall has a V/N of 7.14 while Meyerson Hall has 11.6.).
A more complex rule may, for example, involve the
optimum volume per seat as a function of the length of
the hall. Ultimately the aim of the present work is toinvestigate whether such complex rules exist and if so, to
present them in a designer-friendly form.
NEURAL NETWORK ANALYSIS
Very briefly, neural network analysis (NNA) is a
computer-based technique which learns to recognize
patterns. These patterns are usually in numerical data butcould be in the juxtaposition of pixels or the pitch of
notes. The general technique and its applications have
been described in many texts eg [3],[4] and its
application to a number of architectural acoustics
issues has been described in a several papers by
Fricke eg [5],[6] and Nannariello eg [7],[8].
The method is based on the way the brain works
where neurons are connected by synapses. In a
simple NNA the inputs (eg length and height of a
room) neurons are interconnected to a layer ofhidden neurons which in turn are connected to an
output (eg the reverberation time or acoustic
quality of a room) neuron. The network is trained,
using data (cases) from existing situation where the
inputs and outputs are known. The error between the
actual and predicted values of the output isminimised by systematically changing the weights on
the connections between the neurons.
The advantages over other approaches are that
NNA can handle more than 6 input variables (usually
considered the maximum possible number for a
conventional analytical approach) and can deal withnon-linear relationships. Its disadvantages are that it
is never possible to determine whether an optimal
solution has been found and when a solution has been
found it cannot easily be used in the form of an
equation though it can be easily used in a spreadsheetformat. Often there are not enough cases available to
accurately train, verify and test a network and the
validity of the analysis is only within the range of theinput variables. Also, where there are more than 6
inputs, it is very difficult to represent the output
graphically or to produce rules of thumb from theanalysis.
NNA OF THE ACOUSTIC QUALITY
OF ROOMS
Of the two approaches tried for the prediction of
acoustic quality of rooms the acoustic input
approach [6] gives better results (Standard Deviation
SESSIONS
8/12/2019 Concert hall Acoustic
9/97
Ratio, SDR 0.2) than the geometrical input approach
[5] (SDR 0.9). This is not surprising given the large
number of geometrical inputs required to define an
auditorium (though many of them are related to one
another). The geometrical approach required 10 inputs(V, S, N, L, W, H, SDI, MRA, SH and SE) while the
acoustic approach required only 6 (5 of Beraneks input
parameters EDT, G, IACC, TI, BR and SDI - and
either N or V) where V = room volume, S = room
surface area, N = number of seats, L, W and H are the
maximum length, width and height respectively, SDI =
surface diffusivity index, MRA = mean rake angle of
seating, SH is stage height and SE = stage enclosure.
One modified geometrical approach which has givenuseful results involves categorising halls into two
groups; those with an AQI of 0.7 or greater and those
with an AQI of less than 0.7. With this approach there is
> 90% success rate using N, L/W, H/V1/3, MRA andSDI/SE as inputs.
Another approach is based on Nannariellos work [8]in which acoustical parameters, such as IACC and RT,
are obtained from geometrical inputs. These can then be
used to calculate AQI. The efficacy of this method
should not be in doubt given Nannariellos results for G,
RT, and IACC, (and the certainty that room acoustic
parameters are dependent on size, shape and surfacefinishes of rooms), but the final analysis has yet to be
carried out.
DISCUSSION AND CONCLUSIONS
NNA can be used to predict the acoustic quality of a
concert hall or an auditorium though the accuracy of the
geometrical approach leaves something to be desired.
Both the geometrical and acoustical NNA
approaches are useful in understanding the influences on
the acoustic quality of auditoria and giving an estimate
of acoustic quality early in the design process. It appears
likely that much better predictions of acoustic quality,
using geometrical inputs and more complex networks,
will be developed soon. Once such a network has been
developed and the network embedded in a spreadsheet
for designers to use.Likewise, NNA can be used to predict acoustical
quantities in auditoria such as RT (or EDT), IACC, G,
BR and TIprovided that the space in which the quantities
are to be predicted falls within range of the training
data for the neural network.
There are limitations on the method and if NNA is
to be a success there is a need for a data base on the
web where information can be made available toeveryone. This is necessary as it is doubtful if any
one person is ever going to be able to undertake all
the measurements needed on halls in order to carry
out satisfactory neural network analyses.
As a final comment it must be stated that NNA
should not be considered as a new branch of
architectural acoustics but rather as a new fertiliser
which may help the existing branches bear more
fruit.
REFERENCES
1. Beranek, L. L., Concert Halls and OperaHouses, Acoustical Society of America, Woodbury,
NY, 1996
2. Ando, Y., Concert Hall Acoustics, Springer-Verlag, Berlin, 1985.
3 Fausett, L., Fundamentals of Neural Networks:Architecture, Algorithms & Applications, Prentice
Hall, New Jersey, USA, 1994.
3. Statistica Neural Networks, (1999) TechnicalManual Version 4, StatSoft Inc., Tulsa, OK.
4. Fricke, F. R. & Han, Y. H., (1999), A NeuralNetwork Analysis of Concert Hall Acoustics,
Acustica, 85, 113- 120.5. Fricke, F. R., (2000), Concert Hall Acoustic
Design: An Alternative Approach, Building
Acoustics, 7, 233-246.
6. Nannariello, J. & Fricke, F. R., (1999), ThePrediction of Reverberation Time Using Neural
Network Analysis, Applied Acoustics, 58 (3), 305-
325.
7. Nannariello, J. & Fricke, F. R., (2001),Introduction to neural network analysis and its
application to building services engineering,
Building Services Engineering Research &
Technology Journal, 22, 61-71
8 Nannariello, J. & Fricke, F. R., (2001), ThePrediction of Reverberation Time Using suitable
Neural Networks, Proceedings 17 ICA, Rome
SESSIONS
8/12/2019 Concert hall Acoustic
10/97
Objective evaluations of chamber music halls in Europe and Japan.
Takayuki Hidaka*, Noriko Nishihara*
* Takenaka R&D Institute, 1-5-1, Otsuka, Inzai, Chiba 270-1395, Japan
Abstract:The room acoustical parameters - Reverberation time RT, early decay time EDT, clarity C 80, strength G, initial timedelay gap ITDG, and interaural cross-correlation coefficient IACCE, were measured in 18 major chamber music halls in Europeand Japan employing the procedure in accordance with ISO 3382 [1]. By combining architectural data, the intrinsic parametersfor the acoustics of chamber music halls are examined.
INTRODUCTION
For symphony halls and opera houses, the results ofmeasurements of current room acoustical parametershave been reported in the literature [2,3]. There areonly limited numbers of similar studies on chambermusic halls [4]. There is no assurance whetherexisting data or design guidelines for large symphonyhalls are also suitable for smaller sized spaces,therefore it seems meaningful to assemble theacoustical data and to survey their features. In thispaper, 9 highly-reputed halls of traditional design inEurope and 9 major halls of contemporary design inJapan are compared and studied.
MEASUREMENT RESULT AND SOME
DISCUSSION
The measured halls, which are regularly used forchamber music in each city, are listed in Table 1.European and Japanese halls respectively can beclassified as those of traditional style and those ofmodern construction and materials. The seatingnumbers, N, in these 18 halls vary from 207 to 844,while the volumes, V, and reverberation times(occupied) vary from 1070 to 8475 m3and 0.9 to 2.0 s,respectively. Many of them (15 out of 18 halls) areshoebox, or at least have rectangle floor plans. Thesuffix L, M and 3 associated with the measuredquantities mean the average over 125/250 Hz, 500/1kHz, and 500/1k/2k Hz, respectively. The occupiedvalues were transformed from measured unoccupiedvalues using the method in [5]. The measurements were executed without audiencesand with no instruments on the stage (sometimes apiano existed at the corner of the stage). Themeasuring procedure is exactly the same as in [3,5] andcoincides with that of ISO 3382 [1]. The correlationmatrix for the objective measures shown in Table 2indicate that the independent parameters are RTM, G,IACCE3, BR, and ITDG. This same correlation matrixis also found in symphony halls and opera houses [3,6].
RT : The volume per person on average is 6.4 m3 fortraditional halls and 9.1 m3 for modern halls, thus the
volumes of the latter are about 40% larger. The reasonfor the size differences appears to come from the factthat modern architects prefer medium-upholsteredchairs for greater comfort. Because such chairsabsorb more sound, even when occupied, the roomvolume is larger in modern halls so as to adjust the RTto the volumes shown. The approximate equationwith the form, AoccM SVKRT /, = , is plotted in Fig.
1, where relevant Kvalue falls between 0.13 and 0.14for chamber halls, similar to the value of 0.14 forsymphony halls [2], and RTs seem to converge to ca.1.8 s.C80, EDT : C80and EDT are variables not independentfrom RT, but all these are very highly correlated.However, the subjective impression of clarity inchamber halls is frequently of major concern. Asshown in Fig. 2, C80s (occupied) may be classifiedinto two groups, (3.50.4) and (0.11.6) dB. The
latter coincides with the optimal range for Mozartmusic which was proposed by Reichardt et al. [7].Obviously every hall exceeds the lower limit of -1.5dB.G : Strengths G in dB for traditional and modern hallsare moderately different from each other, except forhall SG, with the largest capacity N=844 (Fig. 3). GLand GMof the former are respectively about 4.5 and 3dB larger than the latter on average, which is probablycaused by the difference in volume, e.g., Beranek hasshown G is proportional to 10log(EDT/V) [2].BR : The bass ratios for occupied condition aredistributed from 0.87 to 1.12 and from 1.07 to 1.24 for
modern and traditional halls (median values are 1.02and 1.14), respectively, which are narrower ranges thanthat of the concert halls, 0.92 to 1.45 in spite of thewider range of V/N. BR highly correlates with GL(r=0.8), although Bradley and Soulodre find that GLismore significant [8].[1-IACCE,80] : [1-IACCE] is also an independentvariable for chamber halls but the variation range isextremely narrow, 0.67 to 0.77. This range is same asthe subjective difference limen by [9], namely it can besaid that every chamber hall has similar binauralquality, provided [1-IACCE,80] is still valid for chamberhall. This situation is quite different from that for a
SESSIONS
8/12/2019 Concert hall Acoustic
11/97
large symphony hall or opera house, where thevariation range is 0.39 to 0.72. Physically, there arevery many lateral reflections within the first 80 msec inevery hall. If we assume that binaural correlationplays a significant role for sound quality in small halls,it is possible to separate them using [1-IACCE,30],where only the information within the first 30 msec isused (Fig. 4). Although there is no precise evidenceat the present moment as to why the integration shouldbe limited to 30 sec, the possibilities may be (1) earlyreflections after 20 msec may deteriorate thelocalization of stereophonic sound [10], and (2)audiences may relish more detailed information fordelicate chamber music.
CONCLUSION
RT, G, BR, ITDG, and IACCE are independentparameters in the chamber halls studied. However,their values for traditional and for contemporary hallshave different ranges except for IACCE,80. IACCE,80
varied within narrow range so that the integration limitof IACCE should be reduced to the first 30 msec toseparate each hall suitably. Further research isrequired to verify its subjective foundation.
REFERENCES
[1] ISO 3382: 1997, Acoustics - Measurement of thereverberation time of rooms with reference to otheracoustical parameters. [2] Beranek, L. L., Concert andOpera Halls,Acoust. Soc. Amer, 1996. [3] Hidaka, T. andBeranek, L. L., J.A.S.A., 107, 368-383 (2000). [4] Barron,M.,Auditorium Acoustics and Architectural Design, E and FNSpon, London, 1993. [5] Hidaka, T., et al., J.A.S.A. 109,1028-1042 (2001) [6] Hidaka, T., et al., J.A.S.A., 107, 340-354 (2000). [7] Reichardt, W., et al., Acustica 32, 126-137 (1975). [8] Bradley, J. and Soulodre, G., J.A.S.A., 98,2590-2597 (1995). [9] Cox, T. J., et al., Acustica 79, 27-41
(1993). [10] Bech, S., 100thConvention AES, Copenhagen(1996).
Fig. 4Plot of [1-IACCE,t] against thenames of halls (not rank-ordered).Integration limit, t, was varied from 30to 80 msec.
Fig. 3Plot of GLs (occupied) vs. BRs (occupied).
Fig. 2Plot of C80s (occupied) vs. EDTMs(unoccupied).
Fig. 1Plot of RTs (occupied) vs. volumedivided by the acoustical area of audience.
Table 2Correlation coefficients among acoustical factors in 18 chamber halls.
Table 1Chamber music halls for which objective measurements are available.
RTocc, M vs. V/SA
ZT
VB
AC
SG
SW
PM
VS
BS
VM
TT
KMTI
TCTD TH
TS
KH
TM
0.5
1.0
1.5
2.0
2.5
5 10 15 20V/SA (m)
RTocc,M
(sec)
Europe
Japan
V N V/SA RTocc, M EDTunocc, M BRocc. C803B GL GM 1-IACCE3 ITDG
m3 m sec sec - dB dB dB (80msec) msec
AC Amsterdam, Kleinersaal in Concertgebouw 2,190 478 9.4 1.25 1.49 1.21 1.5 13.7 12.9 0.69 17
BS Berlin, Kleinersaal in Schauspielhaus 2,150 440 9.0 1.08 1.33 1.24 2.0 12.2 10.9 0.67 11KH Kanagawa, Higashitotsuka Hall 3,576 482 8.6 1.18 1.11 0.87 3.1 5.4 8.7 0.72 10
KM Kirishima, Miyama Conceru 8,475 770 15.8 1.84 1.80 1.12 -0.1 8.2 8.3 0.75 26PM Prague, Martine Hall 2,410 201 18.4 1.76 2.19 1.12 -1.9 12.6 12.6 0.68 11
SG Salzburg, Grossersaal in Mozarteum 4,940 844 11.5 1.66 2.06 1.07 -1.6 9.9 9.6 0.69 27SW Salzburg, Wiennersaal in Mozarteum 1,070 209 8.4 1.11 1.33 1.09 1.7 14.9 14.3 0.77 15
TC Tokyo, Casals Hall 6,060 511 17.8 1.67 1.79 1.00 -1.3 7.6 9.4 0.71 15
TD Tokyo, Harumi Concert Hall 6,800 767 13.3 1.66 1.83 1.09 -0.1 9.8 10.8 0.71 24TH Tokyo, Hamarikyu Asahi Hall 5,800 552 14.7 1.67 1.82 0.93 0.0 7.1 8.8 0.71 15
TI Tokyo, Ishibashi memorial Hall 5,450 662 14.9 1.70 1.84 1.10 -0.8 9.2 10.8 0.75 19TM Tokyo, Mitaka Arts Center 5,500 625 13.3 1.73 2.28 1.02 -2.2 9.1 11.1 0.75 17TS Tokyo, Sumida Small Sized Hall 1,460 252 9.7 0.93 1.08 1.03 2.8 8.1 10.6 0.73 8TT Tokyo, Tsuda Hall 4,500 490 12.5 1.33 1.42 0.90 0.8 7.6 10.7 0.71 20
VB Vienna, Brahmssaal 3,390 604 10.0 1.63 2.37 1.16 -2.8 12.8 1 3.6 0.77 7
VM Vienna, Mozartsaal in Konzerthaus 3,920 716 9.1 1.49 1.79 1.14 -0.2 11.6 10.8 0.70 11VS Vienna, Schubertsaal in Konzerthaus 2,800 336 15.6 1.98 2.54 1.14 -3.3 14.7 13.6 0.77 12ZT Zurich, Kleinersaal in Tonhalle 3,234 610 9.3 1.58 2.11 1.18 -1.8 14.1 13.2 0.70 18
0.3
0.4
0.5
0.6
0.7
0.8
KHPMTDVMSGTHTIACTCVSBSZTTSKMTMTTSWVB
Hall
1-IACCE3
80ms
50ms
30ms
GL vs. BR
SG
VM
BS
ACZT
VBPM
VSSW
TTTH
KM
TITM
TC
TD
TS
KH
4
6
8
10
12
14
16
0.7 0.8 0.9 1.0 1.1 1.2 1.3
BR
GL
(dB)
Europe
Japan
4.5dB
C80,3B,occ vs. EDT
VS
VB
SG
PM
ZT
VM
AC
BSSW
TT
TI
TC
THKM
TD
TSKH
TM
-2
-1
0
1
2
3
4
5
1.0 1.5 2.0 2.5 3.0
EDT (sec)
C80,occ(dB)
Europe
Japan
0.11.6dB
3.50.5dB
RTM RTM EDTM C80,3B C80,3B GL GM IACCE3 BR ITDG Width V N
unocc occ unocc occ
RTM, unocc -
RTM, occ 0.93 -
EDTM 0.98 0.88 -
C80,3B, unoccu. -0.96 -0.87 - 0.98 - Bold: > 0.6
C80,3B, occ. -0.91 -0.94 -0.92 0.95 -
GL 0.30 0.05 0.37 -0.33 -0.12 -
GM 0.21 -0.05 0.32 -0.30 -0.10 0.89 -
IACCE3 -0.25 -0.19 -0.19 0.19 0.15 -0.07 -0.25 -
BR 0.27 0.08 0.30 -0.25 -0.07 0.80 0.56 0.11 -ITDG 0.21 0.37 0.12 -0.14 -0.23 -0.18 -0.34 0.07 -0.04 -
Width -0.03 0.16 -0.16 0.20 0.07 -0.56 -0.65 0.20 -0.34 0.49 -
V 0.39 0.61 0.26 - 0.29 - 0.44 - 0.57 -0.67 -0.08 - 0.29 0.66 0.66 -
N 0.40 0.43 0.28 -0.28 -0.28 -0.29 -0.46 0.08 0.03 0.64 0.61 0.75 -
SESSIONS
8/12/2019 Concert hall Acoustic
12/97
Optimum Design of a Concert Hall by Genetic Algorithms
A. Takizawaa, K. Otorib, T. Hayashib, H. Sakaib, Y. Andob, and H. Kawamuraa
aDepartment of Architecture and Civil Engineering, Kobe University, Rokkodai 1-1, Nada, Kobe, Japan
bGraduate School of Science and Technology, Kobe University, Rokkodai 1-1, Nada, Kobe, Japan
Abstract: Recently, Genetic Algorithms (GA), which is one of the evolutionary computing, are applied to various complexengineering problems. An optimization system of a concert hall by employing GA with four orthogonal preferences and three
models are discussed. The model 1 is that the form is based on the general shoebox type, and its proportion is optimized. Themodel 2 is that its plan is optimized. The model 3 is that the form is also based on the shoebox type but each wall is divided intotriangles and their vertex positions are optimized. The sound simulation was performed by the image method. The results show
that the optimized form of the model 1 is similar to Grosser Musikvertinssal. Those of the model 2 have different characteristicsdepending on the preference. Those of model 3 are various and complex ones, but they have high sound preferences.
INTRODUCTION
In the field of concert hall design, there is anestablished theory that a shoebox form has high sound
efficiency. On the contrary, if such simple form doesnot fit to architects sense, circular or elliptical ones
with the inevitable problem of sound focus have oftenbeen used. Recently, Genetic Algorithms (GA) [1],which are one of the evolutionary computing, areapplied to various complex optimization problems. Inthis paper, GA are applied for a concert hall design in
order to search a form having good sound performancefree from such preconception.
In the following sections, three optimization models
and results are discussed. Four orthogonal factors in
relation to subjective preference, LL, Dt1, Tsub, and
IACC [2], were employed as fitness functions. The
sound simulation was performed by the image method.
The model 1 and 2 used motif-B, and model 3 used
motif-A for evaluation.
MODEL 1 AND RESULT
Firstly, the proportion of shoebox form is optimized.
Width of the initial form is 20m, stage length is 12m,
seats length is 30m, and height is 15m. The sound
source is put on the center of the stage and 72 listening
points are prepared. Each moving range of sidewalls
and ceiling is 5 m from the initial form, and each
moving length of them is coded on a chromosome of
GA. Two values of 1S and 4S which are averaged
subjective preferences of LLand IACC by all listening
points are employed.
The results of optimization by 1S and 4S are shown in
figure1. Widths and lengths are almost same with each
other, but heights show opposite characteristic. Table1
shows the comparison of proportions between the
results and Grosser Musikvereinssaal which is famous
as having very good sound performance. Length/width
ratios are almost same. The height/width ratio of
Grosser is middle of the results. The subjective
preferences employed here seem to be appropriate for
evaluating a concert hall.
FIGURE 1. Results of the model 1: (a) the result by 1S ,
(b) the result by 4S .
Table 1. Comparison of proportions between theoptimized forms and Grosser Musikvereinssaal.
length/width height/width
(a) The result by 1S 2.50 0.71
(b) The result by 4S 2.57 1.43
Grosser Musikvereinssaal 2.55 0.93
MODEL 2 AND RESULT
Next, the initial form of the model 1 is changed a little.
Front and rear walls are divided vertically to two ones,
36
20
14
35m
10
14
S :
Initial model = -0.70 Optimized = -0.55
1 Lager is better. S :
Initial model = -0.30 Optimized = -0.26
4
SESSIONS
8/12/2019 Concert hall Acoustic
13/97
and each sidewall is divided to 5 ones. The coordinates
of two bottom vertexes of each surface are
parameterized. The moving range of each vertex is
2 m in the direction of the surfaces normal line.
Figure 2 shows the results. Front and rear walls have
opposite characteristic between (a) and (b). If 1S is
considered, sounds should be reflected to seats directly.
This means the decrease of 4S .
FIGURE 2. Results of the model 2: (a) the result by
1S , (b) the result by 4S .
MODEL 3 AND RESULT
The model 3 uses a little complex model. Shown at 1ststep of figure 3, the model is consists of a ceiling, a
front wall, a rear wall, two sidewalls, a stage, and afloor. At the 2nd step, vertexes for triangle division are
plotted on each surface except for the stage and floor.At 3rd step, each surface is divided to some trianglesby connecting the vertexes. Two connection patternsare supposed. The coordinates of each vertex areparameterized and optimized. A value that fourpreferences are summed and averaged by 20 listeningpoints is used for evaluation.
Ceiling
Side wallFront wall
Rear wall
Stage Floor
1st Step
2nd Step
1
1 2 3
2
3rd Step
Connection pattern 1
29 10m
45 10m
15 5m
Connection pattern 2
FIGURE 3. The optimization model 3.
Combination of each surfaces connecting pattern
produces eight different initial models. They were all
used for GA optimization. Table 2 shows their details
and evaluation values. Figure 4 shows the optimized
result of md2. Center of the each wall except for the
ceiling is swelling outside. The ceiling is folded along
the centerline of the hall. Two protuberances circled in
figure 4(b) supply sound especially to the corner of the
seats just beside the stage.
Table 2. Each models connection pattern andevaluation value
number ceiling sidewall front/rear wall evaluation value
md1 1 1 1 -0.55
md2 1 1 2 -0.49
md3 1 2 1 -0.60
md4 1 2 2 -0.52
md5 2 1 1 -0.53
md6 2 1 2 -0.52
md7 2 2 1 -0.60md8 2 2 2 -0.60
(b)
(c)FIGURE 4. The result of model 3 (md2): (a) the
whole view, (b) the front view, (c) the left view.
CONCLUDING REMARKS
In conclusion, we would like to state the following
three points.
(1) The subjective preferences used here seem to be
appropriate for evaluating a concert hall from the
similarity of proportions between the optimized
form of model 1 and Grosser Musikvereinssaal.
(2) There is a tradeoff on a concert form between the
preference 1S and 4S .(3) There could be many complex and various forms
having higher preference values than the
conventional shoebox form.
REFERENCES
1. J. H. Holland, Adaptation in Natural and Artificial
Systems, The University of Michigan Press (1975)
2. Y. Ando, Architectural Acoustics, Springer-Verlag New
York (1998)
(a)
S1=-0.20 S4=-0.15
SESSIONS
8/12/2019 Concert hall Acoustic
14/97
SESSIONS
8/12/2019 Concert hall Acoustic
15/97
SESSIONS
8/12/2019 Concert hall Acoustic
16/97
Effects of Scattered Reflections by Array of Columns
Measured after Construction of the Tsuyama-Music-
Cultural Hall
Y. Suzumuraa,b
and Y. Andoa
aGraduate School of Science and Technology, Kobe University, Rokkodai, Nada, Kobe, 657-8501, Japan,
bUrban Design Union, Harbor Land Center Bldg. 1-3-3 Higasi-kawasaki, Chuo, Kobe, 650-0044, Japan
The acoustical design of the Tsuyama-Music-Cultural Hall was made based on the theory of subjective preference. The hall iscalled Bell Fort Tsuyama due to a number of circular columns, realizing the similar effects of scattered reflections by trees ina forest for the sound field of this hall. The array of these circular columns is designed to obtain scattered sound field and to
decrease the value of IACC in the audience seats. In order to examine the quality of the sound field, the four-orthogonal-acoustic
parameters of the sound field were analyzed using the system developed based on the subjective preference theory. From themeasurement of the IACC after construction, it is shown that the sound field of this concert hall is much improved by existing thearray of circular columns.
INTRODUCTION
The purpose of this work is to show that the sound
field in this concert hall is improved by the array of 52circular columns (diameter: 30 cm) installed in front of
the walls both in the audience area and in the stage
enclosure. Effects of these columns on the sound field
in the audience area have been discussed reconfirmed
by a previous study using the 1/10 scale model [4,5].We described in the study that values of IACCdecreased and the initial time delay gap was prolonged
due to the effects of the columns. To calculate the
effects of scattered reflection on sound field is
extremely laborious, in this reason, we adopted the
experimental method to evaluate the sound fieldinvolving scattered reflections.
PROCEDURE
The measurement after construction was made under
the similar condition to 1/10 scale model experiment
previously performed [4,5]. Unfortunately, we couldnot make the measurement without the columns array
in the real hall. An omni-directional loudspeaker was
placed at a height of 1.2m above the center of the stage
as the sound source. Sound signals were recorded
through two microphones at ears entrance of a real
head at 15 seat positions. After obtaining the impulse
response, four-orthogonal-acoustic parameters were
analyzed, and scale values of the subjective preference
were calculated. These four orthogonal acoustic
parameters are listening level (LL), initial time delaybetween the direct sound and the first reflection ( T1),
subsequent reverberation time (Tsub), and magnitude
of the inter-aural cross-correlation (IACC). FIGURE 1
shows the plan ofBell Fort Tsuyama with the array of
circular columns and the15measurement points.
Loudspeaker1
5
913
2
6
10
14
3
7
1115
12
8
4
Columns
FIGURE 1: Plan of the Concert Halland Measurement Points
Measurement points
Column 5m
SESSIONS
8/12/2019 Concert hall Acoustic
17/97
Table 1. Values of IACC Calculated by use of Architectural Scheme and Measured in the Real Hall
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Simulation withoutColumns and Reflectors at
0.52 0.24 0.28 0.28 0.57 0.36 0.27 0.24 0.58 0.52 0.34 0.22 0.45 0.56 0.26
Real Hall with Columns
without reflectors at 500 0.41 0.34 0.36 0.19 0.26 0.40 0.28 0.25 0.15 0.30 0.27 0.28 0.21 0.16 0.20
Simulation without
Columns and Reflectors at0.45 0.16 0.25 0.20 0.51 0.27 0.18 0.10 0.44 0.35 0.21 0.24 0.28 0.51 0.31
Real Hall with Columns
without reflectors at 1000 0.31 0.18 0.14 0.11 0.08 0.23 0.13 0.13 0.23 0.15 0.08 0.12 0.26 0.23 0.09
Simulation without
Columns and Reflectors at0.19 0.31 0.18 0.08 0.26 0.24 0.09 0.20 0.30 0.23 0.18 0.23 0.33 0.47 0.37
Real Hall with Columns
without reflectors at 2000
0.13 0.14 0.14 0.11 0.13 0.09 0.13 0.09 0.14 0.07 0.14 0.07 0.09 0.09 0.08
Calculated and Measured 15 seating Position
RESULTS
Table 1 compares results of the simulation by the use
of architectural scheme (without columns) and the
measurement in the real hall (with columns). These
comparisons can be summarized as follows:1. Values of IACC decrease in side area near
the sidewalls (No.9 15) more than the center area
(No.1 8).
2. The maximum value of IACC appears, in thereal hall, at the center area near the stage at 500Hz.
3. Measured results shows that values of IACCbecome small as the frequency increases. And,
number of audience seats obtaining smaller IACC
increases with increasing frequency due to
columns. These results may be as a typical
scattering effect by columns.
DISCUSSION AND COCLUSION
The acoustical design of this hall was made at three
steps based on the theory of subjective preference. Thefirst is the basic shape planning based on the theory ofsubjective preference, the second is the case study of
the shape of this hall using a computer simulation
system, and the third step is the study about the effects
of the columns array using the scale model of this hall
[5]. It has shown in the third study that the diameter of
the circular column is effective on the frequency of
scattered reflections above 1000 Hz. Columns array
has large effects on the quality of the sound field in a
concert hall and the values of IACC at the seats near
the side walls become small by existing the array of the
circular columns. It should be concluded, from what
has been clarified in this measurement in the real hall,
that these phenomena may be caused by the scattered
reflections of the columns array. The array of the
circular columns is effective on the values of IACC,
especially at above 1000 Hz, and thus improves the
preference of the sound field in this concert hall.
ACKNOWLDGEMENTS
The authors would like to thank I. Yamamoto, and T.
Iizuka for their measurement works of this hall and
Masanao Ohwaki for his cooperation.
REFERENCES
1. Y. Ando, Concert Hall Acoustics, Springer-Verlag, Berlin (1985).
2. Y. Ando, Architectural Acoustics, Blending Sound Sources, SoundFields and Listeners, AIP Press/Springer-Verlag, New York
(1998).
3. H. Sakai, S. Sato, and Y. Ando, J. Acoust. Soc. Am., 104, 1491-1497(1998).
4. Y. Suzumura, Y. Ando, M. Oowaki, T. Iizuka, and I. Yamamoto,
Forum Acusticum, Berlin (1999).5. Y. Suzumura, M. Sakurai, Y. Ando, I. Yamamoto, T. Iizuka, and
M. Oowaki, J. Sound Vib. 232, 303-308 (2000)
SESSIONS
8/12/2019 Concert hall Acoustic
18/97
Blending Architectural and Acoustic Factors in Designing
an Event-hall
A. Takatsua, H. Sakaib, and Y. Andob
aShowa Sekkei Co., 1-2-1-800 Benten, Minato-ku, Osaka 552-0007, Japan
bGraduate School of Science and Technology, Kobe University, Rokkodai, Nada, Kobe 657-8501, Japan
To blend architectural design with acoustic design, a design-process consisting of temporal and spatial factors is proposed. As anapplication of this design-process, a multi-purpose-event-hall, which is the part of complex-architecture, is demonstrated. To
examine the sound field, acoustic measurement was conducted to obtain temporal and spatial factors in a sound field afterconstruction. One goal of this project was to solve acoustic problems caused by the round shape of the event hall, where the
architectural design was previously determined by a certain competition of the complex, in which the architectural concept andtheme was proposed. Nevertheless, the acoustic problems have been solved without unduly affecting the architecture of the hall,and this process would have been considered to be successful. In addition, some knowledge of methods to solve acoustic
problems, caused by the round shaped architecture, was obtained through the designing with the process blending architectural
and acoustic factors.
INTRODUCTION
A process of designing halls and theatres, in which
the temporal and spatial design of architecture is
demonstrated by the temporal and spatial factors of
acoustics, is proposed (Fig. 1). A round-shapedmulti-purpose event hall, the ORBIS Hall (Fig. 2) in a
complex (Kobe Fashion Plaza), was designed using
this process. The sound field was measured to examine
acoustic factors [1,2] after construction.
BLENDING ARCHITECTURAL AND
ACOUSTIC FACTORS
Both of architectural design and acoustic designwere processed by temporal design and spatial factors.
In order to blend architectural design and acoustic
design, it is necessary to consider blending temporal
and spatial design of architecture with temporal and
spatial design of acoustics mutually as shown in Fig. 1.
(1) Blending the temporal factors of architectural
design with those of acoustic design
In order to control appropriate Tsubfor any kind ofevents, a hybrid-reverberation control system was
adopted. The subsequent reverberation time Tsubof this
hall is initially designed for speech. The target value at
500 Hz was 0.7 s in the designing stage. In line with
this, in order to accommodate not only speech but also
events of acoustic sound, an additional system
enhancing subsequent reverberation, which consists of
a reverberation-control-room and an electrical acousticsystem, was designed.
(2) Blending the spatial factors of architectural design
with those of acoustic design
Various equipment and devices including reflectorswere designed to improve IACC and get uniformity of
SPL in the seat area.
REQUIRED CONDITIONS
requirement of customers
social condition
natural condition
ARCHITECTURAL CONCEPT
ACOUSTIC CONCEPT
CONCEPT
UTILIZATION PLAN
FLOW PLANNING SECTION
PREFERENCE AESTHETICS, PROPORTION
ARCHITECTURAL DESIGN
(1) (3) (2)
BLENDING ARCHITECTURAL AND ACOUSTIC DESIGN
t1 IACC
Tsub SPL
ACOUSTIC DESIGN
TEMPORAL DESIGN SPATIAL DESIGN
FIGURE 1. Design process blending architectural designand acoustic design.
(3) Blending the temporal and spatial factors of
architectural design with those of acoustic designUnder-floor space was taken into consideration in
designing a sound field at each seat, since the sound
field below the ears is equally important as well as that
above ears. To eliminate the SPL-dip in the lowfrequency range, sound path to under-floor space,
which is considered as one of the temporal factors
controlled by architectural design, was effective [2]. In
the area in front of end-stage, a perforated floor with5-mm diameter holes in its grid of 15-mm was
designed in order to fuse above- and under-floor space.
The seating areas to the side and in the back have
SESSIONS
8/12/2019 Concert hall Acoustic
19/97
movable chairs that can be stored into the under-floor
as convenient storage. At the steel plates of the chair
basement under the chair legs, there are drilled holes
of a 25% ratio, to the extent that strength permits. This
also allows sound waves to pass through to theunder-floor space, eliminating the dip of
low-frequency-range. In addition, a room for mother
and baby directly facing the end-stage was designed to
prevent echo-disturbance, whispering gallery effect
[3].
opening/closingreflector
reversible reflecor
back stage
m eetingroom room dressingroom
officeticket office
cloak room
atriumfoyer
foyer
bar corner
room for m othersand children
guest room
piano-storage
seating area
center diffusion panel
sm all diffusion panelreversible reflector
heavy-bass speakerunderfloor space
reflecting panel aboveend-stage
FIGURE 2. Plan and section of ORBIS Hall with variousacoustic equipment.
MEASURED RESULTS AND
CONCLUSIONS
After construction, acoustic measurement wasperformed. In the results, the various problems, which
are usually occurred by the round-shaped form, wereexcluded. It is thought that efficiency of the proposed
design-flow was verified, because acoustic problems
could be solved without breaking the architectural
concept under such a worst acoustic condition.
Efficiencies of the various equipment and methods
of acoustic to eliminate acoustic problems of round
shaped hall, are as follows.
(1) Through the temporal design both of architectureand acoustic design, efficiency of the hybrid-
reverberation control system, which consists of
architectural- and electric-acoustic, was verified inmulti- purpose event-hall.
(2) Through the spatial design both of architectural
and acoustic design, the reflector panels in the side of
stage and seating-area are clarified to be efficient to
decrease IACC and to get uniformity of SPL [4].
(3) The room projected at the rear-end of the hall,which has 4.0 m in width and 3.0 m in depth, is
effective to eliminate echo disturbance whispering
gallery effect.
(4) Through both temporal acoustic design and spatial
architectural design, the SPL-dip in the low-frequency
due to the reflection from the floor improvedeffectively by the perforated floor (Fig. 3) [5].
-30
-20
-10
0
10
RelativeSPL
[dB]
()
0 200 400 600 800 1000
Frequency [Hz]
()
-30
-20
-10
0
10
6 m
8 m
10 m
FIGURE 3. Relative SPL as a function of frequency up to
1kHz. (a): Relative SPL on the perforated floor; and (b):Relative SPL on the hard floor.
REFERENCE
1. Ando, Y ., Concert Hall Acoustics, Springer-Verlag,
Heidelberg (1985).2.Ando, Y.,Architectural Acoustics, Blending Sound Sources,
Sound Fields, and Listeners, Springer-Verlag/ AIP Press,
New York (1998).
3.Takatsu, A., Sakai, H., and Ando, Y., Journal of Building
Acoustics7(2), 113-125 (2000).
4.Takatsu, A., Mori, Y., and Ando, Y., The architectural and
acoustic design of a circular event hall in Kobe Fashion
Plaza, in Music and Concert Hall Acoustics, Conference
Proceedings from MCHA 1995, edited by Y. Ando and D.
Noson, Academic Press, London, 1998, Chapter 30.
5.Takatsu, A., Hase, S., Sakai, H., Sato, S., and Ando, Y., J.
Sound Vibration232(1), 263-273 (2000).
SESSIONS
8/12/2019 Concert hall Acoustic
20/97
The Acoustical Renovation of the Palais des Beaux-Arts
Concert Hall in Brussels
D. Commins
commins acoustics workshop, 15, rue Laurence Savart, F-75020 Paris, France,
Originally, the acoustics of Salle Henry-Leboeuf in Brussels was renowned. Over the years, poor maintenance and clumsy
renovations contributed to the deterioration of its acoustics and aesthetics. In the 1990s, measurements were performed and an
extensive investigation of Hortas archives, notes and drawings, was conducted. Most of the details built by Horta were thenexplained and, on this basis, a new renovation programme was decided with, as main goal, the restoration of the originalacoustics of the hall. According to users and audiences, the original acoustics seem to have been recovered.
INTRODUCTION
The main Belgian concert hall, the so-called Salle
Henry le Boeuf of the Brussels Palais des Beaux-Arts
has been inaugurated on October 19, 1929. At the
time, it was considered to be one of the very best
concert halls in the world[1].
The concept and the actual detailed design were led
entirely by the architect himself, Victor Horta, a key
figure of the Art Nouveau school.
Enquiries conducted in 1945 by F. Winckel and
around 1960 by L. Beranek, in particular by
questioning major orchestra conductors, hasconfirmed the reputation of this concert hall: the Salle
Henry le Boeuf was rated then at the level of theGrosser Muzikvereinsaal in Vienna, the
Concertgebouw in Amsterdam and Symphony Hall in
Boston.
The Palais des Beaux-Arts concert hall was famous
for its rich bass response, its intimacy and its warmth
and for enhancing the sound of the violin. This
particular characteristic is of importance since, in
those days, the Belgian school of violin was
considered, with Moscow, to be the best.
Over the years, the hall has been transformed and new
technology has been introduced. Its acoustics
deteriorated: it became dry and lost its extraordinary
bass qualities. The complex wooden stage was
replaced by a concrete box.
A DESCRIPTION OF SALLE HENRY
LE BOEUF
The cross-section of figure 1 shows some detailsintroduced by Horta, including a genuine resonant
chamber under the stage.
FIGURE 1: Original stage cross-section by Horta.
The main parameters are as follows: number of seats
NA : 2150, public area SA = 1300 m2,stage So = 186
m2, total area ST = 1486 m
2, V / SA = 8.4 or 9.4
according to various estimates, V / NA = 5.8 or 6.5
according to various estimates, SA / NA = 0,60, heightof the stage: 92 cm above main floor, first row.
The materials were as of May 1997: ceiling: 75 %
plaster on metal grid, 20 % in heavy glass on heavy
metal structures, damped by a wire mesh (cf. Horta),
5 % of light systems; walls: plaster on brick residue,painted; columns: plaster on concrete; main floor: pine
on 75 mm sleepers on concrete; upper floors: pine
glued directly on concrete; stage floor: wooden floor
on concrete floor ( under the concrete floor Horta
designed a large resonant cavity; originally the floorwas pine with oak veneer as top layer); carpeting:
thick carpet on foam in the stalls, balcony and boxes
(the original carpet was presumably thin or non-
existent); seats of the stalls, dress-circle, balcony and
boxes: absorption on all sides, thick seat and back (not
the original); galleries: upholstered seats, thick woodlayer under the seat and thin wood layer on the back.
SESSIONS
8/12/2019 Concert hall Acoustic
21/97
AN INVENTORY OF KNOWN
MODIFICATIONS
Numerous changes have taken place: an absorptivecarpet has been installed; the seats have been replaced
several times; the original orchestra wooden stage has
been destroyed in the early seventies and replaced by a
concrete stage with a wooden floor on thin sleepers; a
makeshift orchestra pit has been introduced, probably
around 1975, in an attempt to make the room
multipurpose; the room has been painted and even
redecorated several times; the original organ, which
did not seem to be a success when it was inaugurated
in early November 1930, has been destroyed; lightsand other electrical equipment have been modified
several times and many openings have been made in
the ceiling for cables and lights.
THE 1999 RENOVATION
Extensive acoustical measurements have been
performed and a thorough investigation of Hortas
archives has been conducted before renovation.
Measurements before renovation
Most of the MLS tests were performed in the empty
hall but also with a full audience[2].
The hall was found to be quite dry. It is partly due to
the relatively small volume but it is also theconsequence of various low, medium and high
frequency absorption mechanisms that did not exist in
the original design. The room impulse response was
close to the typical response expected from a good
concert hall of elliptical shape.
The renovation
From this data, a very careful renovation was planned
by Architect Georges Baines in an attempt to recover
the original Art Nouveau aspect of the hall and itsoriginal acoustical qualities. The key elements were:the reconstruction of a genuine wooden orchestra
stage with a resonant cavity, a genuine wooden floor
on sleepers in the stalls, the elimination of openings of
various nature, indirect air intake and exhaust,
acoustical insulation.
Measurements after renovation
The measurements performed after completion of the
renovation demonstrate that most of the originalacoustical characteristics have been recovered.
FIGURE 2.View towards the stage
FIGURE 3.Measurements before and after
CONCLUSIONS
Careless renovations of concert halls and opera houses
may considerably alter the acoustics. The example of
the Salle Henry le Boeuf shows that it may be possible
to recover most of the original features.
The author wishes to thank the Palais des Beaux-Artsand the Horta Museum for giving him the opportunity
to analyse this problem. Special thanks are due to Prof.
G. Vermeir for positive contributions during the
construction phase.
REFERENCES
1 L. Beranek,How they sound, concert and opera halls, Woodbury:Acoustical Society of America, 1996, pp. 189-192.
2.D. Commins,Proc. Institute of Acoustics, 19, 213-220 (1997).
0
0,5
1
1,5
2
2,5
3
125 250 500 1000 2000 4000 8000
Frequency
Time(Seconds)
RTBF 1961
Raes 1961
After
renovation
Before
renovation
SESSIONS
8/12/2019 Concert hall Acoustic
22/97
Dissimilarity Judgments in Relation to Temporal and
Spatial Factors for the Sound Field in an Existing Hall
Takuya Hotehama, Shin-ichi Sato and Yoichi Ando
Graduate School of Science and Technology, Kobe University, Rokkodai, Nada, Kobe 657-8501, Japan
To examine the relationships between the subjective attribute and physical factors of sound fields, dissimilarity judgments fordifferent source locations on the stage were performed. This study is based on the model of the auditory-brain system, which
consists of the autocorrelation and crosscorrelation mechanisms for sound signals arriving at two ears and specialization of
human hemispheres. There are three temporal factors (1, 1, e) extracted from the autocorrelation function and four spatial
factors (LL,IACC, IACC, WIACC) from interaural crosscorrelation function of binaural signals. In addition to these temporal andspatial factors, the orthogonal factors of the subjective preference for the sound field were taken into account. The relationships
of the scale value of dissimilarity and these acoustical factors were analyzed by means of the multiple regression analysis. Theresults show that the calculated scale value of dissimilarity agrees with the measured scale value.
INTRODUCTION
A theory of primary sensations and spatialsensations to environmental noise that is based on themodel of the auditory-brain system was previouslyproposed [1, 2]. Primary sensations -loudness, pitch,
timbre and temporal duration- and spatial sensationscan be described by temporal and spatial factors
extracted from the autocorrelation function (ACF) andthe interaural crosscorrelation function (IACF)
respectively. From the ACF analysis, effectiveduration of the envelope of the normalized ACF (e),
the delay time of the first peak (1), and its amplitude
(1) were extracted. From the IACF analysis, thelistening level (LL), IACC, interaural delay time at
which the IACC is defined (IACC) and width of the
IACF at the IACC (WIACC) were extracted. It has beenshown that the environmental noises can becharacterized by these factors [3, 4]. The speech
intelligibility of spoken syllable and the delay time ofa single reflection of sound fields can be calculated bytemporal factors extracted from the ACF [5, 6]. In
concert hall acoustics, the theory of subjectivepreference allows us to calculate the scale values ofsubjective preference in terms of four orthogonalfactors as follows: LL, the initial time-delay gap
between the direct and the first reflection (t1), thesubsequent reverberation time (Tsub) and IACC [1].
In this study, dissimilarity judgments for differentsource locations on the stage in an existing hall wereperformed in order to examine relationships betweenthe subjective attribute and the physical factors based
on the auditory-brain system of sound fields and thetheory of subjective preference by means of
multivariate analysis.
PROCEDURE
Dissimilarity judgments were performed in the"ORBIS Hall" with 400 seats (Figure 1). An anechoicsource of orchestra music ("Water Music" Suite No.2 -Alla Hornpipe by Handel) was used as a source signal.
Six loudspeakers were placed on the stage. Twentylisteners were divided into four groups and seated at
the specific positions. Without moving seat to seat,dissimilarity judgments were performed while
switching the source locations to obtain a scale valueof dissimilarity. The listeners were asked to judge thesubjective difference between the paired stimuli on ascale that have opposite ends: "not different" and"extremely different ". The judgment consisted offifteen pairs that is the possible combinations of sixsound fields at each listener's location. The duration ofthe source signal was 4 s, and the silent interval
between stimuli was 1s. Each pair of sound fields wassepareted by an interval of 5 s, and the pairs arearranged in random order. This session was repeatedfive times.
FIGURE 1. Plan of the "ORBIS Hall". A~D: listeners
locations. 1~6: source locations.
SESSIONS
8/12/2019 Concert hall Acoustic
23/97
MULTIPLE REGRESSION ANALYSIS
In order to examine the relationship between thepsychological distance and physical factors obtained
by acoustical measurements, the data were analyzed bythe multiple regression analysis. For the explanatoryvariables, a distance between paired stimuli wasintroduced by applying the factors extracted from therunning ACF and the running IACF analysis ofrecorded sound signals. In this analysis, the acoustical
factors in relation to subjective preference wereincluded in the explanatory variables, because the
property of sound fields must be taken into account [1].
The explanatory variables were: (1) DLL, (2) D1, (3)
D1, (4) DIACC, (5) DIACC, (6) DWIACC, (7) Dt1and (8)DTsub. In order to construct scale value of dissimilarityamong sound stimuli for the dependent variable, the
original data obtained by dissimilarity judgment werecategorized to seven categories, and a method ofsuccessive categories was applied to the categorizeddata. Correlation coefficients among explanatoryvariables were examined (Table 1). The results showed
that the DWIACC highly correlated with the DIACC. Toavoid the effect of multicollinearity, the DWIACC, whichless correlated with the dependent variable than the
DIACC, were also eliminated from them.In the multiple regression analysis, the distances
for factors were combined linearly due to theexpression given by
D = aDLL+bD1+cD1+dDIACC+eDIACC+fDt1+gDTsub(1)
where a, b, c, d, e, f and gare the coefficients to beevaluated. The coefficients were obtained by a step-
wise regression method.
TABLE 1. Correlation coefficients among explanatory
variables.
RESULTS AND REMARKS
By applying the multiple regression analysis to the
dependent variables and the explanatory variables,regression coefficients were obtained. The partialcorrelation coefficients indicated that the effect ofDIACCwas maximum among all. The D1and the Dt1also contributed to the dissimilarity significantly.
The relationship between the scale value obtained
by dissimilarity judgments and the calculateddissimilarity at each group of four seats is shown in
Figure 2. The correlation coefficient was 0.85 (p 80ms). The frequencies used were the 125 - 1000Hz
octaves, except for the early reflected measurement,
for which the 250 - 1000Hz octaves were used. Ratios
are expressed in dB averaged over the frequency
range.
SESSIONS
8/12/2019 Concert hall Acoustic
57/97
Table. Means and standard deviations of front/back ratios in the two concert halls
Bridgewater Hall, Manchester Waterfront Hall, Belfast
Mean St. Dev. Mean St. Dev.Early front/back ratio (dB) 5.7 2.7 6.0 2.3
Late front/back ratio (dB) 2.3 0.5 2.0 0.8
The two halls are different in design, theManchester hall is parallel-sided whereas the Belfast
hall follows the vineyard terrace scheme. However the
front/back ratios are remarkably similar in the two
halls, see Table. The early and late results for the
Belfast hall are shown in the Figure. The earlyfront/back ratio decreases from the front to the rear of
the hall. We would expect this behaviour due to the
direct sound. However the early reflected sound also
behaves in a similar way, decreasing as one movesaway from the stage. A possible explanation is that
when one is close to the stage, early reflections comefrom the front of the hall; when one is towards the rear
of the hall many reflections arrive from behind.
The behaviour of the late front/back ratio came as a
surprise: it is basically constant. Though the constant
value indicates uniformity, the mean value of 2dB
shows that more reverberant energy arrives from infront. This is not true diffuse behaviour and is, as far
as is known, a new result.
The original hypothesis was that late sound from
the rear might be weak near balcony overhangs. A
weak rear sound would produce a high front/backratio. In the figure there is no evidence of this, the
opposite appears to be more the case with lower values
of the ratio at overhung seats than elsewhere.
CONCLUSIONS
On the evidence of this preliminary exercise, there is
no indication that the front/back ratio matches the
subjective observation of reduced envelopment
perceived near balcony overhangs! The perception oflistener envelopment and sound from behind is clearly
subtle. The differences of view on listener envelop-
ment among researchers needs of course to beresolved. There is also a major need for subjective
evidence from real concerts of perceived LEV and
sound from behind.The measurements reported here provide
interesting new evidence concerning the directional
distribution of reverberant sound in concert halls,
though results from more halls would be welcome.
ACKNOWLEDGMENTS
I am grateful for the help of Dr. J.Y. Jeon during the
measurements.
-2
4
1
11
4
8
2
0
6
2
10
0 10 20 30 40
0 10 20 30 40
Exposed seats:
Overhung seats:
Regression line
Source-receiver distance (m)
Source-receiver distance (m)
Late
front/back
ratio
(dB)
Early
front/back
ratio
(dB)
FIGURE. Individual measured front/back ratios in the
Waterfront Hall, Belfast.
REFERENCES
1. P. Damaske, Acustica 19, 199-213 (1967)
2. A.H. Marshall, J. Sound Vib. 5, 100-112 (1967)
3. M. Morimoto and Z. Maekawa, Proc. 13th ICA,Belgrade, 2, 215-8 (1989)
4. J.S. Bradley and G.A. Soulodre, J. Acoust. Soc. Am 97,
2263-71 and 98, 2590-7 (1995)5. M. Barron Applied Acoustics 62, 185-202 (2001)
6. M. Morimoto and K. Iida, J. Acoust. Soc. Am. 93, 2282(1993)
7. M. Morimoto, K, Iida and K. Sakagami, AppliedAcoustics 62, 109-124 (2001)
8. P. Evjen, J.S. Bradley and S.G. Norcross, AppliedAcoustics 62, 137-153 (2001)
9. T. Hanyu and S. Kimura, Applied Acoustics 62, 155-184(2001)
10.H. Furuya, K. Fujimoto, C. Young Ji and N. Higa,Applied Acoustics 62, 125-136 (2001)
SESSIONS
8/12/2019 Concert hall Acoustic
58/97
Investigation of the Factors Most Important for Determining
the Acoustic Quality of Concert Halls
Y. J. Choi* and F. R. Fricke
Department of Architectural and Design Science, University of Sydney, NSW 2006, Australia,
*E-mail:[email protected]
The purpose of this study is to investigate the acoustic factors that contribute to the overall acoustic quality of concert halls(AQI). The analysis was undertaken using Beranek's six orthogonal parameters (EDT, TI, IACC, Gmid, SDI, and BR) and other
factors such as the number of seats and the hall volume. A neural network analysis was used with inputs of Beraneks parameters
over the frequency range 125-1000Hz. Various combinations of acoustic factors were tried to determine which of Beraneks sixparameters are most significant in accurately predicting AQI and what other facotors are important. It is shown that Beraneks sixfactors can give good prediction of AQI. It is shown that some other combinations of parameters can give predictions as good as
those using Beraneks parameters.
INTRODUCTION
Recently, Beranek [1] suggested six acoustical
features that must be provided for achieving good
acoustics: EDT (Early Decay Time),IACC(Inter-Aural
Cross Correlation), Gmid (the average intensity of the
sound at mid-frequencies), Time to the first reflection(TI), Bass Ratio (BR) and Surface Diffusivity Index
(SDI). Moreover, he indicates how each feature
contributes to the overall acoustic quality of a hall and
provides the preferred values of six features as follows:
IACCE3of 0.3, Gmidof 4 to 5.5 dB, EDT of 2.2 s, TIof
20ms or less, BR of 1.8 s and SDI of 1.0. Beranek's work is based on Ando's investigation[2]
but with two additional factors, BR and SDI. Ando[3]expressed concern about the two added factors and
their orthogonality.
This study is aimed at determining the combination
of factors required for a good concert hall. As a firststep, an independent evaluation of Beranek's approach
was undertaken using Neural Network Analysis. Also,
a modified version of Beranek's theory that used a
combination of some of Beranek's parameters with
geometrical parameters, was examined to see whether
this might give better results.
NEURAL NETWORK ANALYSIS
In the past two decades, Neural Network Analysis
has been extensively studied and applied in solving a
wide variety of problems. NNA is useful for solving
non-linear problems that are not well suited to
traditional methods of analysis. In particular, NNA[4]
is good at pattern recognition and as robust classifiers,
with the ability to generalize in making decisions about
imprecise input data.
The following figure shows the neural network
architecture of this research. In the present study, eight
inputs and one output were used. A neural network
with one hidden layer containing two neurons was
trained.
FIGURE 1. Diagram of the neural network architecture.
RESULTS Neural Network Analyses were undertaken to
investigate the factors which contribute to the
prediction of the acoustic quality of concert halls.
Using the data on 20 halls from Beranek's book[1],
neural networks having different combinations of
inputs were trained over the frequency range 125-
1000Hz.
Networks having different combinations of acoustic
and geometric input parameters were trained. These 17
networks are No.1 (Beranek6+Geo2), No.2
(Beranek6+N), No.3 (Beranek6+V), No.4 (Beranek6),
No.5 (Beranek6-BR+N), No.6 (Beranek6-BR+V),
No.7 (Beranek6-SDI+N), No.8 (Beranek6-SDI+V),
No.9 (Ando4+BR), No.10 (Beranek6-TI), No.11
(Ando4-TI+SDI,V), No.12 (Ando4-TI+SDI,N), No.13
(Ando4), No.14(Ando4-TI+SDI), No.15 (Ando4-
TI+BR), No.16 (Ando4-TI+N) and No.17 (Ando4-
TI+V). Before a Neural Network Analysis was
undertaken, the correlations between the input values
were checked using Statistica software to determine the
orthogonality of the inputs. The inputs are
approximately orthogonal. The correlations in each
octave are slightly different, EDT and Gmid are the
most highly correlated for every frequency band.
EDT
IACC
Gmid
TI
BR
SDI
Volume
Seats
Input Hidden OutputLayer Layer Layer
AcousticQuality
Index (AQI)
SESSIONS
8/12/2019 Concert hall Acoustic
59/97
The results are summarized in Table 1, with standard
deviation ratios (SDRs), over the seven frequency
bands. The SDRs show the degree to which the data
has been fitted (A standard deviation ratio of 0.1 or
lower indicates very good regression performance).The network models that are shown without their
SDRs in Table 1 indicate poor prediction
performances. The SDRs indicate quite different trends
over each octave band, even though the network has
the same input variables.
Table 1.Standard Deviation Ratios (SDR) for 17 Networksover the four octave bands 125Hz-1000Hz and threecombined frequency bands. (No.4 is Beranek's model and
No.13 is Ando's model)
According to the results, Beranek's model shows a
mostly good performance over the each frequency
band. In addition, there are several other network
models that gave good prediction of AQI. The model
having EDT, 1-IACCE3 , Gmid , BR and SDI is good
enough to predict AQI and some factors of Beranek'ssix inputs combined with geometrical data (EDT, 1-
IACCE3 , Gmid , BR, SDI and the number of seats or
volume) show good performances as well.
However, the SDRs do not indicate the interaction
between the inputs. To better understand the
relationships between inputs, Fig.2 presents the AQIresponse surface for the factor of Gmid andN on the
best trained network in the 250Hz octave, using a
modified version of Beranek's approach (EDT, 1-
IACCE3, Gmid, BR, SDI and the number of seats).
The results indicate that the low IACC gives thehighest AQI, as per Beranek and an EDT of 1.71s
would tend to be good. As shown in Fig.2-1, the
highest Gmid of 8-9 dB is preferable, while the
preferred value of TI of 12 ms is the lowest. The
preferred value of SDI would be 1.0. Finally, Fig.2-2
indicates that the preferable value of N would seem to
be 2000-2400 though the relationship with the N is
non-linear.
CONCLUSIONS
In conclusions, there are several network models,
besides Beranek's model which present a goodperformance to predict AQI. Further more, those
models consist of some of Beranek's factors together
with the number of seats and the volume. This
indicates a possibility that geometrical factors could be
one of the significant parameters as well as the
objective parameters to lead to good acoustics quality.
Even though Beranek's model presents one possibility
to give a good prediction of AQI, there is still a
considerable need for further practical investigation of
Beranek's approach on the preferred values and
weightings.
ACKNOWLEDGEMENT
The authors would like to thank Prof.Y.Ando,
Dr.J.S.Bradley, Prof.A.C.Gade, Dr. T.Hidaka, Prof.G.
Vermeir and Prof. M.Vorlaender for allowing access to
the measurement data on specific halls.
REFERENCES
(1) Beranek, L.L.,Concert Halls and Opera Houses: How theysound, American Institute of Physics, Woodbury, 1996.
(2) Ando, Y., Concert hall Acoustics, Springer-Verlag, Berlin, 1985.(3) Ando, Y., Architectural Acoustics: Blending Sound Sources,
Sound Fields, and Listeners, Springer-Verlag, New York, 1998.
(4) Bishop, C., Neural Networks for pattern Recognition, OUP,Oxford, 1995.
Frequency BandsNo.
125Hz 250Hz 500Hz 1kHz125-
250Hz500-1kHz
125-1kHz
1 0.05 0.45 0.21 0.10 0.16 0.09 0.24
2 0.19 0.16 0.11 0.26 0.07 0.23 0.16
3 0.35 0.21 0.52 0.02 - - 0.10
4 0.28 0.17 0.02 0.02 0.14 0.14 0.07
5 0.14 0.09 0.36 0.29 0.31 0.11 0.34
6 0.47 0.14 0.03 0.10 0.38 - 0.13
7 - - - - - - -
8 - 0.22 - - - 0.20 -
9 - - 0.21 - - - -
10 0.28 0.03 0.07 0.14 0.05 - 0.12
11 0.35 0.09 - - - - -
12 0.39 0.05 - 0.10 - - -
13 - - - 0.52 - - -
14 - - 0.25 - - 0.05 -
15 - - - - - - -
16 - - - - - - -17 - - - - - - -
Fig.2-1AQI as a function of Gmidand EDT
Fig.2-2AQI as a function of N and EDT
FIGURE 2. AQI Response Surfaces for the best network in
the 250Hz using a modified version of Beranek's model.
SESSIONS
8/12/2019 Concert hall Acoustic
60/97
Analysis and structural adjustment performed to improve
the acoustics of the "Strehler Theatre" in Milano
G. Zambon and E. Sindoni
Dip.to di Scienze dell'Ambiente e del Territorio, Universit degli Studi di Milano-Bicocca, 20126 Milano, Italy
The analysis and the structural adjustment performed to improve the acoustics of the "Strehler Theatre" in Milano is discussed.
The theatre was originally designed only for drama and, later on, when the Management decided to perform chamber music andlight opera as well, the inadequacy of the acoustic hall soon arose. The Acoustics Laboratory of the Milano-Bicocca University
was addressed to solve the very serious problem.
INTRODUCTION
In 1997 the new theatre "Strehler" was opened inMilano. The theatre was originally designed only for
drama and, later on, when the Management decided to
perform chamber music and light opera as well, the
inadequacy of the hall acoustics soon arose. Not only
the concerts and the opera have been heavily criticized
in the news, but many critics complained even about
the quality of the acoustics for drama performances.
For this reason the Acoustics Laboratory of the
Milano-Bicocca University was addressed for finding a
possible solution to improve the acoustic performance.
FIRST MEASUREMENTS
Reverberation time (T30 )The reverberation time averaged over all the
positions of the theatre hall versus frequency is plotted
in Figure 1.
FIGURE 1. Reverberation time averaged over all the
measurements positions.
It can be noticed that while the T30 values are right
for drama and opera, they are inadequate for concerts,
especially considering that the lower values are taken
when the source is placed in the orchestra pit.
Sound pressure level (LP )The LPvalues decrease very fast with distance from
the source. From the formula of the sound distribution
within a room an approximate value of 0.8 for the
absorption coefficient is obtained and therefore the
theatre hall is fundamentally sound absorbing.
FIRST IMPROVEMENTS
In order to improve the acoustics of the theatre a
series of operations to be carried out gradually was
proposed. The first operation consisted in the
replacement of the absorbing material placed on a largeportion of the side walls (heavy cloth) with a reflecting
material (wood). A second operation was the
replacement of the fitted carpet of the stalls with a
wooden parquet. Thanks to these operations the
reverberation time improved as shown in Figure 2.
FIGURE 2. Increment of reverberation time after the two
operations.
An additional result was the improvement in the
distribution of LP .
0
0.5
1
1.5
2
2.5
3
3.5
125
160
200
250
315
400
500
630
800
1k
1.25k
1.6k
2k
2.5k
3.15k
4k
5k
6.3k
8k
10k
Frequency (HZ)
T30(s)
source on stage
source on pit orchestra
-0.05
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
125
160
200
250
315
400
500
630
800
1k
1,25k
1,6k
2k
2,5k
3,15k
4k
5k
6,3k
8k
10k
Frequency (Hz)
T30
vari
ation
(s)
first operation
second operation
SESSIONS
8/12/2019 Concert hall Acoustic
61/97
ADVANCED MEASUREMENTS
The first changes improved the acoustic quality of
the theatre, but the result was not yet optimized for
some kind of performances such as musical events. A
more accurate characterization of the hall was obtained
by measuring the acoustical parameters: C80, D50,
IACC, ITDG and RASTI in the displayed positions.
FIGURE 3. Position of the receivers.
Table 1 shows the parameters values calculated from
the impulse response.
Table 1. Acoustical parameters in the theatre.
Pos. D50[%] C80[dB] IACC ITDG[ms] RASTI01 40.98 0.19 0.82 35.72 0.90
02 37.66 1.41 0.55 19.91 0.86
03 33.85 0.35 0.59 25.72 0.85
04 35.87 1.01 0.42 39.51 0.69
05 31.82 2.46 0.54 38.86 0.63
06 43.91 2.14 0.63 25.39 0.6907 44.84 3.50 0.48 31.89 0.65
08 57.73 3.57 0.56 17.06 0.67
09 50.94 5.26 0.50 35.74 0.66
10 62.83 4.43 0.40 10.51 0.64
Clarity and Definition index(C80, D50)
The analysis of the data shows that the values eitherfor C80and D50 are low at the first rows but grow to
unacceptable values for concert and symphonic music
away from the stage and the center of the hall. This
behavior is due to the excessive theatre width, the
presence of a leaning-out gallery and a poorly
reflecting ceiling, whose main effect consists in the
severe reduction of the delayed reflections. Near the
stage, where there are no close reflective surface, few
early reflections and many delayed ones generated
from the stage itself are measured. Moving away from
the center and the front of the hall the contribution of
early reflections, coming from side and rear walls,
grows up, while the stage contribution decreases. A
further confirmation of this hypothesis is supported by
the comparison between the shape of the impulse
response of the nearest positions and the farthest ones.
Inter-aural cross correlation (IACC)The values of IACC are rather high away from the
walls and even higher near the symmetry axis of the
stalls. Moving away from the symmetry axis as far as
the sector of the theatre where the seats are turned
towar