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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.

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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.

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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

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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

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The Application of Neural Network Analysis to Auditorium

Acoustics

F. Fricke

Department of Architectural and Design Science, University of Sydney, NSW 2006, Australia.

[email protected]

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

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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

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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

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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


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


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


14/97

SESSIONS


15/97

SESSIONS


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


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


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


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


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


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


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,

[email protected]

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


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


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


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


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


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


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


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


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

concert hall acoustic

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