AES 122 Farina Advancements In Impulse Response Measurements By Sine Sweeps 226 AES122

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Audio Engineering Society

Convention Paper

Presented at the 122nd Convention

2007 May 5–8 Vienna, Austria

The papers at this Convention have been selected on the basis of a submitted abstract and extended precis that have been peer

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Advancements in impulse response

measurements by sine sweeps

Angelo Farina1

1 University of Parma, Ind. Eng. Dept., Parco Area delle Scienze 181/A, 43100 PARMA, ITALY

farina@unipr.it

ABSTRACT

Sine sweeps are employed since long time for audio and acoustics measurements, but in recent years (2000 and

later) their usage became much larger, thanks to the computational capabilities of modern computers. Recent

research results allow now for a further step in sine sweep measurements, particularly when dealing with the

problem of measuring impulse responses, distortion and when working with systems which are neither time

invariant, nor linear.

The paper presents some of these advancements, and provide experimental results aimed to quantify the

improvement in signal-to-noise ratio, the suppression of pre-ringing, and the techniques employable for performing

these measurements cheaply employing a standard PC and a good-quality sound interface, and currently available

loudspeakers and microphones.

1. INTRODUCTION

At AES-Paris in 2000 a paper of the author [1] did

disclose some "new" possibilities related to sine sweep

measurements, triggering a wave of enthusiasm about

this method. The usage of exponential sine sweep,

compared with previously-employed linear sine sweeps,

provided several advantages in term of signal-to-noise

ratio and management of not-linear systems.

Furthermore, the deconvolution technique based on

convolution in time domain with the time-reversal-

mirror of the test signal allowed for clean separation of

the harmonic distortion products. And the release of the

Aurora software package [2] made it possible to

perform these measurements easily and cheaply for

everyone.

In reality, nothing was really new, as other authors

(Gerzon [3], Griesinger [4]) did already discover these

possibilities. The fact that this approach was not

successfully employed before is mainly due to the lack

of computers with enough computational power and of

easily-usable software tools.

In the following 6 years, many research groups and

professional consultants started using sine sweeps, and a

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lot of papers were published (particularly remarkable

were the JAES papers of Muller/Massarani [5] and of

Embrechts et al. [6]). The tradeoffs of this technique

were understood much better, and it was recognized the

need of further perfecting the measurement technique

for dealing with some problems.

- pre-ringing at low frequency before the arrival of the

direct sound pulse

- sensitivity to abrupt pulsive noises during the

measurement

- skewing of the measured impulse response when the

playback and recording digital clocks were mismatched

- cancellation of the high frequencies in the late part of

the tail when performing synchronous averaging

- time-smearing of the impulse response when

amplitude-based pre-equalization of the test signal was

employed

All of the problems pointed out here have been

investigated, and several solutions have been proposed.

This paper presents these "refinements" to the original

exponential sine sweep technique, and divulgates the

results of some experiments performed for assessing the

effectiveness of these techniques.

The methods analyzed include:

- post-filtering of the time-reversal-mirror inverse filter

for avoiding pre-ringing

- "exact" deconvolution by division in frequency

domain with regularization

- development of equalizing filters to be convolved with

the test signal for pre or post equalization.

- counter-skewing of the measured impulse response

when the playback and recording digital clocks are

mismatched

- employing running-time cross-correlation for

performing proper synchronous averaging without

cancellation effects

The experiments for assessing the behavior of these

"enhanced" measurement techniques were performed

employing a state-of-the-art hardware system, including

a multichannel sound interface, a powerful PC, and

modified versions of the Aurora plugins [2]. Three

rooms were chosen for the test: a small listening room

equipped with a professional surround-sound

monitoring system, a concert hall employing a wide-

band, two-way dodechaedron loudspeaker, and the

passenger's compartment of a car.

Various kinds of microphones were employed too, with

the goal of assessing if the measurement of certain

acoustical quantities, such as the "spatial parameters"

described in ISO 3382, and namely LF, LFC and IACC,

can be reliably measured with currently available top-

brand microphones.

The results show that, whilst some of the proposed

methods really improve substantially the sine sweep

measurement method, solving the problems shown

above, on the other hand the weak part of the

measurement chain is still about transducers, and

namely loudspeakers and microphones, which do not act

always along our expectations, and which can cause

severe artifacts in the measured quantities.

It is therefore concluded that any impulse response

measurement chain can be used with confidence only

after a set of careful preliminary tests and alignments.

Without this, the results are prone to be at least

suspicious, and significant errors have been found in the

experimental tests. Of consequence, it appears necessary

to further improve the current measurements standards,

and mainly ISO 3382, for ensuring reliable and

reproducible measurements employing this (and other)

methods of measuring impulse responses.

2. QUICK REVIEW OF THE EXPONENTIAL

SINE SWEEP (ESS) METHOD

This chapter is recalling the theory already presented in

[1], so the reader has a consequential presentation of the

“basic” method, before discussing problems and

possible enhancements. The reader already knowing this

method can skip directly to chapter 3.

When spatial information is neglected (i.e., both source

and receivers are point and omnidirectional), the whole

information about the room’s transfer function is

contained in its impulse response, under the common

hypothesis that the acoustics of a room is a linear, time-

invariant system.

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This includes both time-domain effects (echoes, discrete

reflections, statistical reverberant tail) and frequency-

domain effects (frequency response, frequency-

dependent reverberation).

The following figure shows how a room can be seen,

under these hypotheses, as a single-input, single-output

“black box”.

“Black Box”

F[x(t)]

Noise n(t)

input x(t) + output y(t)

Fig. 1 – A basic input/output system

The system employed for making impulse response

measurements is conceptually described in fig. 2. A

computer generates a special test signal, which passes

through an audio power amplifier and is emitted through

a loudspeaker placed inside the theatre. The signal

reverberates inside the room, and is captured by a

microphone. After proper preamplification, this

microphonic signal is digitalized by the same computer

which was generating the test signal.

test signal output

Loudspeaker

Microphone Input

Reverberant Acoustic Space

microphone

Portable PC with

full-duplex sound card

Fig. 2 – schematic diagram of the measurement system

A first approximation to the above system is a “black

box”, conceptually described as a Linear, Time

Invariant System, with added some noise to the output,

as shown in fig. 1.

In reality, the loudspeaker is often subjected to not-

linear phenomena, and the subsequent propagation

inside the theatre is not perfectly time-invariant.

The quantity which we are initially interested to

measure is the impulse response of the linear system

h(t), removing the artifacts caused by noise, not-linear

behavior of the loudspeaker and time-variance.

The method chosen, based on an exponential sweep test

signal with aperiodic deconvolution, provides a good

answer to three above problems: the noise rejection is

better than with an MLS signal of the same length, not-

linear effects are perfectly separated from the linear

response, and the usage of a single, long sweep (with no

synchronous averaging) avoids any trouble in case the

system has some time variance.

The mathematical definition of the test signal is as

follows:

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−⋅

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ω

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ω

ω

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ln

T

sin)t(x 1

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ln

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t

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1 (1)

This is a sweep which starts at angular frequency ω1,

ends at angular frequency ω2, taking T seconds.

When this signal, which has constant amplitude and is

followed by some seconds of silence, is played through

the loudspeaker, and the room response is recorded

through the microphone, the resulting signal exhibit the

effects of the reverberation of the room (which

“spreads” horizontally the sweep signal), of the noise

(appearing mainly at low frequencies) and of the not-

linear distortion.

These “distorted” harmonic components appear as

straight lines, above the “main line” which corresponds

with the linear response of the system. Fig. 3 shows

both the signal emitted and the signal re-recorded

through the microphone.

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Fig. 4 – sonograph of the test signal x(t) and of the

response signal y(t)

Now the output signal y(t) has been recorded, and it is

time to post-process it, for extracting the linear system’s

impulse response h(t).

What is done, is to convolve the output signal with a

proper filtering impulse response f(t), defined

mathematically in such a way that:

)t(f)t(y)t(h ⊗= (2)

The tricks here are two:

• to implement the convolution aperiodically, for

avoiding that the resulting impulse response folds

back from the end to the beginning of the time frame

(which would cause the harmonic distortion products

to contaminate the linear response)

• to employ the Time Reversal Mirror approach for

creating the inverse filter f(t)

In practice, f(t) is simply the time-reversal of the test

signal x(t). This makes the inverse filter very long, and

consequently the above convolution operation is very

“heavy” in terms of number of computations and

memory accesses required (on modern processors,

memory accesses are the slower operation, up to 100

times slower than multiplications).

However, the author developed a fast and efficient

convolution technique, which allows for computing the

above convolution in a time which is significantly

shorter than the length of the signal. [7]

It must also be taken into account the fact that the test

signal has not a white (flat) spectrum: due to the fact

that the instantaneous frequency sweeps slowly at low

frequencies, and much faster at high frequencies, the

resulting spectrum is pink (falling down by -3 dB/octave

in a Fourier spectrum). Of course, the inverse filter must

compensate for this: a proper amplitude modulation is

consequently applied to the reversed sweep signal, so

that its amplitude is now increasing by +3 dB/octave, as

shown in fig. 5.

Fig. 5 – Fourier spectrum of the test signal (above)

and of the inverse filter (below)

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When the output signal y(t) is convolved with the

inverse filter f(t), the linear response packs up to an

almost perfect impulse response, with a delay equal to

the length of the test signal. But also the harmonic

distortion responses do pack at precise time delay,

occurring earlier than the linear response. The aperiodic

deconvolution technique avoids that these anticipatory

response folds back inside the time window,

contaminating the late part of the impulse response.

Fig. 6 shows a typical result after the convolution with

the inverse filter has been applied.

Fig. 6 – output signal y(t) convolved

with the inverse filter f(t)

At this point, applying a suitable time window it is

possible to extract just the portion required, containing

only the linear response and discarding the distortion

products.

The advantage of the new technique above the

traditional MLS method can be shown easily, repeating

the measurement in the same conditions and with the

very same equipment. Fig. 7 shows this comparison in

the case of a measurement made in a highly reverberant

space (a church).

It is easy to see how the exponential sine sweep method

produces better S/N ratio, and the disappearance of

those nasty peaks which contaminate the late part of the

MLS responses, actually caused by the slew rate

limitation of the power amplifier and loudspeaker

employed for the measurements, which produce severe

harmonic distortion.

Fig. 7 – comparison between MLS

and sine sweep measurements

This method has nowadays wide usage, and is often

employed for measuring high-quality impulse responses

which are later employed as numerical filters for

applying realistic reverberation and spaciousness during

the production of recorded music [8].

3. PROBLEMS WITH THE ESS METHOD

Despite the significant advantages shown by the ESS

method in comparison with all the other previously-

employed methods, some problems can still be found, as

already pointed out in chapter 1.

In the following subchapters, each of these problems is

analyzed, and proper workarounds are presented.

3.1. Pre-ringing

The measured impulse response often shows some

significant pre-ringing before the arrival of the direct

sound.

Linear im

p

ulse res

p

onse

2nd harmonic response

5th harmonic response

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This is easily shown performing directly the

deconvolution of the IR from the original test signal,

without having it passing through the system-under-test.

This way, one should get a theoretically-perfect Dirac’s

delta function. The old MLS method is perfect in this

case, providing exactly a theoretical pulse. The

following figure shows instead what happens with the

standard ESS method.

Fig. 8 – pre-ringing artifact with fade-out

As shown in fig. 8, the peak is in reality some sort of

Sync function, and it shows a number of damped

oscillations both before and after the main peak. This is

due to the limited bandwidth of the signal (22 Hz to 22

kHz, in this case) and to the presence of some fade-in

and fade-out on the envelope of the test signal (0.1s in

this example, employing a 15s-long ESS). These two

factors define substantially a trapezoidal window in the

frequency-domain, which becomes the Sync-like

function in time domain.

However, the situation ameliorates significantly if we

remove the fade-out. The following figure show the

results obtained with exactly the same settings as in the

previous case, but with a length of the fade-in set to 0.0s

(fade-in is still 0.1s).

Albeit the appearance of the waveform looks the same

(due to the “analogue waveform” display of Adobe

Audition), looking carefully at the digital values (the

small squares along the waveform) one now sees that

the results are very close to a theoretical Dirac’s Delta

function, and that no pre-ringing or post-ringing are

anymore significantly present.

Fig. 9 – reduced pre-ringing artifact without fade-out

However, it is not a good idea to remove completely the

fade-out: at the end of the sweep, the final value

computed could be not-zero, and consequently the

sound system will be excited with a step function, which

spreads a lot of energy all along the spectrum.

A solution alternative to removing the fade-out is to

continue the sweep up to the Nyquist frequency (22050

Hz, in our example, as the sampling rate was 44.1 kHz),

and cutting it manually at the latest zero-crossing before

its abrupt termination. This way, no pulsive sound is

generated at the end, and the full-bandwidth of the

sweep removes almost completely the high-frequency

pre-ringing.

However, in some cases, also low frequencies can cause

a significant pre-ringing. This is shown easily

employing a “loopback” connection, that is, connecting

a wire directly from the output to the input of the sound

card.

The following figure shows the result of a “loopback”

measurement, employing the same parameters as for the

previous example (fs=44100 Hz, sweep from 22 Hz to

22050 Hz, 15s long, 0.1s fade-in, no fade-out).

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Fig. 10 – low-frequency pre-ringing artifact

Removing the fade-in does not provide any benefit, in

this case. So, the way of controlling this type of pre-

ringing (due to the analog equipment) is to create a

proper time-packing filter, and to apply it to the

measured IR.

A packing filter is a filter capable of compacting the

time-signature of the impulse response. Various

methods for creating a numerical approximation to an

ideal packing filter have been proposed in the past. The

method employed here is the one developed by Ole

Kirkeby, when working at the ISVR with prof. Nelson

[9]. Although Kirkeby did propose this method for

multichannel inversion (cross-talk cancellation), it can

be successfully employed also just for the purpose of

packing in time the transfer function of a single-input,

single-output system.

The Kirkeby algorithm is as follows:

1) The IR to be inverted is FFT transformed to

frequency domain:

H(f) = FFT [h(f)] (3)

2) The computation of the inverse filter is done in

frequency domain:

() ()

[]

()

[]

() ()

ffHfHConj

fHConj

fC ε+⋅

= (4)

Where ε(f) is a small regularization parameter,

which can be frequency-dependent, so that the

inversion does not operates outside the

frequency range covered by the sine sweep

3) Finally, an IFFT brings back the inverse filter

to time domain:

c(t) = IFFT [C(f)] (5)

Usually the regularization parameter ε(f) is choosen

with a very small value inside the frequency range

covered by the sine sweep, and a much larger value

outside that frequency range, as shown in the following

figure:

εest

εint

flow fhigh

ΔfΔf

Fig. 11 – frequency-dependent regularization parameter

The following figure shows the inverse filter computed

for compacting the “loopback” IR shown in fig. 10:

Fig. 12 – “compacting” inverse Kirkeby filter

When this filter is convolved with the measured

“loopback” IR shown in fig. 10, the result is the one

shown in the next figure:

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Fig. 13 – “loopback” IR convolved with the

“compacting” inverse Kirkeby filter

It can be seen that the usage of the inverse filter

managed to re-pack the measured IR back to an almost

perfect Dirac’s Delta function.

In conclusion, pre-ringing artifacts can be substantially

avoided by combining the usage of a wide-band sweep

running up to the Nyquist frequency, without any fade-

out, and the usage of a suitable “compacting” inverse

filter, computed with the Kirkeby method from a

“reference” impulse response.

In the example shown here, the “reference”

measurement for computing the inverse filter has been

performed electrically, so it does not contain the effect

of power amplifier, loudspeaker and microphones. This

makes sense if the goal of the measurement is to get

information about the behaviour of these

electroacoustics components (in most cases, for

measuring the performances of the loudspeaker).

3.2. Equalization of the equipment

In other cases, in which the goal of the measurement is

just to analyze the acoustical transfer function between

an “ideal” sound source and an “ideal” receiver, also the

effect of the electroacoustical devices should be

removed. In this case, the “reference” measurement is a

complete anechoic measurement including power

amplifier, loudspeaker and microphone, and the Kirkeby

inverse filter will remove any time-domain and

frequency-domain artifact caused by the whole

measurement system.

For example, the following figure shows the anechoic

measurement of the transfer function of a

loudspeaker+microphone setup:

Fig. 14 – measurement of the “reference” IR of an

artificial mouth and an omnidirectional microphone

This example refers to a small, limited-range

loudspeaker, employed in a head-and-torso simulator.

The measured IR and its frequency response are shown

in the following pictures:

Fig. 15 – measured IR of the artificial mouth system

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Fig. 16 – measured frequency response of the artificial

mouth system

Again, a Kirkeby inverse filter is computed, for

correcting the transfer function of the whole

measurement system (this time the usable frequency

range has been narrowed to 10-11000 Hz):

Fig. 17 – “equalizing” inverse Kirkeby filter

When this inverse filter is applied (by convolution) to

the measured IR of this artificial mouth system, we get

an IR and a frequency response as shown here below:

Fig. 18 – measured IR of the artificial mouth system

after equalization with the inverse filter

Fig. 19 – measured frequency response of the artificial

mouth system after equalization

Although in this case the inverse filter did not manage

to provide a “perfect” result, it still caused the transfer

function of the system to closely approach the “ideal”

one. This way, the electroacoustical sound system can

be employed for measurements without any significant

biasing effect.

The latter point to be discussed is if it is better to apply

this equalizing filter to the test signal before playing it

through the system, or to the recorded signal

(indifferently before or after the deconvolution).

Both approaches have some advantages and

disadvantages. Applying the equalizing filter to the test

signal usually results in a weaker test signals being

radiated by the loudspeaker, and in clipping at extreme

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frequencies (where the boost provided by the equalizing

filter is greater).

On the other hand, the usage of the filter after the

measurement is done results in “colouring” the

spectrum of the background noise, which can, in some

case, become audible and disturbing.

In practice, has it often happens, the better strategy

revealed to be hybrid: the test signal is first roughly

equalized, employing one of the standard tools provided

by Adobe Audition (for example Graphic Equalizer).

This allows to limit the boost at extreme frequencies

and the gain loss at medium frequencies, but however

the radiates sound becomes already almost flat.

Then, as usual, a reference anechoic measurement is

performed (employing the pre-equalized test signal); a

Kirkeby inverse filter is thereafter computed, with the

goal of removing the residual colouring of the

measurement system. This inverse filter is applied as a

post-filter, to the measured data, ensuring that the total

transfer function of the measurement system is made

perfectly flat. This is the approach successfully

employed in the Waves project, as described in more

detail in [8].

3.3. Pulsive noises during the measurement

When long sweeps are employed for improving the

signal-to-noise ratio, the risk that some pulsive noise

occurs during the measurement increases, as it is

difficult to keep people perfectly still for more than a

few seconds. Typical sources of pulsive noise are

objects falling on the floor, seats being moved, or

“cracks” caused by steps over wooden floors.

The following sonogram shows a recorded sweep

contaminated by an evident spurious pulsive event (the

vertical line), caused by an object falling on the floor.

Fig. 20 – pulsive event contaminating an ESS

measurement

After convolution with the inverse filter, this pulsive

event causes a quite evident artifact on the deconvolved

IR, as shown here:

Fig. 21 – Artifact caused by a pulsive event

In practice, the artifact is a sort of frequency-decreasing

sweep, starting well before the beginning of the linear

impulse response, and continuing after it. The first part

is practically irrelevant on the linear IR, as it will be cut

away together with the harmonic distortion responses.

However, the part of this spurious sweep occurring in

the late part of the measurement can cause severe

problems. In particular, when analyzing the reverberant

tail, this artifact is causing large errors on the estimate

of the reverberation time and of the other acoustical

parameters computed according to ISO 3382. The

following figure shows a comparison between the

octave-band-filtered IR with and without contamination

by the spurious pulsive noise.

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Fig. 22 – octave-band filtered IR (at 1 kHz)

contaminated from pulsive noise (above)

and without contamination (below)

The presence of the spurious effect generated by the

pulsive noise is causing an overestimate of T30 (2.48 s

instead of 2.13 s). Also Clarity C80 and Center Time are

affected, but more lightly.

One way of removing this artifact consists in silencing

the recording signal in correspondence of the pulsive

event, as shown in the following figure:

Fig. 23 – silencing the spurious event

After deconvolving the edited signal, the following IR is

obtained:

Fig. 24 – effect of the silenced pulsive event

on the deconvolved IR

Despite silencing the event, the artifact is still there,

albeit with reduced amplitude. The analysis of the

reverberant tail still shows some effect of the pulsive

artifact, as shown here:

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Fig. 25 – octave-band filtered IR

with silenced pulsive event

A much better removal of the pulsive event is obtained

by employing the Click/Pop Eliminator provided by

Adobe Audition. The following picture shows how it

works:

Fig. 26 – effect of the Auto Click/Pop Eliminator

In this case, the result of the deconvolution is the

following:

Fig. 27 – effect of the pulsive event

on the deconvolved IR after click/pop Eliminator

The artifact has been further reduced, but it is still there.

Finally, an even better way of removing the artifact is

based on the knowledge of the frequency of the sine

sweep at the moment in which the pulsive event did

happen. In the case presented here, the instantaneous

frequency was 2159 Hz. So, applying a narrow-

passband filter at this exact frequency, all the wide-band

noise is removed, and a “clean” sinusoidal waveform is

restored, as shown in the following figures:

Fig. 28 – usage of FFT Filter for removing the pulsive

artifact

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Fig. 29 – effect of FFT filter for removing

the pulsive artifact

After deconvolution, the measured impulse response is

as follows:

Fig. 30 – result of the FFT filter

Now the artifact amplitude has been reduced so much

that there is no more distortion of the reverberant tail, as

shown here:

Fig. 31 – octave-band filtered IR

with pulsive event removed with FFT filter

So it can be concluded that the best way of removing a

pulsive artifact from a sweep measurement is to apply a

narrow-band filter just around the instantaneous

frequency at which the event occurred.

3.4. Clock mismatch

One of the great advantages of the ESS method over

other methods for measuring the impulse response is

that a tight synchronization between the playback clock

and the recording clock is not required.

In fact, even if two completely independent hardware

devices are employed, and no clock synchronization is

employed, usually the impulse response obtained is

perfectly clean and without observable artifacts.

However, when the mismatch between the two clocks

becomes significant, the deconvolved impulse response

starts to be “skewed” in the frequency-time plane.

For example, the following figure shows the result of a

purely-electrical measurement, obtained playing the test

signal with a portable CD player, directly wired to a

computer sound card, employed for recording.

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Fig. 32 – a skewed IR

The waveform clearly shows that low frequencies are

starting earlier than high frequencies, and the sonograph

demonstrates that, with a logarithmic frequency scale,

the IR does not have a vertical (synchronous)

appearance, but a sloped (skewed) appearance.

Various methods can be applied for re-aligning the

clocks. For example, if a “reference” measurement can

be performed, we could try to use a Kirkeby inverse

filter for fixing the mismatch, as already shown in

chapters 3.1 and 3.2.

The following figure show the result of such an inverse

filter applied to the electrical measurement performed.

Fig. 33 – correction of a skewed IR employing a

Kirkeby inverse filter

The result obtained employing the inverse filter is quite

good; and it is also correcting for the magnitude of the

frequency response of the system, not only for the

frequency-dependent delay.

Nevertheless, this approach requires the availability of a

clean reference measurement, performed either

electrically (as in this example) or under anechoic

conditions.

Whenever a reference measurement is not available, the

inverse filter approach cannot be employed. Another

possible solution is the usage of a pre-strecthed inverse

filter for performing the IR deconvolution.

For example, in this example it can be seen how the

original inverse filter is too short. If we now create an

inverse filter slightly longer than the original one, we

can correct for the skewness of the sonograph.

Looking again at fig. 32, we see that the skewness is

approximately 8.5 ms long. So we generate a new sine

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 15 of 21

sweep, and its inverse sweep, 8.5 ms longer than the

original one.

When we convolve this longer inverse sweep with the

recorded signal, the deconvolution produces the

following result:

Fig. 34 – correction of a skewed measurement

employing deconvolution with a longer inverse sweep

This result is not so clean as the one obtained with the

Kirkeby inversion, but now we have got a quite good

clock realignment without the need of a reference

measurement.

It must be said, however, that a skewed impulse

response, although bad to see and to listen, is still quite

usable for computing acoustical parameters. It is

nevertheless always useful to correct for the clock

mismatch, as this significantly improves the peak-to-

noise ratio. For example, with the data presented here,

the usage of the longer inverse sweep for the

deconvolution provides an amelioration of the peak-to-

noise ratio by 12.45 dB, which is quite significant.

3.5. Time averaging

The usage of averaging several impulse responses for

improving the signal-to-noise ratio is a deprecated

technology when working with the ESS method.

Synchronous time averaging works only if the whole

system is perfectly time-invariant. This is never the case

when the system involves propagation of the sound in

air, due to air movement and change of the air

temperature. So, the preferred way for improving the

signal to noise ratio is not to average a number of

distinct measurements, but instead to perform a single,

very long sweep measurement, as clearly recommended

in the ISO 18233/2006 standard.

However, in some cases the usage of long sweeps is not

allowed (for example, when the method is implemented

on small, portable devices equipped with little memory),

and so time-synchronous averaging is the only way for

getting results in a noisy environment.

Unfortunately, even a very slight time-variance of the

system produces substantial artifacts in the late part of

the reverberant tail, and at higher frequencies.

This happens because the sound arriving after a longer

path is more subject to the variability of the time-of

flight due to unstable atmospheric conditions.

Furthermore, a given differential time delay translates in

a phase error which increases with frequency.

The following picture compares the sonographs of two

IRS, the first comes from a single, long sweep of 50s,

the second from the average of a series of 50 short

sweeps of 1s each.

Fig. 35 – single sweep of 50s (above)

versus 50 sweeps of 1s (below)

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 16 of 21

Although from the above picture it is not very easy to

see the difference, it can be noted that the energy of the

reverberant tail is significantly underestimated, at high

frequency, in the second measurement. This can be seen

easily displaying the spectrum of the signal in the range

100 ms to 300 ms after the direct sound, as shown here:

Fig. 36 – spectrum of single sweep of 50s (above)

versus 50 sweeps of 1s (below)

It can be seen how, above 350 Hz, the synchronously-

averaged IR is systematically underestimated. Around

5-6 kHz the underestimation is more than 10 dB.

This of course affects also the slope of the decay curve,

and the estimate of reverberation times. The following

figure shows the comparison between the octave-band

filtered impulse response and decay curves at 4 kHz:

Fig. 37 – octave-band-filtered impulse response

of a single sweep of 50s (above)

versus 50 sweeps of 1s (below)

It can be seen how the single-sweep measurement is

providing a perfectly linear decay with quite good

dynamic range (63 dB), whilst the synchronously-

averaged IR exhibit strong underestimate of the energy

of the reverberant tail, and simultaneously a much worst

signal-to-noise ratio (43 dB).

It can be concluded that synchronously-averaging a

number of subsequent IRs obtained with the ESS

method is causing unacceptable artifacts.

However, an alternative technique can be used, in these

cases, for processing the data.

It is necessary to create a stereo file, containing the test

signal in the left channel, and the recorded signal in the

right channel, as shown here:

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 17 of 21

Fig. 38 – multisweep signal (test and response)

Now this stereo waveform is processed with the new

Aurora plugin named Cross Functions, which is

employed for computing the transfer function H1, by

performing complex averaging in spectral domain:

()

LL

LR

1G

G

fH = (5)

Where GLR and GLL are the averaged cross-spectrum

and autospectrum, respectively

This is the user’s interface of this plugin:

Fig. 39 – Computation of H1

Only the first half of the resulting transfer function is

kept, for removing most of the effects of the Hanning

window. The following figure shows the recovered

impulse response, compared with the single-sweep one:

Fig. 40 – single sweep of 50s (above)

versus 50 sweeps of 1s (below)

processed with the Cross Functions module

Analyzing the octave-band-filtered impulse response (at

4 kHz), the following is obtained:

Fig. 41 – octave-band-filtered impulse response

of a 50 sweeps of 1s (Cross Functions)

It can be seen that the situation is now significantly

better than with “standard” time-synchronous

averaging: the frequency-domain processing provided

an impulse response with better signal-to-noise ratio and

with a reverberant tail only slightly underestimated. The

single sweep method is still better, but now the

difference is not so large, and the measurement result is

still usable.

So, in practice, the employment of a number of

independent sweeps can provide almost acceptable

results, provided that the deconvolution and averaging

of the impulse response are performed in reversed order

(first averaging, then deconvolution), and in the

frequency domain.

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 18 of 21

4. PERFORMANCE OF ELECTROACOUSTIC

TRANSDUCERS

For room acoustics measurements, it is common to

employ:

• An omnidirectional loudspeaker (dodecahedron)

• An Omni + Figure of Eight microphone

• A binaural microphone (dummy head)

In the previous chapter it has been already discussed

how to measure the impulse response and frequency

response of a measurement chain containing also

loudspeakers and microphones, and how to reasonably

equalize it. However, the problem still arises of the

spatial properties (directivity) of these transducers.

It will be shown here that the measured directivities of

loudspeakers and microphones differ significantly from

the nominal ones, causing errors which are orders of

magnitude greater than those described in the previous

chapter.

4.1. Dodechaedron loudspeakers

These loudspeakers are usually employing single-way,

wide-band transducers, and require heavy equalization

fro providing flat sound power response. However, the

equalization cannot correct the polar patterns of these

loudspeakers, which deviate significantly from

omnidirectional starting at frequencies above 1 kHz.

Here we present the results of polar patterns measured

in anechoic conditions for three dodechaedrons. The

first one is a standard-size (40cm diameter) employing

for building acoustics measurements (LookLine D-300);

the second one is a smaller version (25 cm diameter)

specifically developed for measurement of impulse

responses in theaters and concert halls (Look Line D-

100). Finally, the third one employs waveguides for

reconstructing a more uniform spherical wavefront

(Omnisonics 1000).

The following figure shows the three dodechaedrons

analyzed:

Fig. 42 – 3 dodechaedron loudspeakers

The above loudspeakers have been measured inside an

anechoic chamber over a turntable, so the horizontal

polar patterns have been obtained, in octave-bands.

The following three figures compare these polar

patterns at 1000, 2000 and 4000 Hz.

Horizontal Polar Plot - LookLine D300 - 1000 Hz

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Horizontal Polar Plot - Omnisonic - 1000 Hz

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Fig. 43 – directivity patterns at 1 kHz

Horizontal Polar Plot - LookLine D300 - 2000 Hz

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Horizontal Polar Plot - LookLine D200 - 2000 Hz

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Horizontal Polar Plot - Omnisonic - 2000 Hz

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Fig. 44 – directivity patterns at 2 kHz

Horizontal Polar Plot - LookLine D300 - 4000 Hz

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Horizontal Polar Plot - LookLine D200 - 4000 Hz

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Horizontal Polar Plot - Omnisonic - 4000 Hz

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Fig. 45 – directivity patterns at 4 kHz

It can be seen how all three these dodecaedrons exhibit

quite irregular polar patterns at medium-high frequency.

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 19 of 21

4.2. Omni + Figure of 8 mics

Although the usage of small-size measurement

microphones does not pose any significant problem (as

a B&K ½” capsule is almost perfectly omnidirectional

and with flat frequency response up to 20 kHz), when

spatial parameters such as LE, LF or LFC need to be

measured it is necessary to employ a variable-

directivity-pattern mike, providing both omnidirectional

and figure-of-8 patterns.

For this purpose, it is common to employ not-

measurement-grade probes, often manufactured by top-

quality makers such as Neumann or Schoeps. However,

the values of spatial parameters measured with different

microphonic probes are often quite unreproducible.

So it was decided to perform a comparative experiment

among 4 of these dual-pattern probes, including these

mikes:

• Soundfield ST-250

• Bruel & Kjaer sound instensity kit type 3595

• Schoeps CMC5

• Neumann TLM 170R

The following image shows some of the probes being

compared, during the measurements performed inside

the Auditorium of Parma:

Fig. 46 – 3 microphonic probes

A stereo impulse response has been measured with each

probe, containing the Omni response on the left channel,

and the figure-of-8 response in the right channel. Each

of these 2-channels IRs have been processed with the

Aurora plugin named Acoustical Paramaters, specifying

the type of probe being employed, as shown here:

Fig. 47 – the Acoustical Parameters plugin

This way, the LF parameter has been measuring for all 4

probes, in octave bands, and at two distances from the

sound source (7.5m and 25m). The following figure

shows the results at 25m:

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 20 of 21

Comparison LF - measure 2 - 25m distance

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Fig. 48 – LF measured at 25m

It can be seen how the results are completely diverging;

it is impossible to establish what of the 4 probes was

measuring correctly, albeit the Schoeps looks more

“reasonable” than the other three.

These deviations are caused by the polar patterns of the

probes. As an example, here we report a couple of polar

patterns of the Soundfield ST-250, measured on a

turntable inside an anechoic room:

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Fig. 49 – ST-250 – polar patterns at 500 Hz and 2 kHz

It can be seen that, even at medium frequencies, the

figure-of-8 pattern is distorted, and is not properly gain-

matched with the omnidirectional one. These deviations

are even greater at very low and very high frequencies,

as shown here:

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Fig. 50 – ST-250 – polar patterns at 125 Hz and 8 kHz

It can be concluded that actually no available

microphonic system can be used for assessing reliably

the values of spatial acoustical parameters such as LE,

LF or LFC.

4.3. Binaural microphones

Another way of assessing the spatial properties of a

room is by means of the IACC parameter (inter aural

cross correlation), also defined in ISO-3382, and

measurable employing a binaural microphone and the

Aurora Acoustical Parameter plugin.

However, various makers of dummy heads produce

quite different microphone assemblies. For checking

comparatively their performances, a set of impulse

response measurements have been performed in a large

anechoic chamber, employing a turntable controlled by

the sound card, as shown in the following figure:

Farina

Impulse Response measurements

AES 122nd Convention, Vienna, Austria, 2007 May 5–8

Page 21 of 21

Fig. 51 – anechoic measurements on dummy heads

Also in this case 4 different binaural microphones have

been tested:

• Bruel & Kjaer type 4100

• Cortex

• Head Acoustics HMS-III

• Neumann KU-100

A synthetic diffuse sound field has been generated,

employing a number of loudspeakers surrounding the

dummy head and feeding them with uncorrelated pink

noise.

In principle, given the fact that the sound field was

exactly the same, all the dummy heads should have

given the same value of IACC. Instead, as shown in the

following figure, the results have been quite diverging:

IACCe - random incidence

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Fig. 52 – IACC measured with the 4 dummy heads

The deviations, however, are not so bad as those

obtained in the previous chapter for the measurement of

LF. It can be concluded that, with currently available

systems, the measurement of IACC is slightly more

reproducible than that of LF.

5. ACKNOWLEDGEMENTS

This work was supported by LAE (www.laegroup.org).

6. REFERENCES

[1] A.Farina – “Simultaneous measurement of impulse

response and distortion with a swept-sine

technique”, 110th AES Convention, February 2000.

[2] www.aurora-plugins.com

[3] P.Craven, M.Gerzon - "Practical Adaptive Room

And Loudspeaker Equaliser for Hi-Fi Use" - 92nd

AES Convention, March 1992

[4] D.Griesinger - "Beyond MLS - Occupied Hall

Measurement With FFT Techniques" - 101st AES

Convention, Nov 1996

[5] S. Müller, P. Massarani – “Transfer-Function

Measurement with Sweeps”, JAES Vol. 49,

Number 6 pp. 443 (2001).

[6] G. Stan, J.J. Embrechts, D. Archambeau –

“Comparison of Different Impulse Response

Measurement Techniques”, JAES Vol. 50, No. 4, p.

249, 2002 April.

[7] A. Torger, A. Farina – “Real-time partitioned

convolution for Ambiophonics surround sound”,

2001 IEEE Workshop on Applications of Signal

Processing to Audio and Acoustics - Mohonk

Mountain House New Paltz, New York October 21-

24, 2001.

[8] A. Farina, R. Ayalon – “Recording concert hall

acoustics for posterity” - 24th AES Conference on

Multichannel Audio, Banff, Canada, 26-28 June

2003

[9] O. Kirkeby, P. A. Nelson, H. Hamada, “The "Stereo

Dipole" - A Virtual Source Imaging System Using

Two Closely Spaced Loudspeakers” – JAES vol.

46, n. 5, 1998 May, pp. 387-395.