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.

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-reversalmirror 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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Impulse Response measurements

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

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 wideband, 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 topbrand 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.

- "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

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.

- 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

QUICK REVIEW OF THE EXPONENTIAL
SINE SWEEP (ESS) METHOD

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, timeinvariant system.

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This includes both time-domain effects (echoes, discrete
reflections, statistical reverberant tail) and frequencydomain effects (frequency response, frequencydependent reverberation).

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 following figure shows how a room can be seen,
under these hypotheses, as a single-input, single-output
“black box”.

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, notlinear 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.

Noise n(t)

input x(t)

output y(t)

“Black Box”
F[x(t)]

The mathematical definition of the test signal is as
follows:
⎤
⎡
⎛ t ⎛⎜ ω2 ⎞⎟ ⎞⎥
⎢
⋅ln ⎜
⎟
⎜
⎟
ω ⋅T
T ⎝ ω1 ⎠
x ( t ) = sin ⎢ 1
⋅⎜e
− 1⎟ ⎥
⎢ ⎛ω ⎞ ⎜
⎟⎥
2
⎟⎥
⎟⎟ ⎜
⎢ ln⎜⎜
⎠⎥
⎝
⎢⎣ ⎝ ω1 ⎠
⎦

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.
Reverberant Acoustic Space
Portable PC with
full-duplex sound card

Loudspeaker

microphone

(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 notlinear distortion.

test signal output

Microphone Input

Fig. 2 – schematic diagram of the measurement system

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.

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 notlinear phenomena, and the subsequent propagation
inside the theatre is not perfectly time-invariant.

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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. 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:

h ( t ) = y( t ) ⊗ f ( t )

(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,

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.

2nd harmonic response
5th harmonic response

Fig. 7 – comparison between MLS
and sine sweep measurements

Linear impulse response

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.

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 previouslyemployed 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.

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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. 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.

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).

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).

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.

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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:
Δf

Δf

flow

fhigh

εest

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 preringing (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.

εint

Fig. 11 – frequency-dependent regularization parameter
The following figure shows the inverse filter computed
for compacting the “loopback” IR shown in fig. 10:

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:

Conj[H(f )]
C(f ) =
Conj[H(f )] ⋅ H(f ) + ε(f )

(4)

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:

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

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For example, the following figure shows the anechoic
measurement of the transfer function of a
loudspeaker+microphone setup:

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 fadeout, and the usage of a suitable “compacting” inverse
filter, computed with the Kirkeby method from a
“reference” impulse response.

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:

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.

Fig. 15 – measured IR of the artificial mouth system

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Fig. 18 – measured IR of the artificial mouth system
after equalization with the inverse filter
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. 19 – measured frequency response of the artificial
mouth system after equalization

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:

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.

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:

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. 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. 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 narrowpassband 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. 26 – effect of the Auto Click/Pop Eliminator
In this case, the result of the deconvolution is the
following:

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

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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.
Fig. 29 – effect of FFT filter for removing
the pulsive artifact
After deconvolution, the measured impulse response is
as follows:

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.

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:

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Fig. 33 – correction of a skewed IR employing a
Kirkeby inverse filter

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.

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

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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:

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.

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.

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.

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-tonoise ratio. For example, with the data presented here,
the usage of the longer inverse sweep for the
deconvolution provides an amelioration of the peak-tonoise ratio by 12.45 dB, which is quite significant.
Fig. 35 – single sweep of 50s (above)
versus 50 sweeps of 1s (below)

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 15 of 21

Farina

Impulse Response measurements

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. 37 – octave-band-filtered impulse response
of a single sweep of 50s (above)
versus 50 sweeps of 1s (below)
Fig. 36 – spectrum of single sweep of 50s (above)
versus 50 sweeps of 1s (below)
It can be seen how, above 350 Hz, the synchronouslyaveraged 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:

It can be seen how the single-sweep measurement is
providing a perfectly linear decay with quite good
dynamic range (63 dB), whilst the synchronouslyaveraged 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:

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 16 of 21

Farina

Impulse Response measurements

window. The following figure shows the recovered
impulse response, compared with the single-sweep one:

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:

H1 (f ) =

G LR
G LL

(5)

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:

Where GLR and GLL are the averaged cross-spectrum
and autospectrum, respectively
This is the user’s interface of this plugin:

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.

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

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.

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 17 of 21

Farina

Impulse Response measurements

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)

Fig. 42 – 3 dodechaedron loudspeakers

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.

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

Horizontal Polar Plot - LookLine D200 - 1000 Hz

0
5 10
15 20

3503550
340345
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270
-40
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190185

Dodechaedron loudspeakers

180

Horizontal Polar Plot - Omnisonic - 1000 Hz
0

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320
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310
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-25
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75 285
-30
80 280
-35
85 275
90 270
-40
95 265
100 260
105 255
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250
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190185
175

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40
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-15
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-25
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75 285
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105 255
250
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5 10
15 20

180

5 10
15 20

180

40
45
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75
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85
90
95
100
105
110
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120
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130
135
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165160
175170

Fig. 43 – directivity patterns at 1 kHz

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 D100). Finally, the third one employs waveguides for
reconstructing a more uniform spherical wavefront
(Omnisonics 1000).

Horizontal Polar Plot - LookLine D300 - 2000 Hz
0
3503550
340345
335
330
-5
325
320
-10
315
310
-15
305
300
-20
295
-25
290

5 10
15 20

Horizontal Polar Plot - LookLine D200 - 2000 Hz

0
5 10
15 20

40
45
50
55
300
-20
60
295
-25
65
290
70
285
-30
75 280
-35
80 275
85
-40
270
90
265
95
260
100 255
105 250
110
245
115
240
120
235
125
230
130
225
135
220
215
140
210
145
205
150
200195
155
190185
160
165
175170
180

285
-30
280
-35
275
-40
270
265
260
255
250
245
240
235
230
225
220
215
210
205
200195
190185

Horizontal Polar Plot - Omnisonic - 2000 Hz

0
3503550
340345
335
330
-5
325
320
-10
315
310
-15
305

5 10
15 20

180

40
45
50
55
60
65
70
75
80
85
90
95
100
105
110
115
120
125
130
135
140
145
150
155
165160
175170

Fig. 44 – directivity patterns at 2 kHz
Horizontal Polar Plot - LookLine D300 - 4000 Hz

Horizontal Polar Plot - LookLine D200 - 4000 Hz
0

0
5 10
15 20

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340345
335
330
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320
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190185

The following figure shows the three dodechaedrons
analyzed:

180

3503550
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330
-5
325
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40
-10
315
45
310
50
-15
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55
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-25
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75 285
-30
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-35
85 275
-40
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95 265
100 260
105 255
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250
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130
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225
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200195
165
190185
175170

5 10
15 20

Horizontal Polar Plot - Omnisonic - 4000 Hz
0

3503550
340345
335
330
-5
325
40
320
-10
45
315
50
310
-15
55
305
60
300
-20
65
295
-25
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70
75 285
-30
80 280
-35
85 275
90 270
-40
95 265
100 260
105 255
110
250
245
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125
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200195
160
190185
175170165

5 10
15 20

180

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55
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95
100
105
110
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120
125
130
135
140
145
150
155
165160
175170

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.

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 18 of 21

Farina

4.2.

Impulse Response measurements

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 variabledirectivity-pattern mike, providing both omnidirectional
and figure-of-8 patterns.
For this purpose, it is common to employ notmeasurement-grade probes, often manufactured by topquality 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

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:

• 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. 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:

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 19 of 21

Farina

Impulse Response measurements

It can be seen that, even at medium frequencies, the
figure-of-8 pattern is distorted, and is not properly gainmatched with the omnidirectional one. These deviations
are even greater at very low and very high frequencies,
as shown here:

Comparison LF - measure 2 - 25m distance
1

Schoeps
0.9

Neumann

0.8

Soundfield
B&K

0.7

0.6
0.5

125 Hz

0.4
345350
340
335
330
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320
315
310
305
300

0.3
0.2
0.1

295
290

31.5

125

250

500

1000

2000

4000

8000

285

16000

10 15

0.12

35
40
45

0.1

50
55
60

0.08

0.06

70
75
80

0.02

275

270

Fig. 48 – LF measured at 25m

0.14

0.04

280

Frequency (Hz)

355

265

260

100

255

105

250

110

245
240
235
230
225
220
215
210
205
200
195190

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.

115

185

345350
340
335
330
325
320
315
310
305
300

355
1.6

295

10 15

35
40

1.2

45
50
55
60

1
0.8

295
290
285

65
0.6

70
75

0.4

280

80
0.2

275

500 Hz

85
90

265

260

100

255
10 15

110

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25

240
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200
195190

35
40
45
50
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285

Pressure
Velocity

105

250
5

0.1

290

175

1.4

270

180

120
125
130
135
140
145
150
155
160
170165

8000 Hz

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:

355
345350 0.25
340
335
330
325
0.2
320
315
310
0.15
305
300

Pressure
Velocity

115

185

180

175

120
125
130
135
140
145
150
155
160
170165

75
0.05

280

275

270

265

260

100

255

Pressure
Velocity

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

105

250
240
235
230
225
220
215
210
205
200195

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.

110

245

115

190185

180

175170

120
125
130
135
140
145
150
155
165160

2000 Hz
345350
340
335
330
325
320
315
310
305
300
295
290
285

355
1.8

10 15

1.6

4.3.
30

45
1.2

50
55
60

1
0.8

65
70

0.6

0.4

280
275

0.2

270

80
85
90

265

260

100

255

Pressure
Velocity

105

250

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.

110

245
240
235
230
225
220
215
210
205
200195

Binaural microphones

35
40

1.4

115

190185

180

175170

120
125
130
135
140
145
150
155
165160

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

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:

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 20 of 21

Farina

Impulse Response measurements

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.

Fig. 51 – anechoic measurements on dummy heads

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

Also in this case 4 different binaural microphones have
been tested:
• Bruel & Kjaer type 4100

[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

• 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
1

[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 2124, 2001.

0.9
0.8
0.7

IACCe

0.6
B&K4100
Cortex
Head
Neumann

0.5

[8] A. Farina, R. Ayalon – “Recording concert hall
acoustics for posterity” - 24th AES Conference on
Multichannel Audio, Banff, Canada, 26-28 June
2003

0.4
0.3
0.2
0.1
0
31.5

125

250

500

1000

2000

4000

8000

16000

[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.

Frequency (Hz)

Fig. 52 – IACC measured with the 4 dummy heads

AES 122nd Convention, Vienna, Austria, 2007 May 5–8
Page 21 of 21

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