Soundscape and Psychoacoustics Using the resources for ...dependent sensitivity of human hearing;...

1

Internoise 2016, Hamburg & Berlin - Standards in PsychoacousticsRoland Sottek 1

Roland Sottek

HEAD acoustics GmbH

[email protected]

Soundscape and Psychoacoustics –

Using the resources for environmental noise

protection

Standards in Psychoacoustics

Satellite symposium on August 25 and 26, 2016


Introduction

The evaluation and design of noise is becoming increasingly

important.

Different kind of sources contribute to the noise:

Broadband and narrowband noises, tonal components, modulated

sounds.

The perception is often predicted by psychoacoustic parameters in

order to reduce time-consuming listening tests.

2


Why do we need psychoacoustics?

Almost identical levels and

3rd octave spectra

of an electrical motor and a Mozart concert

Time data and 3rd octave spectrum


Different time structures

Almost identical

3rd octave spectra and

thus identical sound

pressure levels and

stationary loudness

values (calculation from

3rd octave spectra)

Clearly audible

difference also with

respect to loudness

because of different

time structures

40

50

60

80

L/d

B[S

PL

]

f/Hz20 100 2000 20k

Noise

40

50

60

80

L/d

B[S

PL

]

f/Hz20 100 2000 20k

Impulse

40

50

60

80

L/d

B[S

PL

]

f/Hz20 100 2000 20k

Diesel

3rd octave spectra

3


Same sound pressure levels – different loudness values


sound frequency /

Hz

modulation-

rate / Hz

fluctuation roughness

1000 0

1000 1

1000 4

1000 20

1000 70

1000 & 2000 0

Modulated signals, tone complexes

4


Perception and physical measurement

„Optical illusion“


“Acoustical illusion” („signal-estimation“)

fre

qu

en

cy

timetime

pulsation thresholds

5


Acoustics vs. psychoacoustics (1)

In acoustics the sound source is in the center of focus:

What signals? What are the amplitudes? What vibrations /

frequencies? What energy?

Psychoacoustics provides the recipient (the people) in the center

of focus :

What loudness, sharpness, roughness, tonality, annoyance are

perceived?

What are the expectations, attitudes, experiences of those affected?


Acoustics vs. psychoacoustics (2)

In acoustics, the entire sound event is often reduced to a simple

variable in the form of A-weighted sound pressure level dB (A).

A-weighting considers in a highly simplified manner, the frequency-

dependent sensitivity of human hearing; low-frequency tones are

perceived softer as high-frequency tones at the same sound

pressure level.

Psychoacoustics describes the auditory sensation of a human

being as a complex function of the signal composition, the

temporal patterns, the interaction of different frequencies.

Here cognitive and contextual aspects are very important: attitude

to noise, the information content and the cause of the noise.

6


What is psychoacoustics?

Psychoacoustics deals with the sound perception of human

hearing (sound recording, analysis in the inner ear, processing

and analysis in the brain) and is engaged in addition also with the

acoustically correct recording (e.g., with an artificial head

measuring system) and the hearing-related analysis of sound

events.

Taking into account the cognitive aspects of noise

psychoacoustics enables one to describe the transformation of a

sound event in an auditory event.

7


Introduction to loudness

Internoise 2016, Hamburg & Berlin - Standards in PsychoacousticsRoland Sottek 15Was ist Lautheit?André Fiebig 15

Definition of loudness

„Loudness is a psychological term used to describe the

magnitude of an auditory sensation.“ * (Fletcher, Munson, 1933)

„Die Empfindungsgröße der zur Schallstärke gehörenden

Intensitätsempfindung ist die Lautheit.“** (Zwicker, 1982)

(The auditory sensation corresponding to the perceived sound

intensity is loudness.)

* FLETCHER, H. MUNSON, W.A.

Loudness, its definition, measurement, and calculation. J. Acoust. Soc. Amer. 5, p. 82 (1933)

** ZWICKER, E.

Psychoakustik. Hochschultext, Heidelberg, New York, Berlin, Springer Verlag, p. 79. (1982)

8


Sound Sound

Influence of masking on loudness

N5=10,6 sone GF N5=13,5 sone GF


Influence of duration on loudness (temporal integration)

Nmax=8,5 sone

Nmax=14,0 sone

Nmax=16,4 sone

Tone pulse

Tone pulse

Tone pulse

9


Factors influencing loudness

Frequency Tones with the same sound pressure level but different frequency are not

perceived as equal loud.

Spectral composition Sounds with different spectral composition but the same sound pressure

level are not perceived equally loud, e.g. broadband sounds are perceived louder than narrowband sounds at the same level.

Sound pressure level Changes in sound pressure level do not lead to the same degree to

loudness changes.

Simultaneous masking At the same level, loudness varies by different masking effects in the

spectral domain.

Backward and forward masking The temporal structure is influencing the perceived loudness (test tone is

presented before or after the masker).

Signal duration Loudness sensation increases with signal duration up to a duration of 1 s.


Critical band concept

Critical bandwidth can be considered as the bandwidth of auditory

filters.

Critical bandwidth is constant below 500 Hz and is about 20 % of

the center frequency at higher frequencies.

Third octave filters have a similar bandwidth, thus they can "be

considered as a useful approach to auditory filters“ *

The concept of critical bands is for many auditory sensations of

particular importance.

dB(A) does not consider critical bands and masking!

*FASTL, H.

Psychoakustische Methoden, in: Kalivoda, M.T. und Steiner (Hrsg.). Taschenbuch der Angewandten Psychoakustik, Wien,

New York, Springer (1998)

10


Loudness standards


Standardization of psychoacoustic parameters (1)

Loudness evaluation has become a central focus for assuring better

consideration of sound intensity phenomena than frequency-weighted

levels like dB(A).

Different loudness standards available for stationary sounds:

ISO 532:1975 section 1 (method A) [Stevens method]

ISO 532:1975 section 2 (method B) [Zwicker method]

ANSI S3.4:2007 [Moore/Glasberg method]

DIN 45631:1991 [Zwicker method]

Loudness standard available for time-varying sounds:

DIN 45631/A1:2010 [Zwicker method]

WG 9 of ISO TC43 (Acoustics) has worked on (available end of 2016)

• ISO 532-1 “Methods for calculating loudness – Part 1: Zwicker method”

for stationary and time-varying sound based on DIN and

• ISO 532-2 “Methods for calculating loudness – Part 2: Moore/Glasberg

method” for stationary sounds based on ANSI S3.4:2007.

11


History of loudness standardization (Zwicker method)

DIN 45631: 1967 stationary loudness

ISO 532B : 1975 stationary loudness

DIN 45631: 1991 stationary loudness widely used!

corrections to match the ISO equal

loudness contours (ISO 226:1987)

DIN 45631/A1: 2010 time-varying loudness widely used!

ISO 532-1: 2016 stationary and time-varying loudness

based on DIN 45631, but with test

implementation (source code in appendix),

detailed description from time signal to

(specific) loudness vs. time function;

nearly identical results can be obtained

by ISO 532-1 and DIN 45631 or DIN 45631/A1


History of loudness standardization (Moore/Glasberg method)

ANSI S3.4: 2007 stationary loudness

ISO 532-2: 2016 stationary loudness, based on ANSI S3.4

The ISO 532-2 method does not fully

describe obtaining a result from time-signals,

only from described levels versus frequencies.

User interaction is required: description of

tones, noise bands, …!

Moore/Glasberg made the source code of their

loudness model available as part of ISO 532-2.

A time-varying loudness model is planned

for a later update.

12


Standardization of psychoacoustic parameters (2)

Sharpness standard (the weighted first moment of the critical-band

rate distribution of specific loudness, only stationary signals):

DIN 45692 (2009)

Tonality standards: ECMA-74 (IT products), DIN 45681

Standardization of roughness is currently being pursued in a DIN

working group.

Following:

Overview of loudness calculation procedures

Sharpness calculation procedure

Tonality calculation procedure

Roughness model discussed as one option in the DIN working group

Blind source separation

13


Loudness calculation procedures


Loudness calculation procedures

p(t)FF

DF

LP N´ NL

LP

g1

+ N(t)

LP N´ NLg2

LP N´ NLgk

LP N´ NLgK

band pass

filter bank

Bark(Zwicker)

ERB(ANSI)

3rd Oct.(DIN)

?

p(t)FF

DF

LP N´ NL

LP

g1

+ N(t)

LP N´ NLg2

LP N´ NLgk

LP N´ NLgK

band pass

filter bank

Bark(Zwicker)

Bark(Zwicker)

ERB(ANSI)

ERB(ANSI)

3rd Oct.(DIN)

3rd Oct.(DIN)

??

temporal effects and post-masking

(DIN 45631/A1)

14


Comparison: ANSI - DIN

ANSI S3.4-2007 DIN 45631

Choice of sound field Free or diffuse

Band pass filter bank 40 filters, constant band-

width on ERB scale

28 third-octave filters,

approx. 24 Bark bands

Envelope formation Rectifying and low-pass filtering

Frequency weighting Strong attenuation Less attenuation

Nonlinearity Square root law between sound pressure and

loudness (highly simplified)

Opposite effects!


Equal-loudness contours (60 phon)

Equal-loudness contours (60 phon): IS0 226 new/old, DIN 45631, ANSI S3.4-2007 L/dB[SPL]

40

50

60

70

80

90

100

110

120

f/Hz20 50 100 200 1000 2000 5000 10k

ISO 226: 2003ISO 226: 1987DIN 45631ANSI S3.4-2007

Tones are judged much softer by ANSI S3.4-2007 than DIN 45631!

≈ 8 dB

GENUIT, K., SOTTEK, R. AND FIEBIG, A., Comparison of Loudness Calculation Procedures in the Context of Different

Practical Applications, Internoise 2009, Ottawa, Canada (2009).

15


Loudness of technical sounds

DIN 45631 and ANSI S3.4-2007 standards provide significantly

different loudness values in many cases!

6.8 sone

28.3 sone

25.7 sone

6.2 sone

23.8 sone

37.9 sone

29.8 sone

28.9 sone

4.7 soneGF

25.4 soneGF

24.1 soneGF

4.6 soneGF

18.7 soneGF

30.6 soneGF

23.2 soneGF

28.8 soneGF

electric motor

wind noise

vehicle noise at constant speed

power seat

park (New York)

electric screwdriver

electric saw

exhaust system

ANSI S3.4-2007DIN 45631sound source


Signal processing scheme: time-variant loudness (ISO 532-1)

z = z + step sizefalse

Inp

ut sig

na

l

LCB‘ 1

Core loudness

N‘C 1 (eq. A.1.1)

slope loudness > specific loudness

Specific loudness = core

loudness x

Specific loudness = slope

loudness

Total loudness

Mapping to 24 critical bands (Bark) using table A.6

Specific loudness = core loudness x

Summation of specific loudness

Start index z = 0.1 Bark. Step size = 0.1 Bark. Approximated

core loudness, filter number: x = 1

z < 24

Calculation of slope loudness using

table A.7

falsetrue

true

Step to next

CB: x(z)

true

false

Weighting

(table A.1)

LCB‘ 2

LCB‘ 3

LCB‘ 4

LCB‘ i

LCB‘ 20

Weighting

(table A.1)

Weighting

(table A.1)

Weighting

(table A.1)

Weighting

(table A.1)

Weighting

(table A.1)

Weighting

(table A.1)

Weighting

(table A.1)

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

Core loudness

N‘C 2 (eq. A.1.1)

Core loudness

N‘C 3 (eq. A.1.1)

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

Core loudness

N‘C 4 (eq. A.1.1)

Core loudness

N‘C i (eq. A.1.1)

Core loudness

N‘C 20 (eq. A.1.1)

NL

NL

NL

NL

NL

LP1

Applicaton to ISO 532-1 method B

LPi

LP6

LP7

LP8

LP9

LP10

LP11

LP12

LPi

LP28

NL

f

25 HzA

f

3rd octaveA

f

80 HzA

f

125 HZA

f

100 HzA

f

250 HzA

f

200 HzA

315 HzA

f

3rd octaveA

f

12500 HZA

f

160 HZA

f

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

Level corrections

a0 ,DLDF, DLCB

(tables A.2-A.5)

LT 1

LT i

LT 6

LT 7

LT 8

LT 9

LT 10

LT 11

LT 12

LT i

LT 28

t=70 msLP1 LP2

0.530.47

t=3.5 ms

16


ISO 532-1

Reducing uncertainties in loudness calculation of time-variant sounds

In addition to the loudness standard for stationary sounds:

Specification of the third-octave filter bank

Rectification and intensity averaging

Non-linear temporal decay of the hearing system

Temporal weighting of total loudness


Temporal weighting of total loudness

Two 1st order low-pass filters (time constants 3.5 ms and 70 ms)

applied to sum of specific loudness values

Simulates duration dependent behavior of loudness perception for

short impulses: signal with duration of 10 ms is perceived as about

half as loud as one with duration of 100 ms

Total loudness is weighted sum (factors 0.47 and 0.53) of filtered

signal

t=70 msLP1 LP2

0.530.47

t=3.5 ms

17


Representative value for time-variant loudness?

N5 percentile of loudness vs. time representation

Considers peaks -> better than mean value

Especially in the case of many events (cognitive effects)

Even better: root mean cubed average of loudness vs. time function


Representative value for time-variant loudness?

N5 not suited for impulses:

For this special case only: maximum value

18


Summary and conclusion (loudness calculation procedures)

Application of ANSI S3.4-2007 and DIN 45631 standards to technical

sounds provides significantly different loudness values

3 factors influence strongly the results of loudness models

Frequency weighting (differences in equal-loudness-level contours

according to ISO 226:1985, 2003; especially a low frequencies;

new listening tests for normal equal-loudness-level contours

needed!)

Frequency scale (Bark, ERB)

Nonlinearity between sound pressure and spec. loudness

Presentation of an updated ISO 532 standard

Complete description of each signal processing step starting from wave

form to specific or total loudness vs. time functions

Code example for implementation of all algorithms will be available

Reduction of uncertainties in loudness calculation

19


Sharpness calculation procedure


• Ratio of high frequency level to overall level (basic description).

• “Center of gravity,” on frequency scale of spectral envelope: the higher the “c.g.,” the sharper the sound.

• Integration of specific loudness multiplied by a weighting function, divided by total loudness (hence, sharpness is level-independent).

• Normalized to a reference sound, a narrow band of noise centered at 1 kHz at a level of 60 dB and a bandwidth of 160 Hz, which has an agreed value of 1 acum.

Sharpness

20


Calculation of sharpness (DIN 45692)

acum

d)('

dBark/)()('

Bark24

0

Bark24

0

z

z

z

z

zzN

zzzgzN

kS

Barkze

for

Barkz

zgBarkz 8,1585,015,0

8,151

)(8,15/42,0

Solid line:

weighting function according to

DIN 45692 (see above)

Dashed line:

weighting function according to

v. Bismarck

Weighting function according to

Aures depends on loudness N!


white noise, 8 kHz amplified

Sharpness vs. Time

Sharpness vs. Time

Comparison of sharpness methods: von Bismarck / Aures

white noise

21


Influence of time structure on sharpness

stream

stream „random“

22


Tonality calculation procedure


Introduction to tonality

Technical and natural sounds often contain prominent tonal

components that can

significantly influence the individual perception and evaluation of the

sound event,

increase annoyance.

Tonality of sounds is increasingly important, even at very low levels

regarding

sound quality and sound design applications.

Products may emit tonally-perceived noises due not only to pure

tones but also to narrow noise bands, and to same-vicinity

combinations of pure tones and narrow elevated noise bands.

Established methods for tonality calculation such as (specific)

prominence ratio and tone to noise ratio exhibit problems when

compared to listening test data.

23


Available tools for assessing audible tonality

Tone-to-Noise Ratio (TNR: ECMA-74; Information Technology main

use).

Prominence Ratio (PR: ECMA-74; Information Technology main use).

DIN 45681 tonality (German standard, 2006)

Psychoacoustic tonality (“Tonality”: Aures/Terhardt)


Perception of tonality

• Recent research results show a strong correlation between tonality

perception and the partial loudness of tonal sound components.

HANSEN, H., VERHEY, JL. AND WEBER, R.

The Magnitude of Tonal Content. A Review, Acta Acustica united with Acustica, Vol. 97, pp. 355-363 (2011).

HANSEN, H. AND WEBER, R.

Zum Verhältnis von Tonhaltigkeit und der partiellen Lautheit der tonalen Komponenten in Rauschen, Deutsche

Jahrestagung für Akustik, DAGA (2010).

VERHEY, JL. AND, STEFANOWICZ, S.

“Binaurale Tonhaltigkeit”, Deutsche Jahrestagung für Akustik, DAGA (2011).

KAMP, F.

Modellierung der Wahrnehmung tonaler Geräuschkomponenten (Modeling the perception of tonal sound components),

Master thesis (2012).

24


Pure tones (𝑓 = 1 𝑘𝐻𝑧) of different level in pink noise

80 75 70 65 60 55 50 45 400

2

4

6

8

10

12

Pegel des Rauschsignals [dB]

Kat

ego

rie

Pegel Sinuston = 70dB

mean value tonality

median value tonality

mean value loudness of tonal components

median value loudness of tonal components

35 40 45 55 65 750

2

4

6

8

10

12

tone level [dB]

cate

gory

sca

le

noise level = 60dB

45 50 55 65 750

2

4

6

8

10

12

tone level [dB]

noise level = 70dB

55 60 65 750

2

4

6

8

10

12

tone level [dB]

noise level = 80dB

The listening test has shown, that …… the perceived tonality and the loudness of the tonal content are

strongly correlated (for high noise levels).

SOTTEK, R., KAMP, F. AND FIEBIG, A.

A new hearing model approach to tonality, Internoise 2013, Innsbruck, (2013).


Hearing model (Sottek, dissertation, 1993)

SOTTEK, R.

Modelle zur Signalverarbeitung im menschlichen Gehör, Dissertation, RWTH Aachen (1993).

of a Door Slam Noise

Specific Roughness

Specific Loudness

Specific Fluctuation

a1

Channel 1

a i

Formation of Envelope

Ear-related Filterbank

a n

Channel n

0 0.1 0.2 0.3 0.4 s

Bark

0

5

10

15

20

Aurally-adequate Spectral Analysis

Outer and

Middle Ear

Filtering

Lowpass Nonlinearity

Auditory

SensationChannel i

Time Signal

25


Extended nonlinearity of the hearing model (Sottek)

BIERBAUMS, T. UND SOTTEK, R.

Modellierung der zeitvarianten Lautheit mit einem Gehörmodell, DAGA ‘12, Darmstadt (2012).

EPSTEIN, M. AND FLORENTINE, M.

A test of the Equal-Loudness-Ratio hypothesis using cross-modality matching functions, J. Acoust. Soc. Am., vol. 118(2),

pp. 907–913 (2005).

ZWICKER, E.

Über psychologische und methodische Grundlagen der Lautheit, Acustica, vol. 8, pp. 237-258 (1958).


Double (half) loudness of a 1-kHz tone

Level increment (solid line) and decrement (dashed line) DL of a 1 kHz tone, required for double

and half-loudness perception (Zwicker). Mean values of 12 subjects and interquartile ranges of

the measurements are shown. Starting both parts of the experiment with the lowest level!

26


Two-dimensional pitch sensation

Analysis of excitation pattern in (x, τ)-plane allows for modeling psycho-

acoustic phenomena (e. g. difference tones, residual components)

LICKLIDER, J.C.R.

A Duplex Theory of Pitch Perception (1951).


Hearing model (Sottek) (basis)

time signal 𝑠(𝑡)

outer and middle ear filtering

i1 n

auditory filter bank with i=1..n critical bands

one-way rectification

attenuation

autocorrelation function (ACF)

more compressive non-linearity

i1 n

consideration of threshold in quiet

Example: door slam noise

t

SOTTEK, R.

Modelle zur Signalverarbeitung im menschlichen Gehör, Dissertation, RWTH Aachen (1993).

27


Autocorrelation function of periodic signals

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2-5

-4

-3

-2

-1

0

1

2

3

4

5x 10

-4

t / ms

ES

ES

ES

ES

ES

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2-5

-4

-3

-2

-1

0

1

2

3

4

5x 10

-4

t / ms

ES

Pure tone, f = 1 kHz White noise, f = 20 Hz – 20 kHz

𝐸𝑠 = 𝜑𝑠𝑠𝐸 0𝐸𝑠 = 𝜑𝑠𝑠

𝐸 0 = 𝜑𝑠𝑠𝐸 𝑛 ∙ 𝑇


Delay time window

autocorrelation function of a tone in pink noise

0 20 40 60 80

-8

-4

0

4

8delay time window

t0

tStart

tEnd

delay time t / ms

Ende

detection of periodicities

separation of periodic

signals and noise

𝐸𝑠 = 𝜑𝑠𝑠𝐸 0

𝐸𝑡𝑜𝑛𝑎𝑙 = 𝑦 (𝜑𝑠𝑠𝐸 𝜏𝑠𝑡𝑎𝑟𝑡 𝑓 , 𝜏𝑒𝑛𝑑 𝑓

𝐸𝑠 ≥ 𝐸𝑡𝑜𝑛𝑎𝑙

28


Frequency-modulated tone at 2 kHz (fmod=2 Hz, mi=150, L=30 dB)

29


Roughness calculation procedure


Extension to the third dimension

New algorithm:

(two dimensional: time-frequency) auditory filter bank

is extended by modulation spectral analysis to a tensor

Tensor contains information about

time, frequency and time structure (modulation rate).

frequency

time

t

hearing model

spectrogram

3rd dimension:

time structure

frequency weighting

weighting vs. t

30

Internoise 2016, Hamburg - A hearing model approach to roughnessRoland Sottek 66

Model calibration according to Zwicker and Fastl

Internoise 2016, Hamburg - A hearing model approach to roughnessRoland Sottek 67

Roughness of tones (f=1 kHz, fmod=70 Hz, m=1)

31


Roughness of engine sounds

RI

Number of engine noise

Measurement

Simulation


Application of the hearing model roughness calculation

Klemenz (Dissertation ‘05)

Roughness compared to

dissonance

0

0,2

0,4

0,6

0,8

1

1 2 3 4 5 6 7 8

Number of engine noise

roughness

a

M1

M2

M3

M4

SGNB

Attia & Okker (DAGA ’95)

Comparison of different models for

the prediction of engine roughness

Comparison of calculated roughness with experimental results

32


Blind source separation


Investigations of methods for detecting acoustic patterns

Spectral or temporal structures (patterns) are significant for the

hearing impression.

Complex sound events are constructed from several of these

patterns.

In listening tests it can be observed that in the evaluation of

complex sound events often large variations occur, which point to

an individual focusing on one of these patterns.

For a better analysis and exploration of psychoacoustic

phenomena, therefore, an automatic detection and separation of

these patterns is sought by mathematical methods.

33


„Blind“ source separation using spectrograms

Spectrograms are level

representations as a function

of time and frequency.

Better frequency resolution

means worse time resolution,

and vice versa, i.e., depending

on the resolution temporal

structures are recognizable

and the representation in terms of frequencies can be smeared.

The two-dimensional representation is thus often inadequate for

the description and especially for the detection of patterns.

The quality of the results depends greatly on the signal and the

selected resolution.


Extension to the third dimension

New algorithm:

(two dimensional: time-frequency) auditory filter bank

is extended by modulation spectral analysis to a tensor

Tensor contains information about

time, frequency and time structure (modulation rate).

frequency

time

t

hearing model

spectrogram

3rd dimension:

time structure

frequency weighting

weighting vs. t

34


Separation of a mixture of modulated tones (example 1)

Good reconstruction of the modulated tones!

detected pattern 5

original detected pattern 1 detected pattern 2

detected pattern 3 detected pattern 4


Separation of a the patterns of a hard disc noise (example 2)

Different meaningful patterns can be detected.

detected pattern 5

original detected pattern 1 detected pattern 2

detected pattern 3 detected pattern 4

35


Conclusions and outlook

Summary of psychoacoustic parameters

Status of standardization

Hearing model approach of Sottek

Two-dimensional representations for the detection and separation

of the components are often not sufficient.

New method is based on three-dimensional modulation tensor.

Additional information about temporal structure

Based on a signal processing model of human perception

First results indicate that the method can extract patterns in technical

noise similar to the perceived patterns by humans.

Validation shall be performed in listening tests.

Outlook: possible application for soundscape projects


Dr.-Ing. Roland Sottek

Manager Research NVH

[email protected]

www.head-acoustics.de

© Copyright HEAD acoustics GmbH

Thank you for your attention.

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