Psychoacoustics - Startseite TU Ilmenau · 2013-01-16 · Fig: Zwicker, Fastl “Psychoacoustics - Facts and Models”, 2nd Edition, 1999. •narrow-band noise: •noise with a bandwidth

Prof. Dr.-Ing. K. Brandenburg, [email protected] Prof. Dr.-Ing. G. Schuller, [email protected] Page ‹Nr.›

Psychoacoustics

lecturer:

[email protected]


Block Diagram of a Perceptual Audio Encoder

Source: Brandenburg, “Vorlesung: Dig. Audiosignalverarbeitung”

• loudness

• critical bands

• masking:

• frequency domain

• time domain

• binaural cues (overview)


Structure of the Human Ear


Structure of the Human Ear

Quelle: Ars Auditus; http://www.dasp.uni-wuppertal.de/index.php?id=57, 2010

outer ear middle

ear inner ear

ear canal

pin

na

cochlea with

organ of Corti

archways ossicles

eustachische tube ear drum


Structure of the Human Ear - Cochlea

Quelle: Ars Auditus; http://www.dasp.uni-wuppertal.de/index.php?id=57, 2010

left picture :

- cochlea of a 5 month old fetus,

- 2 ½ coils, 35 mm long,

- dimensions are relative constant,

Quelle: Cochlee, http://www.cochlee.org, 2010

- blue arrow oval window

- yellow arrow round window

0,5 mm


Structure of the Human Ear – Organ of Corti

- organ of corti of a guinea pig

- white bar = 20 µm

outer hair cells

(OHC)

inner hair cells

(IHC)

Quelle: Cochlee, http://www.cochlee.org, 2010

Quelle: David C. Mountain, Boston University, 146th ASA Meeting

- ~ 3500 IHC and ~12000 OHC at humans

pumping OHC


Preprocessing of Sound in the Peripheral System

Source: Zwicker & Fastl “Psychoacoustics Facts and Models”

- frequency selectivity of the basilar membrane




- frequency selectivity of the basilar membrane (simulation)

21 kHz

frequency channels (Bark scale)

ba

sila

r m

em

bra

ne

am

plit

ud

e

14 Hz




- frequency selectivity of the basilar membrane (simulation)

frequency channels (Bark scale)

am

pli

tud

e i

n m


Information Processing in the Auditory System


- basilar membrane as a filter bank


Information Processing in the Auditory System

amplitude-time representation

basilar membrane oscillation

neurotransmitter concentration


Sound Perception


Frequency and Level Range of Human Hearing



Threshold in Quiet or the Absolute Threshold



Loudness

• Loudness Level:

• Loudness N: psychological concept to describe the magnitude of an

auditory sensation, the loudness of a sound (measured in ‘sone’)

• loudness level L of a sound is measured in ‘phon’

• L of a sound is the sound pressure of a 1 kHz tone which is as loud as

the sound

Fig: Fletcher, “Speech and Hearing in Communication”, 1953.


Loudness

• Equal-Loudness Level Contours:

Links to measure the sensitivity on different frequencies:

http://www.phys.unsw.edu.au/jw/hearing.html

http://www.phys.unsw.edu.au/music/dB/loudness.html, 2010

Fig: Suzuki et al., “Precise and Full-range Determination of Two-dimensional Equal Loudness Contours”, 2003.

0.15

1

4

16

N=64 sone

Equal loudness contours of

pure tones in a free sound field.

The parameter is expressed in

loudness level, LN, and loudness, N.


Loudness

• Loudness Scale:

• aim: double the number of units on this scale means magnitude of

sensation is doubled

• relation G(L) between loudness level L and the loudness N on the

new scale

• one potential experiment:

• listen to sound with L1 and than adjust same sound until L2=2xL1


Loudness

• Loudness Scale:

• Example 1:

• L=40 phonN=1 sone

• 2 x loudness: N=2 sone

L=40+10 = 50 phon

• Example 2:

• L=40 phonN=1 sone

• ½ of loudness: N=0.5

L=40-7.8 = 32.2 phon



Loudness

• Loudness Scale:

• Example 2:

• L = 40 phonN=1 sone

• ½ of loudness: N=0.5

L=40-7.8=32.2 phon

• for values of L above 40

phon:

N=2^((L-40)/10)



Loudness

Loudness contours for loudspeaker and binaural headphone presentation.

headphone loudspeaker

Fig: Master Thesis, F. Jürgens, TU Ilmenau, 2012.


Loudness

• Loudness Scale:

Fig: en.wikipedia.org/wiki/Sone, 2010.


Sound Example

• Example 1: Equal amplitude

– tones of frequencies 40Hz, 100Hz, 4000Hz, and 12000Hz

• Example 2: Equal amplitude

– Sweep from 0-16000 Hz


Critical Bands


Frequency Grouping in Human Hearing

Source: Brandenburg, “Vorlesung: Dig. Audiosignalverarbeitung

• Different interpretations that produce the same

segmentation

– Constant distance in the Cochlea

– By using tones under the threshold in quiet,

their intensity add up in a critical band and are

now audible

– Tones in a critical band above the threshold in

quiet: their energy adds up

• Formula for the width of the critical bands

– for frequencies < 500 Hz: Constant 100Hz

width

– for frequencies > 500 Hz: 0.2*frequency


Frequency Grouping Bandwidth The Critical Bands


Critical bandwidth as a function of

frequency.

Approximations for low

and high frequency ranges are

indicated by broken lines.


Excursus - Critical Bands and Loudness

• Spectral effects - influence of frequency separation:

• measure the loudness level (or level of the equally loud 1 kHz tone) of 2 tones by

varying the frequency separation

Fig: Zwicker, Fastl “Psychoacoustics - Facts and Models”, 2nd Edition, 1999.


Excursus - Critical Bands and Loudness

• Spectral effects - influence of bandwidth:

• bandwidth of the signals plays an important role

• sound level also influence loudness level

• total sound intensity (SPL) have to be constant to measure loudness

as function of bandwidth

• critical bandwidth



Critical Bands: Bark Scale

• Critical-band concept used in many models and hypothesis

unit was defined leading to so-called critical-band rate scale

• scale ranging from 0 – 24, unit “Bark”

• relation between z and f is important for under-standing many character-istics of human ear


Critical Band Rate and Threshold in Quiet

Source: U. Zölzer, “Digitale Audiosignalverarbeitung”


Signal Power in Critical Bands



Masking


Masking

• data compression

– exploitation of perception in critical bands with

reference to the threshold in quiet is not

enough

• Basis for further compression are masking effects as

described by Zwicker, Fletcher, Fastl, Feldtkeller and others.


Masking of Pure Tones by Noise - Broad-Band Noise


•broad-band noise:

•white noise from 20 Hz

- 20 kHz

•figure:

•masking threshold for

pure tones masked by

broad band noise of

different levels

•uniform masking noise

(UMN) by equalization

of the 10 dB per decade

slope


Masking of Pure Tones by Noise - Narrow-Band Noise


•narrow-band noise:

•noise with a bandwidth equal

or smaller than critical

bandwidth

•figure:

•threshold of pure tones

masked by narrow-band noise

for different centre frequencies

•difference between maximum

of masked threshold and test

tone level


Masking of Pure Tones by Noise - Narrow-Band Noise


•narrow-band noise:

•noise with a bandwidth equal

or smaller than critical

bandwidth

•figure:

•dependence of masked

threshold on level of narrow-

band noise

•dips at higher levels

nonlinear effects (difference noise

caused by interactions between test

tone and noise)


Test: Narrow Band Noise Masking Tone • Example 3:

Narrow Band Noise at 1000 Hz, width 160 Hz; Sine tones at 600, 800, 1000, 1200, 1400, 1600 Hz at varying levels (-80 to -20 dB)


Sound Examples: Masking with White Noise

• Example 4: Masking with white noise

– 500 Hz sinusoid tone at varying amplitude ALONE

– Level: -40,-35,-30,-25,-20,-15,-10 dB


– 500 Hz tone at varying amplitude with White

Noise

– Level: -40,-35,-30,-25,-20,-15,-10 dB

– Noise Level: -50 db


– 5000 Hz tone at varying amplitude with White

Noise

– Levels: same as Example 5


Masking of Pure Tones by Low-Pass or High-Pass Noise



Masking of Pure Tones by Pure Tone


•pure tone:

•single frequency

•figure:

•1 kHz masking tone with

level of 80 dB

•threshold for ‘detection

of anything’

difficulties:

•beats (hatching)

•masker and difference

tone (stippling)


Masking of Pure Tone by Complex Tones


•complex tone:

•fundamental tone with its

harmonics

•figure:

•threshold of pure tones

masked by a complex tone

with 200 Hz fundamental

frequency and nine harmonics


Tonality (1)

• Tonality index :

– noisy signal: = 0

– tonal signal: = 1

• System theory

– Sharp spectral lines = Signal is periodic = Signal is predictable

– Approximation: If the signal is predictable then it should be periodic

– Therefore we can use prediction to approximate if a signal is tonal (by periodicity)


Tonality (2)

Source: Brandenburg, “Vorlesung: Dig. Audiosignalverarbeitung


Tone Masking



Calculating the Masking Threshold

• Different Masking with different maskers:

– Tone masking: (14.5 + i) dB, where i is the frequency in bark

– Noise as a masker: 5.5 dB


Calculating the Masking Threshold

SFM = 0 dB = 0

SFM = -60 dB = 1


In-Band Masking



Masking Neighboring Bands



• Example 7: Dynamic range

– Bach organ music with 16 bits per sample





Sound Examples


Temporal Masking Effects (1)



Temporal Masking Effects (2)

• Post-Masking: corresponds to decay in the effect of

the masker expected

• Pre-Masking: appears during time before masker is

switched on

– Quick build-up time for loud maskers

– Slower build-up time for faint test sounds

• Frequency resolution Blurring in time

• Frequency resolution in the ear Masking in time

• Because of in-ear fast processing between quiet to

loud signals, we get Pre-Echoes

– Pre-Masking: 1-5 ms

– Post-Masking: ~100ms


Pre-Echo: Example without Pre-Echo


Pre-Echo: Example


Sound Examples

• Example 10:

- Castanets original

• Example 11:

- Castanets coded with a block size of

2048 samples


next lecture:

?? Quantization and Coding ??

Documents

Psychoacoustics - Startseite TU Ilmenau · 2013-01-16 · Fig: Zwicker, Fastl “Psychoacoustics - Facts and Models”, 2nd Edition, 1999. •narrow-band noise: •noise with a bandwidth