Department of Electrical & Computer Engineering Auditory Perception Meena Ramani 04/09/2004

Department of Electrical & Computer Engineering

Auditory Perception

Meena Ramani

04/09/2004


NoteFor this lecture many of the slides will be

accompanied by scanned pictures shown on the OHP from Zwicker and Fastl’s

“Psycho-acoustics facts and models” 2nd edition


Main Outline

• Anatomy of the Ear and Hearing DONE

• Auditory perception• Hearing aids and Cochlear implants.

Extra: Direction of Arrival Estimation


Auditory perception

• Shepard Tones

• Masking <Detailed look>

• Ohms Acoustic Law

• Critical Bands

• Webers law

• Just Noticeable Frequency


Roger Penrose M.C. Escher

Ascending and Descending

Optical Illusion

Audio

Illusion


Shepard Tones• Circularity in Judgments of Relative Pitch, Roger N. Shepard,

JASA 1964.– Sensitivity to descending pitch – Sensitivity to volume changes between these

pitches.• A set of eight tones all an octave apart • The tones simultaneously descend in pitch till half of

their original pitch.• Jump back up to their original pitch and repeat the cycle.• Perceive this change?• Unique volume curve• Effect: Seamless transition in the cycle.• It’s all in your head!

• Omit two of the eight tones in the mid frequency range.


You know I can't hear you when the water is running!

MASKING


Masking

• Low-frequency, broad banded sounds (like water running) will mask higher frequency sounds which are softer at the listener's ear (a conversational tone from across the room).– Example 2: Truck in street

• Masking occurs because two frequencies lie within a critical band and the higher amplitude one masks the lower amplitude signal.

• Masking can be because of broad band, narrowband noise, pure and complex tones.

• Masking threshold– Amount of dB for test tone to be just audible in presence of noise

See OHP Figure


Masking by Broad band noise

• White noise- frequency independent PSD• Masked thresholds are a function of frequency.• Low and very high frequency almost same as TOQ.• Above 500Hz, thresholds increase with increase in frequency• Increasing white noise by 10dB increases masked threshold up by

10dB for frequencies >500Hz.• =>Linear behavior of masking• NOTE: TOQ’s frequency dependence almost completely

disappears Ear’s frequency selectivity and critical bands.

See OHP Figure


Masking by Narrow band noise

• Narrow band <=Critical BW• Noise (constant Amplitude, Different Frequency)

– 0.25,1,4KHz – BW: 100, 160, 700Hz– 60dB

• Frequency dependence of threshold masked by 250Hz seems to be broader

• Maximum value of masked threshold is lower for higher frequencies.• Steep increase but flatter decrease

See OHP Figure


Masking by Narrow band noise (cont)

• Noise (Varying Amplitude, Fixed Frequency)– 1KHz noise– 20-100dB

• Slope of rise seems independent of Amplitude• But slope of fall is dependent on amplitude• Non-Linear frequency dependence• Strange effect at high masker amplitudes:

– At high amplitudes ear begins to listen to anything audible!!– Begin to hear difference noise (noise and testing tone)

See OHP Figure


Masking by Pure and Complex tones• Pure tones:

– Below threshold of Quiet of test tone can hear only masking tone– Above it <700hZ can hear both– From 900-10kHz can hear only masking tone though above threshold of

hearing for test tone.– Between 1-2kHz difference tones are also audible– Low level masker wider at low frequencies– High level maskers wider at high frequencies

• Complex tones:– Log scale distance between the partials has a larger difference at LF,

less difference at HF– Dips correspondingly become smaller as frequency increases– 2 octaves above highest spectral content curve approaches TOQ

See OHP Figure


Temporal Aspects of Masking

• Previously assume long lasting test and masking sounds• Speech has a strong temporal structure• Vowels --loudest parts• Consonants faint• Often plosive consonants are masked by preceding loud vowel


Temporal Aspects of Masking (cont)

• Simultaneous Masking• Pre-Stimulus/Backward/Premasking

– 1st test tone 2nd Masker

• Poststimulus/Forward/Postmasking– 1st Masker 2nd test tone


Types of MaskingSimultaneous masking

– Duration less than 200ms test tone threshold increases with decrease in duration.

– Duration >200ms constant test tone threshold– Assume hearing system integrates over a period of 200ms

Postmasking (100ms)– Decay in effect of masker 100ms– More dominant

Premasking (20ms)– Takes place before masker is on!!– Each sensation is not instantaneous , requires build-up time

• Quick build up for loud maskers• Slower build up for softer maskers

– Less dominant effect

See OHP Figure


Ohm’s Acoustic LawThe sound quality of a complex tone depends ONLY on the

amplitudes and NOT relative phases of its harmonics.


Critical Bands• Proposed by Fletcher• Noise which masks a test tone is the part of its spectrum which lies

near the tone

• Masking is achieved when the power of the tone and the power of the noise spectrum lying near the tone and masking it are the same.

• Bands defined this way have a BW which produces same acoustic power in the tone and in the noise in the band when the tone is masked. CRITICAL BANDS

See OHP Figure


Critical Band (cont.)

• How to measure?– Masking of a band pass noise using 2 tones

• CB corresponds with1.5mm spacing on BM.• 24 such band pass filters• BW of the filters increases with increasing center frequency• Logarithmic relationship Weber’s law example.• Bark scale

See OHP Figure


Webers law

• Weber's Law states that the ratio of the increment threshold to the background intensity is a constant.

• So when you are in a noisy environment you must shout to be heard while a whisper works in a quiet room.

• when you measure increment thresholds on various intensity backgrounds, the thresholds increase in proportion to the background.


Just noticeable change in Frequency• (Pg:183)

• Similar to variation in the critical band structure• This is because it depends on number of BPFs• More BPF better resolution• Till about 500Hz JND is about 3.6Hz.• After 500Hz it varies as 0.007f

See OHP Figure


HEARING AIDS


Outline

• Facts on hearing loss

• Cell phones and hearing loss

• Types of Hearing aid

• Inside a hearing aid

• Audiogram


Facts on Hearing Loss in Adults

• One in every ten (28 million) Americans has hearing loss.

• The vast majority of Americans (95% or 26 million) with hearing loss can have their hearing loss treated with hearing aids.

• Only 5% of hearing loss in adults can be improved through medical or surgical treatment

• Millions of Americans with hearing loss could benefit from hearing aids but avoid them because of the stigma.


Cell phones and Hearing aids

• Cell Phones emit a type of electromagnetic energy that interferes with the operation of hearing aids.

• The Federal Communications Commission in mid-July 2003 ordered the cell phone industry to help out the hard-of-hearing.

“Within two years, cell-phone manufacturers must offer at least two phones with reduced interference for each type of cellular technology used, or ensure that one-fourth of phones the carriers sell produce less interference.”

• The FCC’s final milestone is February 2008.


Types of Hearing aids

Behind The earIn the Ear

In the Canal Completely in the canal


Anatomy of a Hearing Aid

• Microphone• Tone hook• Volume control• On/off switch

• Battery compartment


Inside a Hearing aid

1: The microphone The microphone picks up sound waves from the air and transforms them into electrical signals.

2: The microphone suspension The microphone suspension holds the microphone in place.

3: The loudspeaker The loudspeaker sends the amplified sounds into your ear. The loudspeaker is also called the receiver and sometimes the telephone.

4: The battery drawer The battery drawer holds the battery in place.

5: The amplifier The amplifier makes the signals that come from the microphone louder.

6: The telecoil The telecoil makes it possible for you to hear one specific person if you are in a place that supports the use of a telecoil. Many classrooms, churches and cinemas have telecoil. The telecoil makes it possible for you to hear i.e. your teacher without hearing the noise around you. It is also possible to use the telecoil at home - with the TV or the radio.


Audiograms


Direction of Arrival (DOA) estimation algorithm

<Useful for class project ideas>


Talk outline

• Necessity for DOA• DOA algorithm Requirements• Types of DOA algorithms

– Delay and sum– Minimum variance– MUSIC– Coherent MUSIC– Root MUSIC– ESPRIT

• Comparison Measures• Computational Intensity comparison• Accuracy Comparison• Accuracy vs Computational intensity• Conclusion


Where does the DOA come into the picture?

Has 2 microphones

DOA Estimation sn

Beamformer

Lets meet at 11?!?

7 is good for me too!!

11 sounds good!!


Direction of Arrival Estimation Algorithms

The DOA algorithm must satisfy the following conditions :

– Low computational intensity (MIPS/MFLOPS)

– High accuracy (RMSE)

– High speed – Easy implementation– Good performance at low SNRs– Works on a 2 microphone array system with 4cm

separation between them.


DOA Algorithms

Spatial Correlation methods

Subspace decompositionmethods

MUSIC Multiple Signal Estimation

ESPRITEstimation of Signal parameters

using rotational invariance

Delay and Sum Minimum Variance

Coherent MUSIC

Root MUSIC


DOA Method Equation for Implementation

Delay and Sum

Minimum Variance

MUSIC

Coherent MUSIC

Root MUSIC

ESPRIT

*( ) ( ) ( )P a Sa

*

1( )

( ) ( ) ( )P

a inv s a

*

* *

( ) ( )( )

( ) ( )N N

a aP

a E E a

'( )

' 'N N

a aP

a E E a

1

0sin . ( ) /( )K c angle z d

1

0sin arg( ) /( )

K Kc d


Comparison Measures

• To evaluate the computational intensity– MFLOPS comparison plot

• To evaluate the accuracy– Root Mean Square Error comparison plot

• To evaluate the effect at low SNRs– SNR vs Estimated angle plot

• To evaluate overall performance– Accuracy vs computational intensity


Evaluation of computational Intensity:MFLOPS comparison chart Min Variance

0.93 Mflops

Coherent MUSIC

0.3958 Mflops

DS

0.3573 Mflops

MUSIC

0.0813 Mflops

ESPRIT

0.0086 Mflops

Root MUSIC

0.0068 Mflops


Comparison of accuracy at different SNR values

0 5 10 15 20 250

20

40

60

80

100

120

140

160

180

Frame Number

Est

imat

ed D

OA

(de

gree

s)

Comparison of Estimated DOAs: SNR=10dB,Speech= 90' ,Noise=0'

ESPRITRMUSICCMUSICMUSICMVDS

0 5 10 150

20

40

60

80

100

120

140

160

180Estimated DOAS for only those regions which are speech

Frames Number

Est

imat

ed D

OA

(D

egre

es)


Comparison of Accuracy-MFLOPS


Conclusion

• Tradeoff between Accuracy and Computational intensity leads to the conclusion that ESPRIT is the Direction of arrival estimation algorithm best suited for our purpose

• MFLOPS value: 0.0086 • RMSE value:~3 (at 10dB)


0 5 10 15 20 250

20

40

60

80

100

120

140

160

180

Frame Number

Est

imat

ed D

OA

(de

gree

s)

Comparison of Estimated DOAs: SNR=10dB,Speech= 90' ,Noise=0'

ESPRITRMUSICCMUSICMUSICMVDS


0 5 10 150

20

40

60

80

100

120

140

160

180Estimated DOAS for only those regions which are speech

Frames Number

Estim

ate

d D

OA

(D

egre

es)


Documents

Department of Electrical & Computer Engineering Auditory Perception Meena Ramani 04/09/2004