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Computational Perception 15-485/785 Sound localization 2 January 22, 2008

Computational Perception

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Page 1: Computational Perception

Computational Perception15-485/785

Sound localization 2

January 22, 2008

Page 2: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Last lecture

• sound propagation: reflection, diffraction, shadowing

• sound intensity (dB)

• defining computational problems

• sound lateralization

• ITD and IIDs

• duplex theory

• localization acuity, minimum audible angle

• estimating ITD, cross correlation

2

Page 3: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Cross correlation of white noise

3

xR(t)

0 500 1000 1500 2000

xL(t)

−1000 −500 0 500 1000−1

−0.5

0

0.5

1Corr(xR(t), xL(t))

μsecμsec

Page 4: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Cross correlation of a high frequency tone

4

−1000 −500 0 500 1000

Corr(xR(t), xL(t))xR(t) freq=1500 Hz

0 500 1000 1500 2000

xL(t) freq=1500 Hz

μsecμsec

This is called phase ambiguity because there are multiple peaks within the natural range of ±690 µsecs.

Page 5: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Testing the duplex theory

5

• Pure tones are ineffective for lateralization > 1500 Hz.

- Does this mean all sounds are?

• Consider bandpass noise: 3000-3300 Hz

- How would you perceive this sound?

• Sound is correctly localized, but with greater error (60 µsecs vs 10).

Page 6: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

−1000 −500 0 500 1000

Corr(xR(t), xL(t))xR(t) freq=3150 Hz

0 500 1000 1500 2000

xL(t) freq=3150 Hz

Cross correlation of a high frequency tone

6

μsecμsec

Why might this sound not be correctly localized?

Page 7: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

What does the auditory system do?

7

from Yost, 2000

Page 8: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Frequency mapping of the basilar membrane

8

How do we lateralize narrowband sounds if the ear decomposes sound in terms of frequency?

from Warren, 1999

Page 9: Computational Perception

filtering and frequency space (on board)

Page 10: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Integrating across frequency: psychophysical models

10

Note: the sound is still lateralized correctly even though ITD is far outside it’s natural range.

Ensembles of coincidence-counting units (Stern and Trahiotis, 1995)

Narrow band sound lateralized to the right, broadband to left.

How is sound localized when the bandwidth is increased?

Page 11: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Things are not as simple as the might seem

• Delay a 3900 Hz tone modulated at 300 Hz.

• Can this ITD be detected?

• Could ITD of low frequencies explain this?

• No: Beat frequency is 300 Hz

⇒ spectrum is 3900 and 3900±300 Hz.

• Time delay of envelope predicts lateralization.

11

from Blauert, 1997

Page 12: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Limitations of the Duplex Theory

12

• limited to lateralization

• doesn’t do front-back discrimination

• doesn’t explain why are sounds are outside your head

Page 13: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Can sound be localized with one ear?

13

• total deafness in left ear, normal in right

• 100 ms white noise pulses.

• head immobilized

Localization ability improves with experience.

from Blauert, 1997

Page 14: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

The Function of the Pinna

Older theories:

• sound gathering (1600s - even today)

• Darwin (1800s): vestigial form of animal ear, no role in sound localization

• Lord Rayleigh (1907): distinguish between front and back

14

from Warren, 1999

Page 15: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Batteau’s theory (1967, 1968)

• Echos produced by pinnae provide lateralization and elevation cues.

• used microphones in pinna casts

• measured delays for azimuths and elevations:

- azimuths: 2 to 80 μsec

- elevations: 100 to 300 μsec

• then the key experiment:

listening through casts caused externalization

• also observed that animals have pinnae of similar shapes

15

Timmear

Freedman and Fisher (1968):

• Not necessary to use subject’s own pinnae

• subjects can localize with other pinnae, but with less accuracy

• Only a single pinna (monaural) is needed for localization

Page 16: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Testing Batteau’s theory

• Do we perceive monaural echos?

• Combining noise with a delay of itself results in spectral filtering

16

from Warren, 1999

from Warren, 1999

Page 17: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Model proposed by Blauert to explain the effect of the pinna as a reflector.

from Blauert, 1997

17

Page 18: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

An improved analysis

Shaw and Teranishi (1968):

• Investigate pinna behavior in frequency domain using external ear model:

18

from Blauert, 1997

Page 19: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Acoustic resonance in the outer ear

Distribution of sound pressure for several natural resonances:

• confirmed first two resonances in natural ear

• others combine into a broad resonance

Distribution of sound pressure along model ear canal for 10 kHz:

• resonances are direction dependent.

• pinna and ear canal form a system of acoustical resonators.

19

from Blauert, 1997

Page 20: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

The general case

• What limitations do the pinnae measurements have?

- Do not take into account the effect of the head and body.

• How to characterize the filtering?

- Measure the transfer function: ratio of pressure at sound source to pressure of (ideally) sound reaching eardrum

- this is called the head-related transfer function (HRTF)

20

Page 21: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Measuring HRTFs

• Different types of HRTFs

- monaural: pressure at source vs ear drum

- binaural: pressure difference for two corresponding points in the ear canal

21

Kemar the sound dummy

Subject with probe mics

from Blauert, 1997

Page 22: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Measured monaural HRTF

22

from Blauert, 1997

Page 23: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Measured binaural HRTF

23

from Blauert, 1997

Page 24: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

Problems in using HRTFs

24

• HRTFs vary across subjects

• can’t easily get an “average”

• but can do “structural averaging”

from Blauert, 1997

Page 25: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2

More than just direction: cues for sound distance

• Frequency independent 1/r

• pressure attenuation – works if you know some properties of sound source

• HRTF depends on distance

• freq. dependent attenuation (long distances)

• head movements (short distances)

25

Curves have 1/r attenuation factored out

from Blauert, 1997

Page 26: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2 26

Next time: the computational problem

Page 27: Computational Perception

Michael S. Lewicki ◇ Carnegie MellonCP08:: Sound localization 2 27

Misconceptions still persist today...