Auditory Perception

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					Auditory Perception

     Meena Ramani
      04/09/2004



      Department of Electrical & Computer Engineering
                              Note
    For 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




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              Main Outline
• Anatomy of the Ear and Hearing DONE
• Auditory perception
• Hearing aids and Cochlear implants.

Extra: Direction of Arrival Estimation




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Auditory perception

•   Shepard Tones
•   Masking <Detailed look>
•   Ohms Acoustic Law
•   Critical Bands
•   Webers law
•   Just Noticeable Frequency


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Roger Penrose                                                         M.C. Escher
                                   Optical
                                   Illusion




                Ascending and Descending


                              Audio
                              Illusion




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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.


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

                MASKING


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       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



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    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



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 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




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  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


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  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
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    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




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Temporal Aspects of Masking (cont)




    • Simultaneous Masking
    • Pre-Stimulus/Backward/Premasking
       – 1st test tone 2nd Masker
    • Poststimulus/Forward/Postmasking
       – 1st Masker 2nd test tone


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Types of Masking
Simultaneous 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
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Ohm’s Acoustic Law
The sound quality of a complex tone depends ONLY on the
  amplitudes and NOT relative phases of its harmonics.




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 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

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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

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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.




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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

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HEARING AIDS




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                     Outline
•   Facts on hearing loss
•   Cell phones and hearing loss
•   Types of Hearing aid
•   Inside a hearing aid
•   Audiogram




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     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.




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      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.




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Types of Hearing aids

  Behind The ear
                                                           In the Ear




 In the Canal                                              Completely in the
                                                           canal




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Anatomy of a Hearing Aid
                 •     Microphone
                 •     Tone hook
                 •     Volume control
                 •     On/off switch
                 • Battery compartment




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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.

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Audiograms




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Direction of Arrival (DOA) estimation algorithm


        <Useful for class project ideas>



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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




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Where does the DOA come into the picture?




                                   DOA Estimation                        7 is good
        Lets meet                                                         11 sounds
         at 11?!?                     qs & qn                              for me
                                                                             good!!
                                                                            too!!



                                     Beamformer




                    Has 2 microphones




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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.



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                                                 DOA Algorithms


                Spatial Correlation                                                   Subspace decomposition
                     methods                                                                 methods




                                                                                                             ESPRIT
Delay and Sum                    Minimum Variance                         MUSIC
                                                                                                 Estimation of Signal parameters
                                                                 Multiple Signal Estimation
                                                                                                    using rotational invariance




                                                                                  Coherent MUSIC




                                                                                    Root MUSIC




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DOA Method      Equation for Implementation


                P (q )  a (q ) Sa (q )
                               *
Delay and Sum

Minimum                             1
Variance        P(q ) 
                           a* (q )inv( s )a (q )
MUSIC
                               a (q )a(q )
                                *

                P(q ) 
                          a (q ) EN EN a(q )
                           *           *



Coherent                            a 'a
MUSIC            P (q ) 
                               a ' EN EN ' a
Root MUSIC
                 q K  sin 1 c.angle( z ) /(0 d )

ESPRIT           q K  sin
                               1
                                    c arg(   K
                                                   ) /(0 d )




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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




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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



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     Comparison of accuracy at different SNR values
                                                                 Comparison of Estimated DOAs: SNR=10dB,Speech= 90' ,Noise=0'
                                                    180

                                                    160                                                         ESPRIT
                                                                                                                RMUSIC
                                                    140                                                         CMUSIC
                                                                                                                MUSIC
                                                                                                                MV
                          Estimated DOA (degrees)




                                                    120                                                         DS

                                                    100

                                                     80

                                                     60

                                                     40

                                                     20

                                                         0
                                                             0            5            10          15              20           25
                                                                                        Frame Number




                                                                   Estimated DOAS for only those regions which are speech
                                    180

                                    160

                                    140
Estimated DOA (Degrees)




                                    120

                                    100

                                                    80

                                                    60

                                                    40

                                                    20

                                                    0
                                                         0                       5                      10                      15
                                                                                      Frames Number




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Comparison of Accuracy-MFLOPS




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   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)




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                                    Comparison of Estimated DOAs: SNR=10dB,Speech= 90' ,Noise=0'
                          180

                          160                                                                  ESPRIT
                                                                                               RMUSIC
                          140                                                                  CMUSIC
                                                                                               MUSIC
                                                                                               MV
Estimated DOA (degrees)




                          120                                                                  DS

                          100

                          80

                          60

                          40

                          20

                           0
                                0            5             10          15                           20    25
                                                            Frame Number




                                                        Department of Electrical & Computer Engineering
                                    Estimated DOAS for only those regions which are speech
                          180

                          160

                          140
Estimated DOA (Degrees)




                          120

                          100

                          80

                          60

                          40

                          20

                           0
                                0                  5                                  10            15
                                                         Frames Number




                                                  Department of Electrical & Computer Engineering
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