Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals Larry Feth Ashok Krishnamurthy Ohio State...
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Transcript of Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals Larry Feth Ashok Krishnamurthy Ohio State...
Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals
Larry FethAshok KrishnamurthyOhio State University
Spectral Center-of-Gravity Chistovitch and Lublinskaja
(1976,1979)
Perceptual Formant at ‘Center-of-Gravity’
Two-formant synthetic vowel Matched by adjustable single-formant signal Center frequency of match depends on
relative amplitudes of the two formants
Experimental Paradigm
Chistovitch and Lublinskaja Results
Voelcker Two-tone Signals
Voelcker Two-tone Signals
Initially, led to the EWAIF model Envelope-Weighted Average of
Instantaneous Frequency (time domain) Point by point multiply E x F values Sum over N periods Divide by sum of weights
Indicates pitch change in periodic signals
Helmholtz (1954, 2nd English edition) Jeffress (1964)
EWAIF Model
Signal ( ) with envelope ( )
instantaneous frequency ( ).
EWAIF (Envelope weighted
average of instantaneous frequency)
( ) ( )EWAIF[ ( )]
( )
x t e t
i t
e t i t dtx t
e t dt
IWAIF Model Predictions
Two-tone resolution task Feth and O’Malley (1977)
Two-tone resolution I = 1 dB; f independent variable ‘Voelcker-tone pair’ pitch discrimination inverted “u-shaped” psychometric
functions Components resolved beyond –75% point ~3.5 Bark separation = jnnd
Voelcker Signal: Discrimination Task
Discrimination Results
Jnnd – ‘Just not noticeable difference’
Filled circles Breakpoint estimates
Open circles CR – critical ratio CBW CB – ‘empirical’ CBW Solid line TW envelope
IWAIF Model
Intensity Weighted Average of Instantaneous Frequency = Centroid of signal’s positive power spectrum (Anantharaman, et al., 1993)
2
2
20
20
( ) ( )IWAIF[ ( )]( )
| ( )|
| ( )|
e t i t dtx te t dt
f X f df
X f df
Dynamic Center-of-Gravity Effect
Lublinskaja (1996) Three-formant synthetic Russian vowels Listeners identified vowels with:
‘conventional’ formant transitions co-modulated formant pairs that exhibit the same
dynamic spectral center-of-gravity ID functions were very similar with formant
pairs separated by 4.3 Bark or less
Psychophysics
Anantharaman (1998) Two-tone signals with dynamic c-o-g
effect We called them ‘Virtual Frequency’
Glides Listeners matched transition rates in
VF glides to those in FM glides IWAIF model predicts results for
transitions from 2 to ~5 ERB
Dynamic Center-of-Gravity Signals
Waveform
Long-term Spectrum
Spectrogram
Rate-matching results
Model Results
Short-term running IWAIF Model
IWAIF Model Results
Application of ST-IWAIF Model
More Psychophysics
Research Question(s) What is being ‘integrated’ in spectral
integration?OR
Where in the auditory system is the processing located?
Psychophysics Iyer, et al., (2001)
Temporal acuity for FM and VF glides Step vs. linear ramp discrimination Similar T values may mean common
process
Masking patterns for FM and VF glides Peripheral process i.e., ‘Energy Masking’ Different results – VF not peripheral process
Temporal Acuity Paradigm
Step (red) versus Glide (blue) transitions for FM tone (left panel) and Virtual Frequency (right panel)
Temporal Acuity Results
Just discriminable step duration for FM (solid lines; filled symbols) and VF (dashed lines; unfilled symbols) signals. Frequency separations are 2, 5 and 8 ERBu. The results for 1000 Hz are represented by circles and those for 4000 Hz by triangles. Average for 4 listeners.
Frequency separation (ERBu)
2 ERBu 5 ERBu 8 ERBu
Step
Dur
ation
(mse
c)
0
2
4
6
8
10
12
14
16
18
20
Dynamic Center-of-Gravity Maskers
Masking of brief probe by FM glide (left panel) and by VF glide (right panel). Probe is in the spectro-temporal center of each masker. Five auditory filter bands are illustrated.
Time
Fl
Fc
Fh
Time
Fl
Fc
Fh
Masking Results
Masking of a 20 ms probe by FM (light blue) and VF (darker blue) maskers. The probe is placed at the beginning, middle, and end of the masker. Significant differences are seen at 5 and 8 ERB for the middle position and the initial position at 8 ERB. Average for 4 listeners.
Probe in initial position
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
2 ERBu 5 ERBu 8 ERBu
Frequency separation
Am
ou
nt
of
Ma
sk
ing
(d
B S
PL
)
FM Masker
VF Masker
Probe in medial position
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
2 ERBu 5 ERBu 8 ERBu
Frequency separation
Am
ount
of M
aski
ng (d
B SP
L)
FM Masker
VF Masker
Probe in final position
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
2 ERBu 5 ERBu 8 ERBu
Frequency separation
Am
ount
of M
aski
ng (d
B S
PL)
FM Masker
VF Masker
Glide Direction Asymmetry Gordon and Poeppel
3 Frequency ranges: (for F1,F2 & F3) ~ 30 unpracticed listeners 20 trials / signal One interval Direction Identification: Up vs. Dn
Best results at high frequency (F3) range 10- through 160 ms ‘Up’ is easier to ID than ‘Dn’ Less clear-cut results at low or mid-freq. ranges
Glide Direction Asymmetry
Gordon and Poeppel – ARLO (2002)Identification of FM Sweep direction is easier for rising than for
falling tones.
Glide Direction Asymmetry Dawson, (2002)
Tested only high frequency range (F3) Practiced listeners; ~ 100% all
conditions! Modified procedure
Rove each frequency sweep over 1 octave
Practice to ~ asymptote
Glide ID Results Average for 4
listeners One-interval ID task 250 trials / datum
point Well-practiced Subj’s Starting frequency
roved over 1-octave range
Summary FM ‘easier’ than VF Up ‘easier’ than Down
Duration (ms)
5 10 20 30 40 50 80 160
Perc
ent C
orre
ct Id
entif
icat
ion
50
55
60
65
70
75
80
85
90
95
100
FM Up
FM Down
VF Up
VF Down
CV Identification Experiment
[da] – [ga] continuum: varying F3 transition Duration: 50 ms transition into 200 ms base F3 onset: 2018 to 2658 Hz in 80 Hz steps F3 base: 2527 Hz (constant)
Formant transition ‘type’: Klatt synthesizer Frequency Modulated tone glide Virtual Frequency glide
CV Identification: Stimuli
Spectrogram 1. Step 1 of Klatt Monaural Continuum—/ga/ endpoint
CV Identification: Stimuli
Spectrogram 2. Step 1 of FM Monaural Continuum—/ga/ endpoint
CV Identification: Stimuli
Spectrogram 3. Step 1 of VF Monaural Continuum—/ga/ endpoint
CV Identification: Stimuli
Spectrogram 4. Step 1 of Dichotic FM Continuum—/ga/ endpoint
CV Identification: Stimuli
Spectrogram 5. Step 1 of Dichotic VF Continuum—/ga/ endpoint
CV Identification Experiment
Listeners: 8 adults with normal hearing
Procedure: One interval, 2-AFC 3 transition types: Klatt, FM or VF 6 of 8 tokens tested 20 repetitions / token
Results are averaged for the 8 listeners
CV Identification: Results
Fig. 4. Mean Responses for FM Tone and Virtual Glide Conditions
Formant 3 Onset Frequency (in Hz)
1900 2000 2100 2200 2300 2400 2500 2600 2700
% /
da
/ R
esp
on
ses
0
20
40
60
80
100FM
Virtual Glide
CV Identification: ResultsFig. 7. Mean Responses for Dichotic Condition
F3 Onset Frequency (Hz)
1900 2000 2100 2200 2300 2400 2500 2600 2700
% /d
a/ R
espo
nses
10
20
30
40
50
60
70
80
90
Klatt
FM
Virtual Glide
Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals
Conclusions ‘Excitation’ is integrated not signal
energy The processing is central not peripheral
Masking Patterns are very different Temporal Acuity results are similar for FM & VF
glides Direction ID Asymmetry is similar for FM & VF
glides
Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals
Conclusions CV identification functions are similar for:
Klatt synthesized sounds FM formant sounds VF formant sounds
Thus, it doesn’t matter how ‘excitation’ is moved from A to B, the brain will interpret it as the same sound.
The effect is evident under dichotic listening; further support for central processing.
Collaborators
Rob FoxNandini Iyer
Jayanth Anantharaman
Ewa Jacewicz Robin Dawson
Psychoacoustics of Dynamic ‘Center-of-Gravity’ Signals
Thank You
Questions?
Up vs. Down FM Glide
Up vs. Down FM Glide
Up vs. Down VF Glide
Up vs. Down VF Glide
Effect of Masker Direction
Masking produced by VF (above) and FM (below) maskers with F = 5 ERB. Purple bars are “up” glides; yellow bars are “down” glides. Centered probe.
Effect of Masker Position
Masking produced by VF (above) and FM (below) maskers with F = 5 ERB. Purple bars are “up” glides; yellow bars are “down” glides.
Klatt & FM Parameters
Fig. 1. Formant 3 Transitions for Klatt and FM Tokens
Time (ms)
0 10 20 30 40 50 60
Fre
qu
ency
1900
2000
2100
2200
2300
2400
2500
2600
2700
Step 1 (/ga/ endpoint)Step 2 Step 3 Step 4 Step 7 Step 8 (/da/ endpoint)
Virtual Frequency Parameters
Fig. 2. Tone Amplitude Changes in Step 1 (/ga/) of VG Continuum (2018 Hz virtual onset)
Time (ms)
0 10 20 30 40 50 60
Rel
ativ
e A
mpl
itud
e
0.0
0.2
0.4
0.6
0.8
1.0 Tone 1 (2018 Hz)Tone 2 (2658 Hz)
Fig. 3. Tone Amplitude Changes in Step 8 (/da/) ofVG Continuum (2578 Hz virtual onset)
Time (ms)
0 10 20 30 40 50 60
Rel
ativ
e A
mpl
itud
e
0.0
0.2
0.4
0.6
0.8
1.0
Tone 1 (2018 Hz) Tone 2 (2658 Hz)