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Computational Spectro-
temporal Auditory Model
Taishih Chi
June 29, 2003
Auditory Model
• Overview – two stage processing
• Model description and formulation
• Examples of representations
• Reconstruction from model output
representations
• Discussions
Spectral
Estimation
Early Auditory
Spectral
Analysis
Primary Cortex (A1)
Sound
Auditory
Spectrum
Cortical
Representation
Auditory Model
Overview
• Temporal dynamics
reduction
• Monaural model
• Two stage functional
model
– Early stage
(spectrum estimation)
– Cortical stage
(spectrum analysis)
Early stage
Mathematical Formulation
Early Stage MATLAB Implementation
Matlab ToolBox Usage:
yfinal = wav2aud(s, [frmlen, tc, fac, shft], filt);
s : acoustic input signal
yfinal: auditory spectrogram; N(time) x M(freq.)
CF = 440 * 2 .^ ((-31:97)/24 + shft);
Cortical stage
Spectrotemporal Receptive Field
4
0.125
4
0.125
4
0.125
4
0.125
4 4
0.125
C
Frequency(kHz)Frequency(kHz)
Frequency(kHz)
Frequency(kHz)
Frequency(kHz)Frequency(kHz)
Time (ms) Time (ms) Time (ms)
Time (ms) Time (ms) Time (ms)
250 250 250
250250250
0 0 0
000
0.125
D E F
BA
(a)
Time (ms)
Log.Frequency
Downward; Ω:1 cyc/oct, ω:4 Hz
500 1000
0.25 CF
0.5 CF
1 CF
2 CF
4 CF
(b)
-1.25 0 1.25
0
Log. Frequency (octave)
hs
0 1 2 3 4 5
0
Time (sec)
ht
Cortical stage
Model Implementation
Cortical stage
Mathematical Formulation
where
then the spectrotemporal cortical response:
Cortical stage
Mathematical Formulation (cont’d)
Consider the complex wavelet transform
where
then
Cortical stage
Cortical Representation of Speech
Frequency(Hz)
Time (ms)
100 200 300 400 500 600 700 800 900 1000
125
250
500
1000
2000
Multiresolution Cortical Filters and Outputs
Upward Downward
Slow Rate
Coarse Scale
Slow Rate
Fine Scale
Fast Rate
Coarse Scale
Fast Rate
Fine Scale
Slow Rate
Coarse Scale
Slow Rate
Fine Scale
Fast Rate
Coarse Scale
Fast Rate
Fine Scale
Cortical Magnitude Representation of Speech
Frequency(Hz)
Time (ms)
Auditory Spectrogram
100 200 300 400 500 600 700 800 900 1000
125
250
500
1000
2000
Multiresolution Cortical Filters and Outputs
Upward Downward
Slow Rate
Coarse Scale
Slow Rate
Fine Scale
Fast Rate
Coarse Scale
Fast Rate
Fine Scale
Slow Rate
Coarse Scale
Slow Rate
Fine Scale
Fast Rate
Coarse Scale
Fast Rate
Fine Scale
Cortical Stage MATLAB Implementation
Matlab ToolBox Usage:
cr = aud2cor(y, para1, rv, sv, fname, DISP);
cr: 4D cortical representation (scale-rate(up-
down)-time-freq.)
y : auditory spectrogram, N(time) x M(freq.)
para1 = [paras FULLT FULLX BP],paras:see WAV2AUD
FULLT (FULLX): fullness of temporal (spectral)
margin.
BP: pure bandpass indicator.
rv: rate vector in Hz, e.g., 2.^(1:.5:5).
sv: scale vector in cyc/oct, e.g., 2.^(-2:.5:3).

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auditory model

  • 1. Computational Spectro- temporal Auditory Model Taishih Chi June 29, 2003
  • 2. Auditory Model • Overview – two stage processing • Model description and formulation • Examples of representations • Reconstruction from model output representations • Discussions Spectral Estimation Early Auditory Spectral Analysis Primary Cortex (A1) Sound Auditory Spectrum Cortical Representation
  • 3. Auditory Model Overview • Temporal dynamics reduction • Monaural model • Two stage functional model – Early stage (spectrum estimation) – Cortical stage (spectrum analysis)
  • 5. Early Stage MATLAB Implementation Matlab ToolBox Usage: yfinal = wav2aud(s, [frmlen, tc, fac, shft], filt); s : acoustic input signal yfinal: auditory spectrogram; N(time) x M(freq.) CF = 440 * 2 .^ ((-31:97)/24 + shft);
  • 6. Cortical stage Spectrotemporal Receptive Field 4 0.125 4 0.125 4 0.125 4 0.125 4 4 0.125 C Frequency(kHz)Frequency(kHz) Frequency(kHz) Frequency(kHz) Frequency(kHz)Frequency(kHz) Time (ms) Time (ms) Time (ms) Time (ms) Time (ms) Time (ms) 250 250 250 250250250 0 0 0 000 0.125 D E F BA
  • 7. (a) Time (ms) Log.Frequency Downward; Ω:1 cyc/oct, ω:4 Hz 500 1000 0.25 CF 0.5 CF 1 CF 2 CF 4 CF (b) -1.25 0 1.25 0 Log. Frequency (octave) hs 0 1 2 3 4 5 0 Time (sec) ht Cortical stage Model Implementation
  • 8. Cortical stage Mathematical Formulation where then the spectrotemporal cortical response:
  • 9. Cortical stage Mathematical Formulation (cont’d) Consider the complex wavelet transform where then
  • 10. Cortical stage Cortical Representation of Speech Frequency(Hz) Time (ms) 100 200 300 400 500 600 700 800 900 1000 125 250 500 1000 2000 Multiresolution Cortical Filters and Outputs Upward Downward Slow Rate Coarse Scale Slow Rate Fine Scale Fast Rate Coarse Scale Fast Rate Fine Scale Slow Rate Coarse Scale Slow Rate Fine Scale Fast Rate Coarse Scale Fast Rate Fine Scale
  • 11. Cortical Magnitude Representation of Speech Frequency(Hz) Time (ms) Auditory Spectrogram 100 200 300 400 500 600 700 800 900 1000 125 250 500 1000 2000 Multiresolution Cortical Filters and Outputs Upward Downward Slow Rate Coarse Scale Slow Rate Fine Scale Fast Rate Coarse Scale Fast Rate Fine Scale Slow Rate Coarse Scale Slow Rate Fine Scale Fast Rate Coarse Scale Fast Rate Fine Scale
  • 12. Cortical Stage MATLAB Implementation Matlab ToolBox Usage: cr = aud2cor(y, para1, rv, sv, fname, DISP); cr: 4D cortical representation (scale-rate(up- down)-time-freq.) y : auditory spectrogram, N(time) x M(freq.) para1 = [paras FULLT FULLX BP],paras:see WAV2AUD FULLT (FULLX): fullness of temporal (spectral) margin. BP: pure bandpass indicator. rv: rate vector in Hz, e.g., 2.^(1:.5:5). sv: scale vector in cyc/oct, e.g., 2.^(-2:.5:3).