Integrating Perception into the Flexcode Project FlexCode...auditory modeling and audio coding •...

SIP - Sound and Image Processing Lab, EE, KTH Stockholm 1

FlexCode

The Sensitivity Matrix

Integrating Perception into the Flexcode Project

Jan PlasbergFlexcode Seminar Lannion

June 6, 2007


FlexCode Outline

• Flexcode in a Nutshell• The Sensitivity Matrix• Coding with the Sensitivity Matrix• Open Issues


FlexCode Who?

France Telecom

RWTH Aachen

KTH

NokiaEricsson


FlexCode The Problem

• Heterogeneity of networks increasing• Networks inherently variable (mobile users)

• But:– Coders not designed for specific environment– Coders inflexible (codebooks and FEC)– Feedback channel underutilized


FlexCode Adaptation and Coding

set of models, fixed quantizer

flexible

rigid

CELP with FEC

fixed model

fixed quantizer

adaptive coding

AMR

FlexCode

PCM


FlexCode The Tools

• Tools include– Models of source, channel, receiver– High-rate quantization theory– Multiple description coding (MDC)– Iterative source-channel decoding– Distortion measures using the sensitivity matrix


FlexCode Outline

• Flexcode in a Nutshell• The Sensitivity Matrix

– Why, what and how?– What can it tell us?

• Coding with the Sensitivity Matrix• Open Issues


FlexCode

• Simultaneous masking (frequency masking)

Human Auditory Masking


FlexCode

• Non-simultaneous masking (time masking)

• Not accounted for by simple auditory models• Coding standards use (heuristic) work-arounds

Human Auditory Masking


FlexCode

• Merge the worlds ofauditory modeling and audio coding

• Advanced auditory models too complex for coding

AM

AM+

x

x̂⋅ )ˆ,( xxd

perceptual distortion criterion

Motivation


FlexCode The Sensitivity Matrix

• Sensitivity Matrix M from Taylor expansion

Complexity problem solved!

Analysis of model properties using linear algebra• Masking curve• Subspace-based analysis

0)ˆ,(),ˆ()()ˆ(21)ˆ,( →−−≈ xxxxxMxxxx dd x

H

xx

xxxM=

∂∂∂

=ˆ

2

, ˆˆ)ˆ,()]([

jijix xx

d


FlexCode Application to an Auditory Model

• A typical auditory model (here: the Dau model)

• Distortion is sum of per-channel distortions

Filte

rban

k

Stage 1

Stage 2

Stage KL yx

channel m



• Find sensitivity matrix for model output y per channel m

Filte

rban

kStage

1Stage

2Stage

KL yx

)ˆ()()ˆ(21)ˆ,( )()( yyyMyyyy −−= m

yHmd

IyM 2)()( =myhere



• Each model stage linearized by respective Jacobian

Filte

rban

kStage

1Stage

2Stage

KL yx

z∂ y∂)(zJ z



• Get sensitivity matrix for channel m in input signal domain from chain rule;

Filte

rban

kStage

1Stage

2Stage

KL yx

∏∏⎥⎥⎦

⎤

⎢⎢⎣

⎡=

k

mk

H

k

mk

mx x )()()( 2)( JJM



• Sensitivity Matrix is sum of per-channel matrices

Filte

rban

kStage

1Stage

2Stage

KL yx

∑ ∏∏∑⎥⎥⎦

⎤

⎢⎢⎣

⎡==

m k

mk

H

k

mk

m

mxx

)()()( 2)()( JJxMxM


FlexCode Validity of the Approximation

• Narrow-band music + white noise at different SNR (10-60 dB), correlation > 0.9

(dB)Daud

(dB)SMd coding possible


FlexCode Analysis: Fourier Transform

• Sensitivity matrix for frequency domain vectors, with = DFT in matrix notation

)(XM X

HxX FxMFXM )()( =

F

)ˆ()ˆ( XXFxx −=− H


FlexCode Analysis: Masking Curve

• Assume masking threshold is at • Masking curve at frequency i:

gain for unit distortion in DFT bin i

to approach masking threshold

iiXHi guXMu )(

211 =

[ ]Hi 010 LL=u

[ ] iiXig

,)(2XM

=⇔

ig

1)ˆ( =XX,d

pos. i


FlexCode

0 500 1000 1500 2000 2500 3000 3500 40000

10

20

30

40

50

60

F

MA

SK

Example 1: Simultaneous Masking

• Masking curve for 50 dB sinusoid at 1000 Hz

dB

f (Hz)

- sensitivity matrix for Dau et al.- spectral model (v.d.Par, 2002)O human listeners (Zwicker, 1982)


FlexCodeExample 2: Non-Simultaneous Masking

• Subspace analysis of M: low sensitivity space

signal

noise

projection

t (ms)


FlexCodeF

200

700

F

200

700

F

T 50 100

200

700

A Spectro-Temporal Experiment

• Spectrograms for two sinusoids (200 Hz and 700 Hz) coded with an APCM coder

signal

WMSE-coder

Sens.-coder

f (H

z)

t (ms)

f (H

z)f (

Hz)


FlexCode Outline



FlexCode Problem

• Sensitivity Matrix generally not diagonal in typical coding domains (e.g., time, frequency, etc.)

– distortion not single-letter:

– no analytical solution known for optimal coding– so far only trained VQ available

(undoable for large dimensions)!

)ˆ()()ˆ(21)ˆ,( xxxMxxxx −−≈ x

Hd


FlexCode Solution Outline

• Sensitivity Matrix diagonal in perceptual domain– transform signal vectors into perceptual domain– (W)MSE-optimal coding in perceptual domain results in

minimum perceptual distortion • Optimal Transform:

)()()( xMxFxF xoptT

opt c=′′


FlexCode Making it Practical

• Problem: optimal transform depends on x– not known at decoder!

• Solution: Parameterize transform as DCT + diagonal weights

– combines DCT coding gain with perceptual transform!– Model-driven approach to temporal noise shaping (TNS)

tDCTf WTWxF =′ )(


FlexCode Examples

• Original

• Freq. weights

• Time-freq. weights

DCTf TWxF =′ )(

tDCTf WTWxF =′ )(


FlexCode Outline



FlexCode Complexity

• Main complexity lies here:

• Can we make multiplications ‘sparse’?• Can we reduce the size of the matrices?

∑ ∏∏⎥⎥⎦

⎤

⎢⎢⎣

⎡=

m k

mk

H

k

mk

)()(2)( JJxM


FlexCode Conclusion

• Using auditory models in coding is possible• General method• Direct applicability in AbS structures (CELP)• Solution outline for transform coding


FlexCode The End

Thank you!

Integrating Perception into the Flexcode Project FlexCode...auditory modeling and audio coding •...

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