Overview of the AMR concept Global System for Mobile ... · Overview of the AMR concept oUnlike...

1

Global System for Mobile Communications (GSM)

Eloi Batlle

Digital Speech Processing

Universitat Pompeu Fabra

Overview of the AMR concept

o Unlike previous GSM codecs which operate at a fixed rate and constant error protection level, AMR adapts to the local radio channel and traffic conditions

o Full-rate only for maximum robustness to channel errors

o Half-rate only for maximum capacity advantage

Multi-rate adaptation

o The AMR adaptation is based on the quality of the radio channel

o Modes

7.95 kbits/s 5.90 kbits/s7.40 kbits/s 5.15 kbits/s6.70 kbits/s 4.75 kbits/s

Half-rate

12.2 kbits/s 6.70 kbits/s10.2 kbits/s 5.90 kbits/s7.95 kbits/s 5.15 kbits/s7.40 kbits/s 4.75 kbits/s

Full-rate

bit-rateChannel

Bit allocation

954.75 kbit/s

1035.15 kbit/s

1185.90 kbit/s

1346.70 kbit/s

1487.40 kbit/s

1597.95 kbit/s

20410.2 kbit/s

24412.2 kbit/s

Bits per frameMode

2

Transmit side Receive side

Notesn 1) 8-bit A-law or -law PCM (ITU-T recommendation G.711), 8

000 samples/s;n 2) 13-bit uniform PCM, 8 000 samples/s;n 3) Voice Activity Detector (VAD) flag;n 4) Encoded speech frame, 50 frames/s, number of bits/frame

depending on the AMR codec mode;n 5) Silence Descriptor (SID) frame (marked SID_FIRST or

SID_UPD);n 6) TX_TYPE, 2 bits, indicates whether information bits are

available and if they are speech or SID information;n 7) Information bits delivered to the radio subsystem;n 8) Information bits received from the radio subsystem;n 9) RX_TYPE, the type of frame received quantized into three

bits, (classified by the RSS).

Discontinuous transmission

o Each direction of transmission is occupied about 50% of the time

o Discontinuous transmission (DTX)n Mobile Station battery life will be prolongedn Better radio frequency spectrum efficiency

o DTX requires some functionsn Voice Activity Detector (VAD)n Comfort noise

3

Voice Activity Detection

o The input to the VAD is a set of parameters computed by the encoder

o Each 20 ms the system decides whether the frame contains speech or not

Comfort noise insertiono When transmission is on, the background

noise is transmitted together with the speech

o When the speech ends, the connection is off and the perceived noise would drop to a very low level

o This step modulation of noise may be perceived as annoying

o Comfort noisen Evaluation of background noisen Noise parameters encoding and decodingn Generation of comfort noise in the receiver

Lost speech frame substitution

o Frames may be lost due to transmission errors

o In order to mask the effect of an isolated lost frame, it is substituted by a predicted one based on previous frames

o For several lost frames, a muting technique shall be used

AMR codec homing

o All modules shall react on a given input sequence always with the corresponding bit exact output sequence, provided that the tested modules are in their home-state when starting

o Special inband signaling frames have been defined to provoke these homing-functions also in remotely placed modules

4

Frequency responseAMR Codec Frequency Response

-35

-30

-25

-20

-15

-10

-5

0

5

50 470 890 1310 1730 2150 2570 2990 3410 3830

Frequency [Hz]

[dB]

12.2 kbit/s

10.2 kbit/s

7.95 kbit/s

7.40 kbit/s

6.70 kbit/s

5.90 kbit/s

5.15 kbit/s

4.75 kbit/s

Speech encodero Pre-processingo Linear prediction analysis and quantizationo Open-loop pitch analysiso Impulse response computationo Target signal computationo Adaptive codebooko Algebraic codebooko Quantization of the adaptive and fixed

codebook gainso Memory update

Speech encoder (2)

o Speech frames of 20ms (160 samples)

o 8000 samples/s frequencyo Speech frame divided into 4

subframes of 5 ms (40 samples)o Adaptive and fixed codebook

parameters are transmitted every subframe

Speech encoder (and 3)

w indowingand a utoc orr elationR [ ]

Le vinson-Durbin

R[ ] A(z)

A(z)

LSPquantiza tion

c ompute ta rgetfor

innova tion

update filterme mories forne xt subfra me

O pe n-loop pitch se arc h Adaptive c ode bookse ar ch

Innovativ e codebookse ar ch

Filter m em oryupdate

inte rpola tion

subframe sLSP A(z)

LSP

c omputew eighte d

spee ch(4 subfra me s)

findope n-loop pitc h

find be st innova tion

fixed codebook

ga in qua ntiz ation

A(z )^

x(n)

pitchindex

codeinde x

frame subframe

s (n) c ompute targetfor a da ptivec odebook

Tofind be st de lay

a nd gain

x (n)

c omputeimpulse

re spons eA( z)^

A(z) h(n)

h(n)

A(z)

LPC analy sis(twice pe r frame )

A(z)

(twice pe r fram e)

x (n)2

qua ntizeLTP-gain

computeadaptive

codebookcontr ibution

LSPindic es

LTPgain

index

gain indexfixe d code book

inte rpola tionfor the 4

subfr amesLSP A(z)^

for the 4

Pre -proc es sing

Pr e-proc ess ing

computeexcita tion

5

Speech decoder

LSPin dices

d ecode LSP

int erpo latio n of LSP fo r th e4 su bframe s

LSP

d ecodead aptiv eco deboo k

deco deinn ovati veco debo ok

p itchi ndex

c odein dex

deco degains

A(z)^

co nstructexcit ation

frame subfram e post-processing

s'(n)^s(n)^p ost f ilter

g ainsindi ces

sy nthesisf ilter

CELP synthesis modelo Code-excited linear predictive coding model

A(z)1 s(n)^

+

v(n)

c(n)

u(n)

gc

fixedcodebook

adaptive codebook gp

LP synthesis

post-filtering s'(n)^

Pre-processing

o High-pass filteringo Down-scaling (factor of 2)

21

21

1 911376953.0906005859.11927246903.08544941.1927246093.0)( −−

−−

+−+−=

zzzzzHh

Windowing and autocorrelationo 12.2 kbits/sn Twice per frame analysis using two different

asymmetric windows with L 1(I)=160, L 2

(I)=80, L1

(II)=232 and L 2(II)=8

−+=

−−

−=

−

−=

−+=

−

−+

−=

−

−=

1,, , 14

)(2cos

,1,,0 , 12

2cos46.054.0

)(

.1,, , 1

)(cos46.054.0

,1,,0 , 1

cos46.054.0

)(

)(2

)(1

)(1)(

2

)(1

)(1)(

1

)(2

)(1

)(1)(

2

)(1

)(1)(

1

IIIIIIII

II

II

II

II

III

I

I

II

I

LLLnL

Ln

LnL

n

nw

LLLnL

Ln

LnL

n

nw

K

K

K

K

π

π

π

π

6

Windowing and autocorrelation (2)

o 12.2 kbits/s

20 ms5 ms

frame (160 sample s) sub frame(40 sa mples)

fr ame n-1 frame n

t

Iw (n)

IIw (n)


o 12.2 kbits/s

n The autocorrelation is computed by

r k s n s n k kacn k

( ) ' ( ) ' ( ) , , , ,= − ==

∑239

0 10 K

o 12.2 kbits/sn A 60Hz bandwidth expansion used by lag

windowing the autocorrelation

n Where f0=60Hz is the bandwidth expansion and fs=8000Hz is the sampling frequency


( )

,10,1 ),()()('

10,1,2

21

exp2

0

K

K

==

=

−=

kkwkrkr

if

ifiw

lagacac

slag

π


o 12.2 kbits/sn A white noise correction factor is usedn It is equivalent to adding a noise floor of

-40dB

r rac ac' ( ) . ( )0 1 0001 0=

7

Windowing and autocorrelation (and 6)

o All other kbits/s modes

n Once per frame analysis using wII(n) window with L1=200 and L2=40

n Autocorrelation of the windowed speech and a 60Hz bandwidth expansion

n White noise correction factor of -40dB

Levinson-Durbin

[ ]( )

end)1()1()(

end

do 1 to1for

1

)('

1

do 10 to1for

)0(')0(

2

)1()1()(

)(

1

0)1(

)1(0

−−=

+=

−==

−

−−=

=

=

=

−−

−

−

=−

−

∑

iEkiE

akaa

ijka

iE

jirak

a

i

rE

i

ijii

ij

ij

ii

i

i

j acij

i

i

ac

LP to LSP conversion

o The linear prediction coefficients (LP) are converted to the line spectral pair (LSP) representation for quantization and interpolation purposes

o LSPs are defined as the roots of

( ) ( ) ( )( ) ( ) ( )111

2

1111

−−

−−

−=′

+=′

zAzzAzF

zAzzAzF

LP to LSP conversion (2)

o F1’(z) is symmetric and F2

’(z) is anti-symmetric

o All these roots are on the unit circle and they alternate each other

o F1’(z) corresponds to the vocal tract

with the glotis closed and F2’(z) with

the glotis open

8


o F1’(z) has a root z=-1 (ω=π)

o F2’(z) has a root z=1 (ω=0)

o To eliminate these two roots we define

( ) ( ) ( )( ) ( ) ( )1

22

111

1

1−

−

−′=

+′=

zzFzF

zzFzF

o Each polynomial has 5 conjugate root on the unit circle, therefore they can be written as

o Where qi=cos(ω i) with ω i being the line spectral frequencies (LSF) and qi are the LSP in the cosine domain


( ) ( )

( ) ( )∏

∏

=

−−

=

−−

+−=

+−=

10,,4,2

212

9,,3,1

211

21

21

K

K

ii

ii

zzqzF

zzqzF


o The LSP are found by evaluating F1(z) and F2(z) at 60 points equally spaced between 0 and π and checking for sign changes

o The sign change interval is then divided by 4 to better track the root


o LPC vs. LSP

9

LP to LSP conversion (and 7) LSP coefficients quantization

o 12.2 kbits/sn The two sets of LP coefficients are

quantified using the LSP representation in the frequency domain

( )ff

q iis

i= =2

1 10π

arccos , , , ,K

LSP coefficients quantization (2)

o 12.2 kbits/sn A 1st order MA prediction is applied and

the prediction residual vectors are given by

n Where z(n) are the mean-removed LSF vectors and p(n) is the predicted vector

( ) ( ) ( )( ) ( ) ( )

r z pr z p

( ) ( )

( ) ( ),,

1 1

2 2n n nn n n

= −= −

and

( ) ( )p rn n= −0 65 12. $ ( )


o 12.2 kbits/sn The two residual vectors are jointly

quantified using split matrix quantization (SMQ)

n The matrix (r(1) r(2)) is split into 5 submatrices of 2x2

n The 5 submatrices are quantified with 7, 8, 8+1, 8 and 6 bits respectively (the third matrix uses a signed codebook)

10


o All other kbits/s modesn The LP coefficients are quantified using

the representation in the frequency domain

n A 1st order MA prediction is applied

LSP coefficients quantization (and 5)

o All other kbits/s modesn The residual vector is split into 3 subvectors of

dimensions 3, 3 and 4

7884.75 kbit/s

7885.15 kbit/s

9985.90 kbit/s

9986.70 kbit/s

9987.40 kbit/s

9997.95 kbit/s

99810.2 kbit/s

Subvector 3Subvector 2Subvector 1Mode

LSP interpolation

o 12.2 kbits/sn The two sets of LP parameters are used

for the 2nd and 4th subframen 1st and 3rd subframes use a linear

interpolation of the parameters in the adjacent subframes

$ . $ . $ ,$ . $ . $ .

( ) ( ) ( )

( ) ( ) ( )q q q

q q q1 4

12

3 2 4

05 0 5

05 05

n n n

n n n= += +

−

LSP interpolation (and 2)

)(4

)1(4

)(3

)(4

)1(4

)(2

)(4

)1(4

)(1

ˆ75.0ˆ25.0ˆ

ˆ5.0ˆ5.0ˆ

ˆ25.0ˆ75.0ˆ

nnn

nnn

nnn

qqq

qqq

qqq

+=

+=

+=

−

−

−

oAll other kbits/s modesnLP parameters are used for the 4th

subframen1st, 2nd and 3rd subframes use a linear

interpolation of the parameters in the adjacent subframes

11

LSP to LP conversion

o Once the LP are quantified and interpolated, they are converted back to the LP coefficients domain

( )( )

( ) ( ) ( )

( ) ( ) ( ) ( )

endend

212 1 down to 1for

2212 5 to1for

1001

111211

11121

1

1

−+−−=−=

−+−−===

=−

−

−

jfjfqjfjfij

ififqifi

ff

i

i

LSP to LP conversion (2)

o f1’(i) and f2’(i) are found by

o And the LP coefficients by

( ) ( ) ( )( ) ( ) ( )′ = + − =′ = − − =

f i f i f i if i f i f i i

1 1 1

2 2 2

1 1 51 1 5, , ,, , ,

KK

( ) ( )( ) ( )a

f i f i i

f i f i ii =′ + ′ =

′ − − ′ − =

05 05 1 5

05 11 0 5 11 6 101 2

1 2

. . , , ,

. . , , ,

K

K

Monitoring resonance

o Resonances in the LPC filter are monitored to detect possible problems

Open-loop pitch analysis

o How to determine the location and height of the impulses?

o Based on analysis-by-synthesiso Filtering of the input signal with a

perceptual weighting filter

( ) ( ) ( )

( ) ( ) ( ) ( ) 1,,0,10

12

10

11

21

−=−−−+=

=

∑∑==

Lninsainsansns

zAzAzW

iw

ii

i

iiw Kγγ

γγ

12

Open-loop pitch analysis (2)

o 12.2 kbits/sn Search for the maxima of the correlation

in three ranges

n And normalized by dividing by

O s n s n kk w wn

= −=∑ ( ) ( )

0

79

.143,,721,71,,362,35,,183

KKK

===

iii

s n t iw in2 ( ),− =∑ 1, ,3K


o The best open-loop delay is found by

( )( )

( )

( )( )

T t

M T M

if M M T

M T MT t

endif M M T

M T MT t

end

op

op

op

op

op

op

op

op

=

=

>

==

>

==

1

1

2

2

2

3

3

3

0 85

0 85

.

.


o 10.2 kbits/sn Twice per frame (every 10ms)n The correlation is determined by

n Windown Low pitch lag (tables)n Previous frame lago dL=20o Told median 5 previous

( ) ( ) ( ) ( )C d s n s n d w d dw wn

= − ==∑

0

79

20 143, , ,K

( ) ( ) ( )w d w d w dl n=( ) ( )w d cw dl =

( ) ( )w d

cw T d d vn

old L=− + >

, . ,

. ,

0 3

1 0 otherwise,


o 7.95, 7.40, 6.70, 5.90 kbits/sn Twice per frame (each 10ms)

n And normalized by

n Maxima and delays are (Mi,t i), i=1,2,3

O s n s n kk w wn

= −=∑ ( ) ( )

0

79

.143,,801,79,,402,39,,203

KKK

===

iii

s n t iw in2 ( ),− =∑ 1, ,3K

13



( )( )

( )

( )( )

T t

M T M

if M M T

M T MT t

endif M M T

M T MT t

end

op

op

op

op

op

op

op

op

=

=

>

==

>

==

1

1

2

2

2

3

3

3

0 85

0 85

.

.


o 5.15, 4.75 kbits/sn Once per frame (each 20ms)

n And normalized by

n Maxima and delays are (Mi,t i), i=1,2,3

O s n s n kk w wn

= −=∑ ( ) ( )

0

79

.143,,801,79,,402,39,,203

KKK

===

iii

s n t iw in2 ( ),− =∑ 1, ,3K

Open-loop pitch analysis (and 8)


( )( )

( )

( )( )

T t

M T M

if M M T

M T MT t

endif M M T

M T MT t

end

op

op

op

op

op

op

op

op

=

=

>

==

>

==

1

1

2

2

2

3

3

3

0 85

0 85

.

.

Impulse response

o The impulse response of the weighted synthesis filter is computed each subframe

o This impulse response will be used for the search of codebooks

( ) ( ) ( ) ( ) ( )[ ]H z W z A z A z A z= γ γ1 2$

14

Adaptive codebook

o Adaptive codebook search is performed on a subframe basis

o The parameters are the delay and gain of the pitch filter

o The codebook contain entries taken from the previously synthesized excitation signal

Algebraic codebook

o Based on interleaved single -pulse permutation (ISPP) designn A few sparse impulse sequences that are

phase-shifted versions of each othern All the pulses have the same magnituden Amplitudes are +1 or -1

Algebraic codebook (and 2)o 12.2 kbits/sn 10 non-zero pulses

o 10.2 kbits/sn 8 non-zero pulses

o 7.95, 7.40 kbits/sn 4 non-zero pulses

o 6.70 kbits/sn 3 non-zero pulses

o 5.90, 5.15, 4.75 kbits/sn 2 non-zero pulses

CELP synthesis modelo Code-excited linear predictive coding model

A(z)1 s(n)^

+

v(n)

c(n)

u(n)

gc

fixedcodebook

adaptive codebook gp

LP synthesis

post-filtering s'(n)^

15

CELP synthesis model (and 2)

o To reconstruct speechn A noise-like excitation modeln A pitch filter model of the glottal

vibrationsn A linear prediction filter model of the

vocal tract

Speech decoder

LSPin dices

d ecode LSP

int erpo latio n of LSP fo r th e4 su bframe s

LSP

d ecodead aptiv eco deboo k

deco deinn ovati veco debo ok

p itchi ndex

c odein dex

deco degains

A(z)^

co nstructexcit ation

frame subfram e post-processing

s'(n)^s(n)^p ost f ilter

g ainsindi ces

sy nthesisf ilter

Speech decoder (2)

o Decodingn LP parametersn Adaptive codebook vectorn Adaptive codebook gainn Innovative codebook vectorn Innovative codebook gain

o Smoothing of the fixed codebook gaino Anti-sparseness processingo Speech synthesis

Adaptive codevector

o The received pitch index is used to find the integer and fractional parts of the pitch lag

o The adaptive codebook vector v(n) is obtained by interpolating the past excitation u(n) at the pitch delay

o The received index is used to find the quantised adaptive codebook gain gpfrom the quantisation table

16

Algebraic codebook

o The received index is used to extract the positions and amplitude signs of the excitation pulses and to find the algebraic code vector c(n)

o The received index is used to compute the quantised fixed codebook gain gc

Reconstructing speech

o The input excitation is

o The excitation is filtered by the LP filter

( ) ( ) ( )ncgnvgnu cp +=

( ) ( ) ( )zUzA

zY 1=

Overview of the AMR concept Global System for Mobile ... · Overview of the AMR concept oUnlike...

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