Title of Invention

STOCHASTIC CODEBOOK EXCITATION VECTOR CODING METHOD

Abstract The invention relates to a coding method of an excitation vector of a stochastic codebook used in a speech coding apparatus that is divided into a plurality of channels, the coding method comprising: associating an excitation vector waveform candidate of a predetermined channel with an excitation vector waveform candidate of another channel, such that the excitation vector waveform candidate of the predetermined channel changes in association with a change of a number representing the excitation vector waveform candidate of the another channel; searching for an excitation vector waveform that minimizes coding distortion using the associated excitation vector waveform candidate of the predetermined channel and the excitation vector waveform candidate of the another channel; and determining a code of the excitation vector of the stochastic codebook using a code of the excitation vector waveform obtained by the searching, wherein: the searching, after the associating, calculates a function value using the number representing the changed excitation vector waveform candidate of the another channel and the excitation vector waveform candidate of the predetermined channel changed based on the associating, and, by the function value, finds an excitation vector waveform candidate of each channel that minimizes the coding distortion; and the determining finds the code of the excitation vector waveform by coding the excitation vector waveform candidate of each channel that minimizes the coding distortion as the excitation vector waveform, and determines the code of the excitation vector of the stochastic codebook using the code of the excitation vector waveform.
Full Text DESCRIPTION
STOCHASTIC CODEBOOK EXCITATION VECTOR CODING METHOD
Technical Field
The present invention relates to a stochastic
codebook excitation vector coding method in a CELP speech
coding apparatus/speech decoding apparatus.
Background Art
When speech signals are transmitted in a packet
communication system typified by Internet communication,
a mobile communication system, or the like, compression
and coding techniques are used to improve the speech signal
transmission efficiency. Many speech coding methods
have been developed to date, and many low bit rate speech
coding methods developed in recent years, such as CELP,
separate a speech signal into spectrum envelope
information and spectrum detailed structure information,
and perform compression and coding of the separated
information.
In a CELP speech coding apparatus, synthetic speech
vectors are calculated for all combinations of adaptive
code vectors stored by an adaptive codebook and fixed
code vectors stored by a stochastic codebook, distance
calculation is performed for each synthetic speech and
input speech signal, and the adaptive code vector index
and fixed code vector index for which the distance is

smallest are found.
One known stochastic codebook is an algebraic
codebook. This codebook enables a stochastic codebook
search to be performed with a comparatively small amount
of calculation, and has consequently been widely used
in CELP in recent years.
An excitation vector of an algebraic codebook is
composed of a small number of pulses with an amplitude
of 1 and polarities ( + , -) , and the pulses (in this case,
excitation vector waveform candidates) are positioned
so as not to overlap each other.
For example, when the subframe length is 32 and the
number of pulses (= number of channels) is 4, the number
of pulses per channel is 32/4 = 8, and the channel 0 pulse
positions ici0[i0], channel 1 pulse positions icil[il],
channel 2 pulse positions ici2[i2], and channel 3 pulse
positions ici3[i3] are as shown below. Here, i0, i1, i2,
and i3 denote indexes of the respective channels.
ici0[i0] = {0, 4, 8, 12, 16, 20, 24, 28}
ici1[i1] = {1, 5, 9, 13, 17, 21, 25, 29}
ici2[i2] = {2, 6, 10, .14, 18, 22, 26, 30}
ici3[i3] = {3, 7, 11, 15, 19, 23, 27, 31}
A conventional stochastic codebook codes the pulse
positions of each channel independently, and takes codes
combining these with polarity codes as stochastic
excitation vector codes.
For example, in the above case of a subframe length
of 32 and 4 channels, a conventional codebook 103

represents a pulse position of each channel as 3 bits,
and together with the polarity code, performs coding using
a code of (3+l)x4=16 bits.
However, a problem with the above conventional
stochastic codebook coding method is that, if the bit
rate is low the bits assigned to each channel are also
limited, and there are positions where there is no pulse
at all, so that variations of an excitation vector waveform
corresponding to a code (position information) decrease,
and sound quality degradation occurs.
In the above case of a subframe length of 32 and
4 channels, for example, there are positions where there
is no pulse at all if coding is performed with fewer than
16 bits.
Disclosure of Invention
It is an object of the present invention to provide
a stochastic codebook excitation vector coding method
that enables variations to be secured so that there are
no positions where there is no pulse at all while achieving
a reduction of the number of bits used when coding
stochastic codebook pulses.
This object is achieved by associating a pulse
position of a predetermined channel with a pulse position
of another channel, searching for a pulse position by
means of a predetermined algorithm, and taking a found
pulse position code and a polarity code as a stochastic
excitation vector code.

Brief Description of Drawings
FIG.1 is a block diagram showing the configuration
of a CELP speech coding apparatus;
FIG.2 is a flowchart showing an example of a pulse
search algorithm for each channel in a coding method
according to Embodiment 1 of the present invention;
FIG. 3 is a flowchart showing an example of a pulse
search algorithm for each channel in a coding method
according to Embodiment 1 of the present invention;
FIG. 4 is a flowchart showing an example of a pulse
search algorithm for each channel in a coding method
according to Embodiment 2 of the present invention; and
FIG. 5 is a flowchart showing an example of a pulse
search algorithm for each channel in a coding method
according to Embodiment 2 of the present invention.
Best Mode for Carrying out the Invention
FIG.l is a block diagram showing the configuration
of a CELP speech coding apparatus. An input speech signal
is input sequentially to the speech coding apparatus
divided into processing frames at time intervals of
approximately 20 ms.
The input speech signal input to the speech coding
apparatus every processing frame is first supplied to
an LPC analysis section 101. LPC analysis section 101
performs LPC (Linear Predictive Coding) of the input
speech signal and obtains an LPC coefficient, performs

vector quantization of the LPC coefficient to produce
an LPC code, and decodes this LPC code to obtain a decoded
LPC coefficient.
An excitation vector creation section 104 reads an
adaptive code vector and fixed code vector respectively
from an adaptive codebook 102 and stochastic codebook
103, and sends these to an LPC combining section 105.
LPC combining section 105 performs combining filtering
of the adaptive code vector and fixed code vector supplied
from excitation vector creation section 104, and the
decoded LPC coefficient provided from LPC analysis
section 101, with an all pole type combining filter in
the filter coefficient, and obtains a combined adaptive
code vector and combined fixed code vector.
A comparison section 106 analyzes the relationship
between the combined adaptive code vector and combined
fixed code vector output from LPC combining section 105,
and finds adaptive codebook optimum gain to be multiplied
by the combined adaptive code vector, and stochastic
codebook optimum gain to be multiplied by the combined
fixed code vector.
Comparison section 106 also adds together the vector
obtained by multiplying the combined adaptive code vector
by the adaptive codebook optimum gain and the vector
obtained by multiplying the combined fixed code vector
by the stochastic codebook optimum gain, and obtains a
combined speech vector, and performs a distance
calculation on the combined speech and input speech signal .

Then comparison section 106 obtains the adaptive code
vector stored by adaptive codebook 102 and the combined
speech vector stored by stochastic codebook 103, and finds
the adaptive code vector index and fixed code vector index
for which the distance between the combined speech and
input speech signal is smallest. Comparison section 106
then sends the indexes of the code vectors output from
the codebooks, the code vectors corresponding to the
respective indexes, and the adaptive codebook optimum
gain and stochastic codebook optimum gain, to a parameter
coding section 107.
Parameter coding section 107 codes the adaptive
codebook optimum gain and stochastic codebook optimum
gain and obtains a gain code, and outputs the gain code,
the LPC coefficient provided by LPC analysis section 101,
and the indexes of each codebook together for each
processing frame.
Parameter coding section 107 also adds together the
two vectors comprising the vector obtained by multiplying
the adaptive code vector corresponding to the adaptive
codebook index by the adaptive codebook gain
corresponding to the gain code, and the vector obtained
by multiplying the fixed code vector corresponding to
the stochastic codebook index by the stochastic codebook
gain corresponding to the gain code, and obtains a drive
excitation vector, and updates the old adaptive code
vector in adaptive codebook 102 with the drive excitation
vector.

Combining filtering by LPC combining section 105
generally makes combined use of a linear predictive
coefficient, a high emphasis filter, and a weighting
filter that uses a long-term predictive coefficient
obtained by long-term predictive analysis of input
speech.
Adaptive codebook and stochastic codebook optimum
index searches, optimum gain calculation, and optimum
gain coding processing are generally carried out in
sub frame units resulting from further division of a frame.
In a speech decoding apparatus (decoder), the same
configuration of LPC analysis section 101, adaptive
codebook 102, stochastic codebook 103, excitation vector
creation section 104, and LPC combining section 105 is
provided as shown in FIG.1, and an excitation vector
waveform is obtained by decoding codes transmitted from
a speech coding apparatus .
In order to reduce the amount of calculation,
comparison section 106 usually searches for an adaptive
codebook 102 excitation vector and stochastic codebook
103 excitation vector by means of an open-loop procedure.
This open-loop search procedure is described below.
(1) First, excitation vector creation section 104
chooses excitation vector candidates (adaptive
excitation vectors) in succession from adaptive codebook
102 only, LPC combining section 105 creates a composite
tone, and comparison section 106 carries out a comparison
of the input speech and composite tone and selects the

optimum adaptive codebook 102 code. At this time, gain
is selected on the assumption that it is the value at
which coding distortion is minimal (optimum gain).
(2) Next, the above-described adaptive codebook
code is fixed, excitation vector creation section 104
successively selects the same excitation vector from
adaptive codebook 102 and stochastic codebook 103
successively selects the excitation vector (stochastic
excitation vector) corresponding to the comparison
section 106 code, LPC combining section 105 generates
composite tones, and comparison section 106 compares the
sum of both composite tones with the input speech and
determines the optimum stochastic codebook 103 code. As
in (1) above, gain is selected at this time on the
assumption that it is the value at which coding distortion
is minimal (optimum gain).
Use of the above procedure to search for the optimum
excitation vector results in a slight degradation of
coding capability, but also a major reduction in the amount
of calculation, compared with the method of searching
for the optimum excitation vector by comparing
combinations of all excitation vectors or both codebooks .
The stochastic codebook 103 excitation vector
search method will now be described in detail.
Excitation vector code derivation is carried out
by searching for the excitation vector that minimizes
coding distortion E in Equation (1) below. In Equation
(1) , x denotes the coding target; p, adaptive excitation

vector gain; H, a weighting combining filter; a, an
adaptive excitation vector; q, stochastic excitation
vector gain; and s, a stochastic excitation vector.

As the adaptive excitation vector search is
performed by means of an open-loop procedure, stochastic
codebook 103 code derivation is performed by searching
for the excitation vector that minimizes coding
distortion E in Equations (2) below. In Equations (2),
y denotes the stochastic excitation vector search target
vector.

Here, gain values p and q are determined after the
excitation vector search, and by making gain p = gain
q = 1, Equations (2) above can be written as Equations
(3) below.

Minimi zing this distortion expression is equivalent
to maximizing function C in Equation (4) below.


Therefore, in the case of a search for an excitation
vector composed of a small number of pulses such as an
algebraic codebook excitation vector, calculating yH and
HH beforehand enables function C above to be found with
a small amount of calculation.
yH can be found by reversing the order of vector
y and convoluting matrix H, and then reversing the order
of the result, and HH can be found by multiplication of
the matrices.
Stochastic codebook 103 searches for and codes a
stochastic excitation vector using the procedure
described in (1) through (4) below.
(1) First, as preliminary processing, vector yH and
matrix HH are found.
(2) Next, pulse polarities are determined from the
polarities (+ -) of vector yH elements. Specifically,
the polarity of the pulse at each position is matched
to the value of that position in yH, and the polarity
of the yH value is stored in another array. After the
polarities of all positions have been stored in another
array, yH values are all made absolute values and converted
to positive values. HH values are also converted in
accordance with these polarities by performing polarity
multiplication.
(3) Next, function C shown in Equation (4) is found

by adding yH and HH values using an n-fold loop (where
n is the number of channels), and the pulse positions
of the channels at which this value is largest are found.
(4 ) The found pulse position of each channel is coded,
and a code combining this with a polarity code is taken
as the stochastic excitation vector code.
With reference now to the accompanying drawings,
stochastic codebook excitation vector coding methods
according to embodiments of the present invention will
be explained in detail below. In the descriptions of
these embodiments, an algebraic codebook is used for which
the subframe length is 32 and the number of pulses (=
number of channels) is 4.
(Embodiment 1)
In Embodiment 1, a case is described in which an
index of a predetermined channel is changed in accordance
with another channel.
In this embodiment, channel 0 pulse positions
ici0[i0], channel 1 pulse positions icil[jl], channel
2 pulse positions ici2 [j2], and channel 3 pulse positions
ici3[j3] are as shown below.
iciO[i0] = {0, 4, 8, 12, 16, 20, 24, 28}
icil[j1] = {1, 5, 9, 13, 17, 21, 25, 29}
ici2[j2] = {2, 6, 10, 14, 18, 22, 26, 30}
ici3[j3] = {3, 7, 11, 15, 19, 23, 27, 31}
Here, i0 (0 (0
index of channel 2 , and j 3 (0 3.
For example, the i0=0 pulse position is {0}, the
i0 = 1 pulse position is {4}, and so on; and the j1 = 0 pulse
position is {1}, the j1=1 pulse position is {5}, and so
on .
Channel 1, channel 2, and channel 3 pulses are
grouped into pairs. For example, for channel 1, pulses
are grouped into group 0 {1, 5}, group 1 {9, 13}, group
2 {17, 21}, and group 3 {25, 29}.
Then, if i1 (0 group index, i2 (0 index, and i3 (0 index, the relationship between indexes j1, j2, and j3
and group indexes i1, i2, and i3 is as shown in Equations
(5) below.

InEquations (5), the "%" symbol denotes an operation
that finds the remainder when the numeric value on the
left of "%" (index) is divided by the numeric value on
the right. If indexes iO through i3 are expressed as
binary numbers, the "%" operation can be implemented
simply by checking the code of the least significant bit
of the index on the left.
In this embodiment, as shown in Equations (5) above,

the indexes of channels 1 through 3 are changed according
to the index of another channel. For example, index j1
of channel 1 changes according to index iO of channel
0, so that ici1[jl] = {1, 9, 17, 25,} when iO = 0, and
icil[j1] = {5, 13, 21, 29} when iO = 1.
FIG.2 and FIG.3 are flowcharts showing an example
of a pulse search algorithm for each channel in a coding
method according to this embodiment.
In FIG.2 and FIG.3, loop 0 is a loop in which iO
is changed from 0 through 7, loop 1 is a loop in which
i1 is changed from 0 through 3, loop 2 is a loop in which
i2 is changed from 0 through 3, and loop 3 is a loop in
which i3 is changed from 0 through 3.
In FIG.2 and FIG.3, first, i0, i1, and i2 are fixed
at 0, and as the first stage, y and H in each i3 are
calculated in loop 3, and maximum values ymax and Hmax
thereamong, and iO, i1, i2, and i3 at that time are stored
as ii0, ii1, ii2, and ii3 respectively. In this case,
the channel pulse positions searched for are ici3[j3]
= {3, 11, 19, 27 } .
Next, as the second stage, i2 is incremented in loop
2, and the above first-stage computations are performed
for each i2. When iO = 0, i1 = 0, and i2 = 1, the channel
3 pulse positions searched for in the first stage are
ici3[j3] = {7, 15, 23, 31}. Thus, the channel 3 pulse
positions searched for in the first stage change according
to the values of iO, i1, and i2.
Then, as the third stage, i1 is incremented in loop

1, and the above first-stage and second-stage
computations are performed for each i1. In this case,
the channel 2 pulse positions searched for in the second
stage change according to the values of i0 and i1.
Lastly, as the fourth stage, i0 is incremented in
loop 0, and the above first-stage, second-stage, and
third-stage computations are performed for each iO. In
this case, the channel 1 pulse positions searched for
in the third stage change according to the value of iO.
Thus, in this embodiment, using an n-fold loop search
algorithm (where n is the number of channels), internal
loop candidate positions are changed according to
loop-external codes.
Then ii0, ii1, ii2, and ii3 are found for which y
and H are largest at all pulse positions searched for.
As a result, ii0 is 3 bits and ii1, ii2, and ii3
are 2 bits each, so that pulse position coding can be
performed in 9 bits, and together with the polarity codes
of each channel (1 bit x 4 channels), coding can be
performed with a 13-bit code. Therefore, compared with
the conventional method, the number of bits necessary
for coding can be reduced, and a lower bit rate can be
achieved.
Meanwhile, 8 locations are possible respectively
for indexes j1, j2, and j3 of channels 1 through 3, and
therefore there are no positions where there is no pulse
at all in a subframe, variations of excitation vector
waveforms corresponding to codes (position information)

can be secured, and sound quality degradation can be
prevented.
Thus, according to this embodiment, pulse positions
of a predetermined channel are associated with pulse
positions of another channel by changing the
predetermined channel index in accordance with another
channel. As a result, a stochastic excitation vector can
be represented by fewer bits than heretofore, and
variations can be secured so that there are no positions
where there is no pulse at all.
(Embodiment 2)
In Embodiment 2, a case is described in which the
pulse positions themselves of a predetermined channel
are changed in accordance with another channel.
In this embodiment, channel 0 pulse positions
ici0[i0], channel 1 pulse positions icil[il], channel
2 pulse positions ici2 [i2], and channel 3 pulse positions
ici3[i3] are as shown below.
ici0[i0] = {4, 7, 12, 15, 20, 23, 28, 31}
ici1[i1] = {0, 8, 16, 24}
ici2[i2] = {2, 10, 18, 26}
ici3[i3] = {5, 13, 21, 29}
Here, iO (0 (0 index of channel 2, and i3 (0 3.
For example, the i0=0 pulse position is {4}, the

i0 = 1 pulse position is {7}, and so on; and the i1 = 0 pulse
position is {0}, the i1=1 pulse position is {8}, and so
on .
Then channel pulse positions ici0[i0], ici1[i1],
ici2[i2], and ici3[i3] are adjusted to kO, k1, k2, and
k3 with indexes i0, i1, i2, and i3 by means of Equations
(6) below.
k 0 = i c i 0 [ i 0 ]
k 1 = i c i 1 [ i 1 ] X2+ ( i 0 % 2 )
k2=ici0 [ i 2 ] X2+ (( i 0 + i 1 ) % 2 )
k3=ici0 [13] X2+ (( i 1 + i 2 ) % 2 )
... Equation (6)
InEquations (6), the "%" symbol denotes an operation
that finds the remainder when the numeric value on the
left of "%" (index) is divided by the numeric value on
the right.
In thi s embodiment, as shown in Equations (6) above,
the pulse positions themselves of channels 1 through 3
are changed according to another channel. As a result,
adjusted pulse positions k0, k1, k2, and k3 of channels
0 through 3 are as shown below.
kO = {4, 7, 12, 15, 20, 23, 28, 31}
k1 = {0, 1, 8, 9, 16, 17, 24, 25}
k2 = {2, 3, 10, 11, 18, 19, 26, 27}
k3 = {5, 6, 13, 14, 21, 22, 29, 30}
FIG. 4 and FIG.5 are flowcharts showing an example
of a pulse search algorithm for each channel in a coding
method according to this embodiment.

In FIG.4 and FIG.5, loop 0 is a loop in which iO
is changed from 0 through 7, loop 1 is a loop in which
i1 is changed from 0 through 3, loop 2 is a loop in which
i2 is changed from 0 through 3, and loop 3 is a loop in
which i3 is changed from 0 through 3.
In FIG.4 and FIG.5, first, iO, i1, and i2 are fixed
at 0, and as the first stage, y and H in each i3 are
calculated in loop 3, and maximum values ymax and Hmax
thereamong, and iO, il, i2, and i3 at that time are stored
as iiO, ii1, ii2, and ii3 respectively.
Next, as the second stage, i2 is incremented in loop
2, and the above first-stage computations are performed
for each i2 .
Then, as the third stage, i1 is increased in loop
1, and the above first-stage and second-stage
computations are performed for each il.
Lastly, as the fourth stage, iO is increased in loop
0, the above first-stage, second-stage, and third-stage
computations are performed for each iO, and iiO, ii1,
ii2, and ii3 are found for which y and H are largest at
all pulse positions searched for.
As a result, iiO is 3 bits and iil, ii2, and ii3
are 2 bits each, so that pulse position coding can be
performed in 9 bits, and together with the polarity codes
of each channel (1 bit x 4 channels), coding can be
performed with a 13-bit code. Therefore, compared with
the conventional method, the number of bits necessary
for coding can be reduced, and a lower bit rate can be

achieved.
Meanwhile, 8 locations are possible respectively
for the adjusted pulse positions (k1, k2, and k3) of
channels 1 through 3, and therefore there are no positions
where there is no pulse at all in a subframe, variations
of excitation vector waveforms corresponding to codes
(position information) can be secured, and sound quality
degradation can be prevented.
Thus, according to this embodiment, by changing the
pulse positions of a predetermined channel in accordance
with another channel, a stochastic excitation vector can
be represented by fewer bits than heretofore, and
variations can be secured so that there are no positions
where there is no pulse at all.
In a stochastic codebook provided in a speech
decoding apparatus, a stochastic excitation vector
searched for by a speech coding apparatus can be found
by performing computations by means of an above-described
search algorithm on codes of each channel coded and
transmitted in an above-described embodiment.
In the above embodiments, a 2's remainder is found
as variations are assumed to be 2-fold, but the present
invention is not limited to this, and is also effective
in a case where the numeric value for which a remainder
is found is made larger, to 3 or more, in order to achieve
a still lower bit rate and extended subframe length.
Also, in the above embodiments, information of a
plurality of channels is integrated by means of addition,

but the present invention is not limited to this, and
is also effective in a case where a more sophisticated
function, such as weighted addition (addition with
multiplication by a constant) or a random number generator,
is used.
Furthermore, in the above embodiments, a value
reflecting information of another channel is extracted
by means of multiplication, but the present invention
is not limited to this, and is also effective in a case
where a more sophisticated function is used, such as when
a random number generator or conversion table is used.
Moreover, in the above embodiments, a case has been
described in which an algebraic codebook is used and an
impulse position corresponds to a code, but the present
invention is not limited to this, and is also effective
in a case where a stochastic codebook is composed of sums
of partial waveforms, and the starting position thereof
corresponds to a code.
Also, in the above embodiments, a case has been
described in which an algebraic codebook is used and an
impulse position corresponds to a code, but the present
invention is not limited to this, and is also effective
in a case where a stochastic codebook is composed of a
multiplicity of fixed waveforms stored in ROM, and an
excitation vector waveform is created by the sum of a
plurality thereof, and that waveform number corresponds
to a code. In this case, the present invention can be
applied easily by replacing "position" with "waveform

number."
As is clear from the above description, according
to the present invention, by performing coding with a
pulse position of a predetermined channel associated with
a pulse position of another channel, and taking a code
combining this and a polarity code as a stochastic codebook
excitation vector code, it is possible to represent a
stochastic excitation vector with fewer bits than
heretofore, and to secure variations so that there are
no positions where there is no pulse at all.
This application is based on Japanese Patent
Application No.2002-330768 filed on November 14, 2002,
the entire content of which is expressly incorporated
by reference herein.
Industrial Applicability
The present invention is applicable to a CELP speech
coding apparatus/speech decoding apparatus.

WE CLAIM:
1. A coding method of an excitation vector of a stochastic codebook used in a
speech coding apparatus that is divided into a plurality of channels, the coding
method comprising: associating an excitation vector waveform candidate of a
predetermined channel with an excitation vector waveform candidate of another
channel, such that the excitation vector waveform candidate of the
predetermined channel changes in association with a change of a number
representing the excitation vector waveform candidate of the another channel;
searching for an excitation vector waveform that minimizes coding distortion
using the associated excitation vector waveform candidate of the predetermined
channel and the excitation vector waveform candidate of the another channel;
and
determining a code of the excitation vector of the stochastic codebook using a
code of the excitation vector waveform obtained by the searching, wherein:

the searching, after the associating, calculates a function value using the number
representing the changed excitation vector waveform candidate of the another
channel and the excitation vector waveform candidate of the predetermined
channel changed based on the associating, and, by the function value, finds an
excitation vector waveform candidate of each channel that minimizes the coding
distortion; and
the determining finds the code of the excitation vector waveform by coding the
excitation vector waveform candidate of each channel that minimizes the coding
distortion as the excitation vector waveform, and determines the code of the
excitation vector of the stochastic codebook using the code of the excitation
vector waveform.
2. The coding method as claimed in claim 1, wherein:
the searching searches for the excitation vector waveform by a loop calculation
of n-fold loops, multiplexed a number of times corresponding to a number of
channels n, and repeats the associating predetermined times to change the
excitation vector waveform candidate of the predetermined channel by

changing the number representing the excitation vector waveform candidate of
the another channel, and
the loop calculation changes the number representing the excitation vector
waveform candidate of the another channel by a predetermined loop, changing
the excitation vector waveform of the predetermined channel by a loop within
the predetermined loop.
3. The coding method as claimed in claim 1, wherein the stochastic codebook
comprises an algebraic codebook, and the excitation vector waveform candidate
is represented by a pulse position.
4. The coding method as claimed in claim 1, wherein the associating associates
the excitation vector waveform candidate of the predetermined channel with a
remainder operation result using the number representing the excitation vector
waveform candidate of the another channel.

5. A speech coding apparatus that codes an excitation vector of a stochastic
codebook in a coding method as claimed in claim 1.

Documents:

903-KOLNP-2005-ABSTRACT 1.1.pdf

903-kolnp-2005-abstract.pdf

903-KOLNP-2005-CANCELLED PAGES.pdf

903-KOLNP-2005-CLAIMS 1.1.pdf

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903-KOLNP-2005-CORRESPONDENCE 1.1.pdf

903-kolnp-2005-correspondence.pdf

903-KOLNP-2005-DESCRIPTION (COMPLETE) 1.1.pdf

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903-KOLNP-2005-EXAMINATION REPORT REPLY RECIEVED 1.1.pdf

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903-kolnp-2005-form 1.pdf

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903-kolnp-2005-form 13.2.pdf

903-KOLNP-2005-FORM 13.pdf

903-kolnp-2005-form 18.1.pdf

903-kolnp-2005-form 18.pdf

903-KOLNP-2005-FORM 2 1.1.pdf

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903-kolnp-2005-form 2.pdf

903-kolnp-2005-form 26.pdf

903-kolnp-2005-form 3.1.pdf

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903-KOLNP-2005-GPA.pdf

903-kolnp-2005-gpa1.1.pdf

903-kolnp-2005-granted-abstract.pdf

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903-kolnp-2005-granted-specification.pdf

903-KOLNP-2005-OTHERS.pdf

903-kolnp-2005-others1.1.pdf

903-KOLNP-2005-PA.pdf

903-KOLNP-2005-PETITION UNDER RULE 137.pdf

903-KOLNP-2005-PRIORITY DOCUMENT.pdf

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903-KOLNP-2005-REPLY TO EXAMINATION REPORT.pdf

903-kolnp-2005-reply to examination report1.1.pdf

903-kolnp-2005-specification.pdf

903-KOLNP-2005-TRANSLATED COPY OF PRIORITY DOCUMENT 1.1.pdf

903-kolnp-2005-translated copy of priority document.pdf


Patent Number 246634
Indian Patent Application Number 903/KOLNP/2005
PG Journal Number 10/2011
Publication Date 11-Mar-2011
Grant Date 08-Mar-2011
Date of Filing 17-May-2005
Name of Patentee PANASONIC CORPORATION
Applicant Address 1006, OAZA KADOMA, KADOMA-SHI, OSAKA
Inventors:
# Inventor's Name Inventor's Address
1 TOSHIYUKI MORII 3-1-12-304, NIJIGAOKA, ASAO-KU, KAWASAKI-SHI, KANAGAWA 215-0015
PCT International Classification Number G01L 19/12
PCT International Application Number PCT/JP2003/014298
PCT International Filing date 2003-11-11
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 2002-330768 2002-11-14 Japan