Note: Descriptions are shown in the official language in which they were submitted.
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SPECIFICATION
TITILE OF THE INVENTION
SPEECH CODING APPARATUS
BACKGROUND OF THE INVENTION
Field of the Invention
This invention relates to a speech coding systems, and
more particularly, to a speech coding apparatus for encoding
a speech signal in a high quality at a low bit rate,
espec~ially at 8-4 kb/s.
Related Art
Recently it has been of urgent necessity to implement
a digitalized system of such devices as an automotive mobile
phone or a codeless phone employing a radio communication.
Since an available frequency band is narrow in a radio
communication, it is important to develop a system in which
r
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a speech signal is coded very efficiently in a high quality
conditlon at a low bit rate by compressing the speech signal
into smaller number of bits.
CELP(Code Excited LPC Coding) as described in a paper
titled "Code-excited linear prediction: High quality speech
at low bit rates" by M. Schroeder and B. S. Atal(ICASSP
Proc. 85, pp. 937-940, 1985; hereinafter referred to as the
"reference No. 1") is known as a coding system in which a
speech signal is coded at a low bit rate of 8-4 kb/s.
In this method, an encoding process is carried out at
a transmission s-ide in the following procedure. First, for
every frame (for example, 20 ms), spectrum parameters
representing frequency characteristics of the speech signal
are extracted(short-term prediction).
Then each frame is subdivided into narrower subframes
(for example, 5 ms). In every subframe, a pitch parameter
representing a wide interval correlation(pitch correlation)
is extracted from past speech source signals and the long-
term prediction of a speech signal in the subframe i,s
carried out with the pitch parameter.
Next, a code vector and a gain which minimize the
error power between a synthesized signal generated using the
code vector extracted from a noise signal (code vector)
which is composed of pre-prepared types of quantization
codes, and a residual signal obtained by the long-term
/ T ~ i
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prediction, are decided. The index representing the type of
the decided -code vector, the decided gain, the spectrum
parameter, and the pitch parameter are transmitted.
More specifically, in search of a quantization code
the following procedure is employed. First, a signal z[n] is
derived by executing a weighting for compensation of an
auditory sense to, and subtraction of a past influence
signal from, an inputted speech signal x[n].
Next, a synthesized signal Hej[n] is calculated by
driving with a code vector ej[n] of a quantization code j, a
synthesis filter H composed of spectrum parameters, obtained
by the short-term prediction, quantized, and inversely
quantized.
Then, a quantization code j which minimizes Ej
representing an error energy between the signal z[n] and the
synthesized signal Hej[n], as defined in the following
expression, is obtained.
Ns-l 2 (1)
E j= ~ (z[n]- H ej[n] )
n=0
In above expression (1), Ns indicates the length of
the subframe and H indicates a matrix implementing the
synthesis filter. For a practical use, the expression (1) is
expanded as follows,
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Ns-l 2 C i (2)
E j= ~ z[n] -
n=O G j
A numerator Cj in the second term in the above
expression (2) is a cross-correlation and a denominator Gj
is an auto-correlation, and they are calculated with
following expressions (3) and (4) respectively.
Ns-l
C j= s z[n]- H ej[n] (3)
n=O
Ns-l 2 (4)
G j= ~ ( H ej[n])
n=O
The above auto-correlation and cross-correlation are
calculated after Hej[n] is calculated by driving the
synthesis filter (i.e. filtering). In this case, the number
of filtering operations carried out is equal to the size of
a code book. Therefore, the quantity of operations, that is,
the number of times of product and sum operations(multiply
and add operations) for processing one frame becomes vast as
seen from the following expression,
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(M- N+N+N)- 2 (5)
where M denotes an order of the synthesis filter, N
denotes a length of the frame, and B denotes the number of
bits of the speech source.
5A method for calculating a cross-correlation with an
inverse filtering and calculatlng an auto-correlation with
an auto-correlation approximation method, as described in a
paper titled "EFFICIENT PROCEDURES FOR FINDING THE OPTIMUM
INNOVATION IN STOCASTIC CODERS" by I. M. Transco and B. S.
10Atal (ICASSP Proc., p. 2375, 1986; hereinafter referred to
as the "reference No. 2") is well known as the method to
obtain a code with the reduced quantity of operations.
In this method, a cross-correlation and an auto-
correlation are derived as follows. In case of calculating
15the cross-correlation, a value given by the following
expression is calculated at first. This process is referred
to as an inverse filtering.
H z[n]= ~ h[i- n]- z[i] (6)
i=n
In the above expression (6), h[n] represents an
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impulse response of the synthesis filter.
The cross-correlation is calculated with the following
-expression using the value obtained from the above
expression (6).
C j= ~ H z[n] ej[n] (7)
n=O
In this case, the filtering process is carried out
only once in calculating the impulse response of the
synthesis filter and in the above expression (6) so that the
quantity of product and sum operations in each frame for
calculating the cross-correlation is given by the following
expression (8),
M I- sf+ (N - I+ l)- I- sf - I- (I+ l)- sf+ N 2
(8)
where sf denotes the number of the subframes in a frame.
The auto-correlation function is calculated with the
following approximation expression (9) as described in the
reference No.2,
G j= hh[O] R j[O]+ 2 ~ hh[i] R j[i] (9)
i =O
r l
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where hh[i] indicates an ith order auto-correlation
funct1on of the impulse response of the synthesis filter,
Rj[i] indicates an ith order auto-correlation function of
the code vector ej[n], and I indicates the order of the
impulse response of the synthesis filter.
The order I is-usual-ly set to a value of 21 or so in
consideration of an attenuation of the impulse response of
the synthesis filter. A transfer function of the synthesis
filter is generally represented as an all-pole type 1/A(Z),
however it is approximated with an impulse response of
limited order (for example, 21) to reduce the quantity of
operations.
By calculating beforehand an auto-correlation function
of the impulse response and storing it in a data ROM for
every speech source, the auto-correlation function may be
calculated with a smaller quantity of operations without
filtering process. In this method, the auto-correlation is
calculated with a quantity of product and sum operations as
expressed in the following expression.
. B (10)
I ( I + 1 ) sf+ I 2 sf
Accordingly, with the above expressions (7) and (9),
the quantity of product and sum operations is given by the
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following expression (11).
M I; sf+ (N - I+ 1) I- sf+ - I- (I+ 1) sf+ N 2
+ - I- (I+ 1)- sf+ I- 2 B- sf (11)
Under the condition that the length of the frame
N=240, the length of the subframe N9=60, the number of the
subframes sf=4, the length of the impulse response I=21, the
order of the synthesis filtering M=10, and the size of the
code book B=7 (bits), the quantity of product and sum
operations by the conventional method given as the above
expression (5) and the quantity of product and sum
operations by the approximation method described in the
reference No. 2 in which the quantities of product and sum
operations of the cross-correlation and the auto-correlation
are given by the above expressions (8) and (10)
respectively, are given as those listed in Table 1:
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Table 1
Comparison of the quantity of product and sum operations
Quantity of
Method Expression product and
sum operations
Filtering for
each code vector expression(5) 12.288(MOPS)
Approximation expression(8)+
method in the expression(l0) 1.584(MOPS)
reference No.2
In above Table 1, MOPS (Million Operations Per Second)
indicates a quantity of product and sum operations per
second (unit is one million).
As may be seen from Table 1, the approximation method
described in the reference No.2 fairly reduces the quantity
of product and sum operations as compared with the
conventional method (i.e. by nearly one order of magnitude).
However, with the above described approximation method
there still remains a large quantity of operations even
after the reduction of operations, so that only limited
types of processors such as those having a large
computational power may carry out such large quantity of
operations in a real time processing environment.
In addition, the above described approximation method
reduces the quantity of operations in case of searching for
the speech source code book in the data ROM which contains
. s l~
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the auto-correlation functions of the speech sources,
-however, the additional number of product and sum operations
given by the following expression is needed in case of
searching for a code book, such as an adaptive code book, in
which a speech source varies by every subframe to be coded,
- so that the auto-correlation function must be calculated for
.
each code.
( N s I - - I ( I - 1 ) ) 2 sf (12)
Under the same condition as that employed in Table 1,
the above expression (12) gives a value of 17.92 (MOPS) and
a larger quantity of operations are needed than in the
conventional method in which the filtering is carried out
for each code vector. As a result thereof, the
approximation method described in the reference No.2 cannot
be employed and it is difficult to carry out operations in a
real time processing.
SUMMARY OF THE INVNETION
.In view of the above-mentioned drawbacks of the prior
art techniques, it is an object of the present invention to
provide a speech coding system with a good tone quality with
a smaller quantity of operations even at 4 kb/s.
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For accomplishing the above described object, the
present invention provides a speech coding apparatus
comprising:
a speech analyzing unit for deciding, in every
predetermined interval of a spee-ch signal, codes of short-
term .prediction parameters representing frequency
characteristics of the speech signal,
an impulse response calculating unit for calculating
an impulse response of a speech synthesis filter generated
with the short-term prediction parameters,
an inverse filter unit for filtering the speech signal
inversely with the impulse response,
an adaptive code book for storing an input signal fed
to the speech synthesis filter generated within a past
speech coding interval,
a long-term prediction speech source for generating
from the adaptive code book a long-term prediction source
representing a pitch correlation of the speech signal,
a cross-correlation calculating unit for calculating a
cross-correlation between the speech signal and an output
signal of the speech synthesis filter fed with said long-
term prediction speech source as an input,
an auto-correlation calculating unit of an impulse
response for calculating an auto-correlation of the impulse
response of the speech synthesis filter to an order of
,; ,1
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Ismall being less than a length of said impulse response,
. an auto-correlation calculation unit of long-term
predictlon speech source for calculating an auto-correlation
of the long-term prediction speech source to the order
Ismall less than the length of said impulse response,
an auto-correlation .calculating unit for calculating
an auto-correlation of said output signal to the order
Ismall less than the length of said impulse response from
two types of said auto-correlation function,
an evaluation function calculating unit for
calculating error energy with results of said auto-
correlation and said cross-correlation,
an optimum code deciding unit for deciding an optimum
long-term prediction code with said evaluation function,
a speech source code book comprising speech source
signals and quantization codes indicating residual signals
after the long-term prediction, and
a speech source code book searching unit for deciding
an optimum quantization code from said speech source code
book.
One of the features of the present invention is that
the auto-correlations are calculated with an auto-
correlation function approximation order set to a value of
an Ismall being less than the length of the impulse
response of the synthesis filter.
f , ~
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The present invention in the second aspect provides a
speech coding apparatus comprising:
a speech analyzing unit for deciding, in every
predetermined interval of a speech signal, codes of short-
term prediction. parameters representing frequency
- characteristics of the speech signal,
an adaptive code book for storing an input signal fed
to a speech synthesis filter generated in a past speech
coding interval,
an adaptive code book searching unit for deciding an
optimum code from said adaptive code book,
an impulse response calculating unit for calculating
an impulse response of said speech synthesis filter
generated from said short-term prediction parameters,
an auto-correlation function calculating unit of an
impulse response for calculating an auto-correlation
function of the impulse response of said speech synthesis
filter to an order of Ismall less than the length of the
impulse response,
a speech source code book comprising speech source
signals and quantization codes indicating residual signals
after the long-term prediction,
a code vector generating unit for generating a code
vector from said speech source code book,
an auto-correlation function calculating unit of a
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code vector for obtaining an auto-correlation function of
said code vector to the order of Ismall less than the length
of said impulse response,
' .an inverse filter unit for inversely filtering said
5 'speech signal'with said impulse responses,
a cross-correlation calculating unit for calculating a
cross-correlation between said spe'ech signal and an output
signal of said speech synthesis filter, with said code
vector being fed to said speech synthesis filter as an
input,
an auto-correlation calculating unit for calculating
an auto-correlation of said output signal to the order
Ismall less' than the length of said impulse response from
two types of said auto-correlation functions,
an evaluation function calculating unit for
calculating an error energy with said auto-correlation and
said cross-correlation, and
an optimum code deciding unit for deciding an optimum
code vector with said evaluation function.
The present invention in the third aspect provides a
speech coding apparatus comprising:
a speech analyzing unit for deciding in every
predetermined interval of a speech signal codes of short-
term prediction parameters representing frequency
characteristics of the speech signal,
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an- impulse response calculating unit for calculating
an im.pulse response of a speech synthesis filter generated
. with said short-term prediction parameters,
an inverse filter unit for inversely filtering said
speech signal with said impulse response,
an adaptive code book for storing an input signal fed
to said speech synthesis filter generated in a past speech
coding interval,
a long-term prediction speech source generating unit
for generating from said adaptive code book a long-term
prediction speech source representing a pitch correlation of
said speech signal,
a cross-correlation calculating unit for calculating a
cross-correlation between said speech signal and an output
signal of said speech synthesis filter with said long-term
prediction speech sources being fed to said speech synthesis
filter as an input,
an optimum code deciding unit for deciding an optimum
long-term prediction code based on said cross-correlation,
a speech source code book comprising speech source
signals and quantization codes indicating residual signals
after the long-term prediction, and
a speech source code book searching unit for deciding
an optimum quantization code with said speech source code
book.
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The present invention in the fourth aspect provides a
speech coding apparatus comprising: .
a speech analyzing unit for deciding in every
predetermined interval of a speech signal codes of short-
term prediction parameters - representing frequency
characteristics of the speech signal,
an adaptive code book for storing an input signal
fed to a speech synthesis filter generated in a past speech
coding interval,
an adaptive code book searching unit for deciding an
optimum code from said adaptive code book,
an impulse response calculating unit for calculating
an impulse response of said speech synthesis filter
generated with said short-term prediction parameters,
a speech source code book comprising speech source
signals and quantization codes indicating residual signals
after the long-term prediction,
a code vector generating unit for generating a code
vector from said speech source code book,
an inverse filter unit for inversely filtering said
speech signal with said impulse responses,
a cross-correlation calculating unit for calculating a
cross-correlation between said speech signal and an output
signal of said speech synthesis filter with said code
vectors being fed to said speech synthesis filter as an
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input, and
an optimum code deciding unit for deciding an optimum
code vector with said cross-correlation.
The present invention in the above first and second
aspects, provides a speech coding apparatus preferably
comprising an approximation order deciding unit for deciding
an order of Ismall for calculating an auto-correlation for
each interval of a speech signal to be coded.
According to the present invention, by using,
preferably in the CELP method, a value of the auto-
correlation approximation order of Ismall smaller than the
length of an impulse response of a synthesis filter I,
accomplishes the significant reduction in the quantity of
product and sum operations in a calculation of an auto-
correlation, reduces the quantity of product and sumoperations in an auto-correlation for each code, and also
prevents tone quality from being degraded.
In addition, the present invention quickly obtains an
auto-correlation function of a code vector by table lookup
of a speech source auto-correlation code book in which auto-
correlation values of a speech source code book are stored
beforehand, reduces the quantity of operations in a
calculation of an auto-correlation by using a value of an
approximation order of Ismall smaller than a length of an
impulse response, reduces the number of auto-correlation
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functions of impulse responses of a synthesis filter, and
reduces the memory capacity of a ROM in the speech source
auto-correlation code book.
Further, the present invention significantly reduces
the quantity of operations, as shown in the above Table 2,
by setting the auto-correlation approximation order Ismall
to 1 and representing an evaluation function only by cross-
correlations without degradation of tone quality.
Furthermore, the present invention provides a speech
coding apparatus which reduces the quantity of product and
sum operations for an auto-correlation and efficiently
prevents tone quality from being degraded by variably
controlling, according to the characteristics of coded
speech signals, the auto-correlation approximation order
Ismall with an approximation order deciding circuit.
In the above described auto-correlation approximation
method of the prior art example, the approximation order is
set to I being equal to the length of the impulse response
of the synthesis filter.
The present invention has been developed based on the
knowledge by the present inventors that it is not needed to
match the approximation order to the length of the impulse
response of the synthesis filter I and that the auto-
correlation may well be approximated with good accuracy even
by a very small value Ismall.
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.
i9
That is, with the present invention, by setting the
approximation order of an auto-correlation to Ismall less
- than the length of the impulse response of the synthesis
filter I, the quantities of operations required for
- calculating an auto-correlation function of the speech
-source and the impulse response and for calculating an auto-
correlation of the synthesized signal are reduced. In
addition, the present invention may reduce a memory
capacity required for calculating the auto-correlation
function of the speech source and the impulse response.
With the present invention the evaluation function may
be calculated only with the cross-correlation if the
approximation order Ismall is set to 1, so that the quantity
of product and sum operations for calculating the auto-
correlation may be reduced significantly.
Furthermore, with the present invention the
approximation order Ismall may be variably controlled
according to characteristics of the coded speech signal.
Brief Description of the Drawin~s
The above and other objects, features and advantages
of the present invention will be more apparent from the
following description taken in conjunction with the
accompanying drawings, in which
Fig. 1 is a block diagram showing a whole structure of
a speech coding and decoding apparatus of the present
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.
invention;
Fig.2 is a flow chart in operation of a circuit 160
according to a first embodiment of the present invention;
Fig.3 is a flow chart in operation of a circuit 180
-according to an embodiment of the present invention;
Fig.4 is a flow chart in operation of a circuit of 160
according to another embodiment of the present invention;
Fig. 5 is a flow chart in operation of a circuit 180
according to a still another embodiment of the present
invention;
Fig. 6 is a flow chart in operation of a circuit 160
according to still another embodiment of the present
invention; and
Fig.7 is a flow chart in operation of a circuit 160
according to a yet another fifth embodiment of the present
invention.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
Referring to the drawings, preferred embodiments of
the present invention will be described in detail.
Fig. 1 is a schematic diagram showing a speech coding
and decoding apparatus according to the present invention.
In Fig. 1, a component (1) shown in the left side and a
component (2) shown in right side represent a coding circuit
(encoder) and a decoding circuit (decoder) respectively.
First, each component module is explained in the below.
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21
An input terminal 100 is an speech input terminal of
an encoder. A buffer circuit 110 is a circuit for storing a
speech signal. An LPC analyzing circuit 120 is a circuit for
extracting an LPC coefficie-nt, that is, a spectrum parameter
of the speech signal. A parameter quantization circuit 130
is a circuit for quantizing the LPC coefficient. A weighting
circuit 140 is a circuit for weighting to the speech signal
for compensating an auditory sense. An adaptive code book
150 is a circuit for storing past speech sources. An
adaptive code book searching circuit 160 is a circuit for
searching for a long-term prediction parameter.
A speech source code book 170 is a code book in which
code vectors representing long-term prediction residuals,
the length of which is equal to the length of subframes, are
being stored. This book 170 may be either a noise code book
or a learning code book in which learning is made by a
vector quantization (VQ) algorithm. The former has been
disclosed in detail in the reference No.1, while the latter
has been proposed in Japanese Patent Kokai JP-A Nos. Hei 3-
243998(1991), Hei 3-243999(1991) by one of the inventors of
the present invention.
A speech source code book searching circuit 180 is a
circuit for deciding an optimum code vector from the speech
source code book 170. A gain code book 190 is a code book in
which long-term prediction speech sources and parameters
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22
representing gain- terms in the code vector are stored. A
gain code book searching circuit 200 is a circuit for
deciding a long-term prediction speech source and a
quantlzatlon gain of the code vector from the gain code
book 190.
A multiplexer 210 is a circuit for combining code
series to output them. A demultiplexer 220 is a circuit for
decoding the encoded codes into code series. A synthesis
filter 230 is a circuit for reproducing a speech signal from
a generated speech source and a speech synthesis filter. An
output terminal 240 is an speech output terminal of a
decoder.
In operation a speech signal is inputted through the
input port 100 and stored in the buffer 110. By executing a
short-term prediction analysis based on given samples of the
speech signal stored in the buffer 110, the LPC analyzing
circuit 120 calculates an LPC coefficient representing
spectrum characteristics of the speech signal.
The spectrum parameter (LPC coefficient) obtained by
the LPC analyzing circuit 120 is quantized by the parameter
quantizing circuit 130. The quantized code of the LPC
coefficient is sent to the multiplexer 210 and the quantized
code is inversely quantized to be used in the subsequent
coding processes.
The speech signal stored in the buffer 110 is weighted
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: 23
for compensation of an auditory sense with the LPC
coefflcient quantized/inversely quantized by the weighting
circuit 140 to be used in the subsequent code book
searching.
Code book searching is executed with the adaptive code
- book 150, the speech source code book 170, and the gain code
book 190 respectively.
~irst, the adaptive code book searching circuit 160
executes a long-term prediction, decides a long-term
prediction parameter representing a pitch correlation,
transfers the code of the long-term prediction parameter to
the multiplexer 210, and generates a long-term prediction
speech source. The operation of the circuit 160 according
to the present invention will be described in detail later.
Next, after the effect of the speech source
representing the obtained long-term correlation is
subtracted, the speech source code book searching circuit
180 then searches in the speech source code book to decide a
speech source code, generates a code vector, and transfers
the speech source code to the multiplexer 210.
After the long-term prediction signal and the code
vector are obtained, the gain code book searching circuit
200 calculates gains of the two speech sources and transfers
each gain code to the multiplexer 210.
The mulltiplexer 210 combines each code to convert the
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combined code into and thus outputs a transmission code.
This code lS supplied to the demultiplexer 220 which
in turn decomposes the inputted transmission code into each
code. It generates a filter from the code representing the
LPC factor and transfers it to the synthesis filter 230.
A long-term prediction speech source is generated from
the code representing the long-term prediction parameters
with the adaptive code book 150, a code vector is generated
from the speech source code with the speech source code book
170, and the gains of the code vectors of the adaptive code
book 150 and the speech source code book 170 are calculated
from the gain code. An input signal fed to the synthesis
filter is generated by multiplying each speech source with
the gain term. Finally the synthesis filter 230 synthesizes
a speech signal with the input signal.
Turning to Fig.2, the processing procedure in the
adaptive code book searching circuit 160 is shown as a first
embodiment of the present invention.
In Fig.2, (a) is a step for calculating an impulse
response of a speech synthesis filter from an order of 0 to
I- 1.
(o) is a step for calculating an auto-correlation
function of the impulse response from an order of 0 to
Ismall- 1. Ismall is set such that I>Ismall may be met.
(b) is a step for inversely filtering the speech
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signal with the impulse response (see the above expression
: (6)).
(c) is a step for setting the range within which a
speech source is searched for.
(dl) is a step for generating a long-term prediction
speech source corresponding to each code with the adaptive
code book 150.
(el) is a step for calculating an auto-correlation
function of the generated long-term prediction speech source
from an order of 0 to Ismall- 1.
(f) is a step for calculating an approximate auto-
correlation to an order Ismall based on the above
approximation expression (9).
(g) is a step for calculating a cross-correlation
based on the above expression (7).
(hl) is a step for calculating an evaluation functlon
following the above expression (2).
(i) is a step for deciding an optimum code which
minimizes the evaluation function.
Describing in more detail, first, in the step (a), an
impulse response of the synthesis filter h[0]~ h[I- 1] is
derived and in (o), an auto-correlation function from an
order of 0 to Ismall- 1 is calculated. Then in the step (b),
an inverse filtering is performed.
In the step (c), the range within which the code book
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is searched is set and the processes by the steps (dl) to
(hl) are executed for each search code. Assuming that the
-number of bits of a speech source B =7, a large amount of
processing is required to execute processes (dl) to (hl) for
128 codes, so that in the step (c) the code book to be
searched is limited only within the predetermined range.
The step (dl) generates a long-term prediction speech
source (ej[n]) corresponding to each code (e.g. j) with the
adaptive code book.
The step (el) calculates an auto-correlation functions
of the speech source with a generated speech source (ej[n])
from an order of 0 to Ismall- l(Rj[i]; i=0~ Ismall).
The step (f) calculates an auto-correlation Gj with
the auto-correlation function of the speech source (Rj[i])
obtained in the step (el) and the auto-correlation function
of the synthesis filtering (hh[i]) by the auto-correlation
approximation method, as expressed in the above expression
(9) -
In this case, the auto-correlation Gj is calculated to
an order of Ismall less than the length of the impulse
response I to reduce the quantities of operations (I in the
above expression (9) is equal to Ismall). Setting Ismall to
a lower order reduces the quantities of operations in a
calculation of the auto-correlation Gj, the auto-correlation
function of the impulse responses obtained in the step (a),
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.
27
and the auto-correlation function of the speech source in
the step (el). Further, it reduces RAM regions.
- Next, the step (g) calculates a cross-correlation Cj
with the output of the inverse filtering. The step (hl)
calculates an evaluation function as expressed in the above
expression (2) with the obtained auto-correlation and cross-
correlation. The step (i) decides a code for minimizing the
evaluation function as an optimum code.
Referring to Fig.3, there is shown a flow chart in
operation of the speech source code book searching circuit
180, (d2) is a step for generating a code vector
corresponding to each code with a speech source code book
170. (e2) is a step for generating an auto-correlation
function of the speech source and calculating an auto-
correlation function corresponding to each search code bytable lookup method into a speech source auto-correlation
code book 175. Other steps are the same as those shown in
Fig.2.
In operation, the step (a) calculates an impulse
response of the synthesis filter and the step (o) calculates
its auto-correlation functions from an order of 0 to Ismall
- 1. The step (b) then executes an inverse filtering. The
step (c) sets the range within which the code book is
searched for and the processes by the steps (dl) to (hl) are
executed for each search code.
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The step (d2) generates a code vector corresponding to
each code from the speech source code book 170.
- The step (e2) calculates an auto-correlation function
of the code vector from an order of 0 to Ismall- 1. Unlike
the adaptive code book, values contained in the speech
source code book are predetermined. As a result thereof, the
auto-correlation values of the code vectors are stored
beforehand in the speech source auto-correlation code book
175 and the auto-correlation function of the code vector is
obtained by referring to a speech source auto-correlation
code book 175.
An auto-correlation Gj is calculated with the auto-
correlation function of the speech source and the auto-
correlation function of the synthesis filter by the auto-
correlation approximation method. In this case, the auto-
correlation Gj is calculated to an order Ismall less than
the length of the impulse response I to reduce the quantity
of operations. Setting Ismall to a lower order reduces the
quantity of operations for calculating the auto-correlation
Gj and the number of the auto-correlation functions of the
impulse response obtained in the step (a). Furthermore, it
reduces the memory capacity of the ROM in the speech source
auto-correlation code book 175.
Next, the step (g) calculates a cross-correlation Cj
with the output of the inverse filter. The step (hl)
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calculates an evaluation function with the obtained auto-
correlatlon and cross-correlation. The step (i) decides a
code which minimizes the evaluation function as the optimum
code.
Referring to Fig.4, the adaptive code book searching
circuit 160 according to the present embodiment includes a
sep (h2) for calculating evaluation function only with
cross-correlations. Other modules used in the present
embodiment are the same as the ones used in the first
embodiment.
The difference between the present embodiment and the
first embodiment is that in the present embodiment, the
evaluation function is expressed only by a cross-
correlation, so that the calculation of an auto-correlation
function of an impulse response, a code book for an auto-
correlation function of the speech source, and the
calculation of an auto-correlations are not required. As a
result thereof, a smaller quantity of operations are needed.
The present embodiment corresponds to the first embodiment
in which the order Ismall is set to 1.
Turning to Fig.5, there is shown a flow chart of the
speech source code book searching circuit 180. The
difference between the present embodiment and that shown in
Fig.2 is that in the present embodiment, an evaluation
function is represented only by a cross-correlation. A
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calculation of an auto-correlation function of the impulse
response and autb-correlations, and speech source auto-
correlation function code book are not required, so that a
smaller quantity of operations and less memory capacity are
needed. Also-in the present embodiment, the order Ismall is
set to 1. Experiment has shown that even when the order
Ismall is set to 1 and no auto-correlation is calculated,
there exists no special deterioration in coded speech
signals.
Fig.6 and Fig.7 show the process procedures in the
adaptive code book searching circuit 160 according to
another embodiment. In the present embodiment, a step (m)
is added to the above described first or second embodiment.
The step (m) is a circuit to decide the approximation
order Ismall of an auto-correlation and sets a value of
Ismall according to characteristics of encoded speech
signals. A value of Ismall is a variable to search a code
book and need not be transmitted. With the present
embodiment, the approximation order Ismall is varied
according to characteristics of coded speech signals such as
voiced or unvoiced ones.
In each of the above mentioned embodiments, the
invention is described using the LPC analyzing circuit,
however other analyzing methods such as the BURG method
for extracting a spectrum parameter may accomplish the same
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effect.
In addition, in each of the above embodiments the
invention is described using the LPC coefficient, however it
is obvious that other spectrum parameters such as PARCOR
coefflcient or the LSP (Line Spectrum Pair) coefficient may
accompllsh the same effect. Furthermore, in each of the
above embodiments the speech source code book searching
circuit is of a single-stage structure, however a multi-
stage structured speech source code book searching circuit
may as a matter of course accomplish the same effect.
As is stated, according to the invention the above
expression (10) may be replaced with the following
expression (13) by using, preferably in the CELP method,
with a value of the auto-correlation approximation order
Ismall being smaller than the length of an impulse response
I. .
(I- I small- - I small- (I small- 1)) sf+ I small- 2 sf
(13)
The quantity of product and sum operations of an
auto-correlation function for each code given by the above
expression (12) is replaced with the following expression
(14).
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(N I small- - -I small- (I small- 1)) 2 sf (14)
s 2
In this case, when the quantity of product and sum
operations is calculated on the same condition as in Table 1
with Ismall=1 and Ismall=O, the results are given in Table
2:
Table 2
Comparison of the quantity of product and sum operations
Quantity of
Method Expression product and
sum
operations
Filtering all
code vectors expression(5) 12.288(MOPS)
Searching the speech expression(8)+
source code book by expression(10)
the approximation in
the No.2 document 1.584(MOPS)
Searching the expression(8)+
adaptive code book by expression(10)+
the approximation in expression(12)
the No.2 document 19.504(MOPS)
Searching the expression(8)+
adaptive code book expression(13)+
with Ismall=1 expression(14) 2.239(MOPS)
Searching the speech expression(8)+
source code book expression(13)
with Ismall=1 1.215(MOPS)
I small= 0 expression(8) 1.195(MOPS)
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As may be seen from in Table 2, the present invention
significantly reduces the quantity of the product and sum
operations in the adaptive code book searching circuit, for
example, with the approximation order Ismall=l as comparied
.with the approximation described.in the reference No.2.
The preferred embodiments described herein are
therefore illustrative and not restrictive, the scope of the
invention being indicated by the appended claims and all
variations which come within the meaning of the claims are
intended to be embraced therein.
