Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission
Reexamination Certificate
1998-04-01
2001-02-20
Hudspeth, David R. (Department: 2741)
Data processing: speech signal processing, linguistics, language
Speech signal processing
For storage or transmission
C704S220000, C704S226000, C704S222000
Reexamination Certificate
active
06192334
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to an audio encoding apparatus and audio decoding apparatus which adopt a hierarchical encoding/decoding method.
2. Description of the Prior Art
Heretofore, the aim of introducing an audio encoding apparatus and decoding apparatus which adopt the hierarchical encoding method which enables decoding audio signals from a part of a bitstream of encoded signals as well as all of it, is to cope with the case that a part of the packets of encoded audio signals are lost in a packet transmission network. An example of such apparatus based on the CELP (Code Excited Linear Prediction) encoding method comprises excitation signal encoding blocks in a multistage connection. This is disclosed in “Embedded CELP coding for variable bit-rate between 6.4 and 9.6 kbit/s” by R. Drog in proceedings of ICASSP, pp. 681-684, 1991 and “Embedded algebraic CELP coders for wideband speech coding” by A. Le Guyader, et. al. in proceedings of EUSIPCO, signal processing VI, pp. 527-530, 1992.
With reference to
FIGS. 2A and 2B
, the operation of an example of the prior art will be explained. Although only two excitation signal encoding blocks are connected in the example for simplicity, the following explanation can be extended to the structure of three or more stages.
Frame dividing circuit
101
divides an input signal into frames and supplies the frames to sub-frame dividing circuit
Sub-frame dividing circuit
102
divides the input signal in a frame into sub-frames and supplies the sub-frames to linear-predictive analysis circuit
103
and psychoacoustic weighting signal generating circuit
105
.
Linear predictive analyzing circuit
103
applies linear predictive analysis to each sub-frame of the input from sub-frame dividing circuit
102
and supplies linear predictor coefficients a(i) (i=1,2,3, . . . , Np) to linear predictor coefficient quantizing circuit
104
, psychoacoustic weighting signal generating circuit
105
, psychoacoustic weighting signal reproducing circuit
106
, adopt ive codebook searching circuit
109
, multi-pulse searching circuit
110
, and auxiliary multi-pulse searching circuit
112
. Number Np in the former sentence represents the degree of linear predictive analysis and, for example may take a value of
10
. The correlation method and the covariance method are two examples of linear predictive analysis and they are explained in detail in chapter five of “Digital Audio Processing” published by Tohkai University Press in Japan.
Linear predictor coefficient quantizing circuit
104
quantizes the linear predictor coefficients for each frame instead of sub-frame. In order to decrease bitrate, it is common to adopt the method in which only the last sub-frame in the present frame is quantized and the rest of the sub-frames in the frame are interpolated using the quantized linear predictor coefficients of the present frame and the preceding frame. The quantization and interpolation are executed after converting linear predictor coefficients to line spectrum pairs (LSP). The conversion from linear predictor coefficients to LSP is explained in “Speech data Compression by LSP Speech Analysis-Synthesis Technique” in Journal of the Institute of Electronics, Information and Communication Engineers, J64-A, pp. 599-606, 1981. Well-known methods can be used for quantizing LSP. One example of such methods is explained in Japanese Patent Laid-open 4-171500.
After converting quantized LSPs to quantized linear predictor coefficients a′(i) (i=1,2,3, . . . , Np), linear predictive coefficient quantizing circuit
104
supplies the quantized linear predictor coefficients to psychoacoustic weighting signal reproducing circuit
106
, adaptive codebook searching circuit
109
, multi-pulse searching circuit
110
, and auxiliary multi-pulse searching circuit
112
and supplies indices representing quantized LSPs to multiplexer
114
.
Psychoacoustic weighting signal generating circuit
105
drives the psychoacoustically weighting filter Hw(z) represented by equation (1) by input signal in a sub-frame to generate psychoacoustically weighted signal which is supplied to target signal generating circuit
108
:
Hw
(
z
)
=
1
-
∑
i
=
1
N
p
a
(
i
)
R
2
i
z
-
i
1
-
∑
i
=
1
N
p
a
(
i
)
R
1
i
z
-
i
,
(
1
)
where R
1
and R
2
are weighting coefficients which control the amount of psychoacoustic weighting. For example, R
1
=0.6 and R
2
=0.9.
Psychoacoustic weighting signal reproducing circuit
106
drives a psychoacoustically weighting synthesis filter by excitation signal of the preceding sub-frame which is supplied via sub-frame buffer
107
. The psychoacoustic weighting synthesis filter consists of a linear predictive synthesis filter represented by equation (2) and psychoacoustically weighting filter Hw(z) in cascade connection whose coefficients are of the preceding sub-frame and have been held therein:
H
s
(
z
)
=
1
1
-
∑
i
=
1
N
p
a
′
(
i
)
z
-
i
.
(
2
)
After the driving, psychoacoustic weighting signal reproducing circuit
106
drives the psychoacoustically weighting synthesis filter by a series of zero signals to calculate the response to zero inputs. The response is supplied to target signal generating circuit
108
.
Target signal generating circuit
108
subtracts the response to zero inputs from the psychoacoustic weighting signal to get target signals X(n) (n=0,1,2, . . . , N−1) . Number N in the former sentence represents the length of a sub-frame. Target signal generating circuit
108
supplies the target signals to adaptive codebook searching circuit
109
, multi-pulse searching circuit
110
, gain searching circuit
111
, auxiliary multi-pulse searching circuit
112
, and auxiliary gain searching circuit
113
.
Using excitation signal of the preceding sub-frame supplied through sub-frame buffer
107
, adaptive codebook searching circuit
109
renews an adaptive codebook which has held past excitation signals. Adaptive vector signal Ad(n) (n=0,1,2, . . . , N−1) corresponding to pitch
d
is a signal delayed by pitch
d
which has been stored in the adaptive codebook. Here, if pitch
d
is longer than the length of a sub-frame N, adaptive codebook searching circuit
109
detaches
d
samples just before the present sub-frame and repeatedly connects the detached samples until the number of the samples reaches the length of a sub-frame N. Adaptive codebook searching circuit
109
drives the psychoacoustic weighting synthesis filter which is initialized for each sub-frame (hereinafter referred to as a psychoacoustic weighting synthesis filter in zero-state) by the generated adaptive code vector Ad(n) (n=0,1,2, . . . , N−1) to generate reproduced signals SAd(n) (n=0,1,2, . . . , N−1) and selects pitche d′ which minimizes error E(d), which is the difference between target signals X(n) and SAd(n), from a group of
d
within a predetermined searching range, for example d=17, . . . , 144. Hereinafter the selected pitch d′ will be referred to as
d
for simplicity.
E
(
d
)
=
∑
n
=
1
N
X
(
n
)
2
-
(
∑
n
=
1
N
X
(
n
)
SAd
(
n
)
)
2
∑
n
=
1
N
SAd
(
n
)
2
(
3
)
Adaptive codebook searching circuit
109
supplies the selected pitch
d
to multiplexer
114
, the selected adaptive code vector Ad (n) to gain searching circuit
111
, and the regenerated signals SAd(n) to gain searching circuit
111
and multi-pulse searching circuit
110
.
Multi-pulse searching circuit
110
searches for
P
pieces of non-zero pulse which constitute a multi-pulse signal. Here, the position of each pulse is limited to the pulse position candidates which were determined in advance. The pulse position candidates for a different non-zero pulse are different from one another. The non-zero pulses are expressed only by polarity. Therefore, the coding the multi-pulse signal is equivalent to selecting index
j
which minim
Chawan Vijay B
Hudspeth David R.
NEC Corporation
Ostrolenk Faber Gerb & Soffen, LLP
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