Title of Invention

SPEECH CODING APPARATUS, SPEECH DECODING APPARATUS AND METHODS THEREOF

Abstract Base layer coding section 101 encodes an input signal to obtain base layer coded information. base layer decoding section 102 decodes the base layer coded information to obtain a base layer decoded signal and long term prediction information (pitch lag). Adding section 103 inverts the polarity of the base layer decoded signal to add to the input signal, and obtains a residual signal. Enhancement layer coding section 104 encodes a long term prediction coefficient calculated using the long term prediction information and the residual signal to obtain enhancement layer coded information . Base layer decoding section 152 decodes the base layer coded information to obtain the base layer decoded signal and long term prediction information. Using the long term prediction information, enhancement layer decoding section 153 decodes the enhancement layer coded information to obtain an enhancement layer decoded signal. Adding section 154 adds the base layer decoded signal and enhancement layer decoded signal to obtain a speech/sound signal. It is thereby possible to implement scalable coding with small amounts of calculation and coded information.
Full Text FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(See section 10, rule 13)
"SPEECH CODING APPARATUS, SPEECH
DECODING APPARATUS AND METHODS
THEREOF"
MATSUHITA ELECTRIC INDUSTRIAL CO. LTD., 1006, Oaza Kadoma, Kadoma-shi, Osaka 571-8501, Japan
The following specification particularly describes the invention and the manner in which it is to be performed.

2F04017—PCT



DESCRIPTION
SPEECH CODING APPARATUS, SPEECH DECODING APPARATUS AND
METHODS THEREOF
Technical Field
The present invention relates to a speech coding apparatus, speech decoding apparatus and methods thereof used in communication systems for coding and transmitting speech and/or sound signals.
Background Art
In the fields of digital wireless communications, packet communications typified by Internet
communications, and speech storage and so forth, techniques for coding/decoding speech signals are indispensable in order to efficiently use the transmission channel capacity of radio signal and storage medium, and many speech coding/decoding schemes have been
developed. Among the systems, the CELP speech coding/decoding scheme has been put into practical use as a mainstream technique.
A CELP type speech coding apparatus encodes input speech based on speech models stored beforehand. More
specifically, the CELP speech coding apparatus divides a digitalized speech signal into frames of about 20 ms, performs linear prediction analysis of the speech signal
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on a frame-by-frame basis, obtains linear prediction coefficients and linear prediction residual vector, and encodes separately the linear prediction coefficients and linear prediction residual vector. 5 In order to execute low-bit rate communications, since the amount of speech models to be stored is limited, phonation speech models are chiefly stored in the conventional CELP type speech coding/decoding scheme. In communication systems for transmitting packets
such as Internet communications, packet losses occur depending on the state of the network, and it is preferable that speech and sound can be decoded from part of remaining coded information even when part of the coded information is lost. Similarly, in variable rate communication
systems for varying the bit rate according to the communication capacity, when the communication capacity is decreased, it is desiredthat loads onthe communicat ion capacity can be reduced at ease by transmitting only part of the coded information. Thus, as a technique enabling
decoding of speech and sound using all the coded information or part of the coded information, attention has recently been directed toward the scalable coding technique. Some scalable coding schemes are disclosed conventionally.
The scalable coding system is generally comprised of a base layer and enhancement layer, and the layers constitute a hierarchical structure with the base layer
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being the lowest layer. In each layer, a residual signal
is coded that is a difference between an input signal
and output signal in a lower layer. According to this
constitution, it is possible to decode speech and/or sound
signals using the coded information of all the layers
or using only the coded information of a lower layer.
However , in the convent ional scalable coding system ,
the CELP type speech coding/decoding system is used as
the coding schemes for the base layer and enhancement
layers, and considerable amounts are thereby required
both in calculation and coded information.
Disclosure of Invention
It is therefore an object of the present invention
to provide a speech coding apparatus, speech decoding apparatus and methods thereof enabling scalable coding to be implemented with small amounts of calculation and coded information.
The above-noted object is achieved by providing an
enhancement layer to perform long term prediction, performing long term prediction of the residual signal in the enhancement layer using a long term correlation characteristic of speech or sound to improve the quality of the decoded signal, obtaining a long term prediction
lag using long term prediction information of a base layer, and thereby reducing the computation amount.
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Brief Description of Drawings
FIG. 1 is a block diagram illustrating conf igurations of a speech coding apparatus and speech decoding apparatus according to Embodiment 1 of the invention; FIG.2 is a block diagram illustrating an internal configuration a base layer coding section according to the above Embodiment;
FIG.3 is a diagram to explain processing for a
parameter determining section in the base layer coding
section to determine a signal generated from an adaptive
excitation codebook according to the above Embodiment;
FIG.4 is a block diagram illustrating an internal
configuration of a base layer decoding section according
to the above Embodiment;
FIG.5 is a block diagram illustrating an internal
configuration of an enhancement layer coding section
according to the above Embodiment;
FIG.6 is a block diagram illustrating an internal configuration of an enhancement layer decoding section according to the above Embodiment;
FIG.7 is a block diagram illustrating an internal configuration of an enhancement layer coding section according to Embodiment 2 of the invention;
FIG. 8 is a block diagram illustrating an internal configuration of an enhancement layer decoding section according to the above Embodiment; and
FIG.9 isablockdiagramillustrat ing configurations
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of a speech signal transmission apparatus and speech signal reception apparatus according to Embodiment 3 of the invention.
Best Mode for Carrying Out the Invention
Embodiments of the present invention will specifically be described below with reference to the accompanying drawings. A case will be described in each of the Embodiments where long term predict ion is performed
in an enhancement layer in a two layer speech coding/decoding method comprised of a base layer and the enhancement layer. However, the invent ion is not limited in layer structure, and applicable to any cases of performing long term prediction in an upper layer using
long term prediction information of a lower layer in a hierarchical speech coding/decoding method with three or more layers. A hierarchical speech coding method refers to a method in which a plurality of speech coding methods for coding a residual signal (difference between an input
signal of a lower layer and a decoded signal of the lower layer) by long term predict ion to output coded information exist in upper layers and constitute a hierarchical structure. Further, a hierarchical speech decoding method refers to a method in which a plurality of speech
decoding methods for decoding a residual signal exists in an upper layer and constitutes a hierarchical structure Herein, a speech/sound coding/decoding method existing
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in the lowest layer will be referred to as a base layer. A speech/sound coding/decoding method existing in a layer higher than the base layer will be referred to as an enhancement layer. In each of the Embodiments of the invention, a case is described as an example where the base layer performs CELP type speech coding/decoding.
(Embodiment 1)
FIG.l isablockdiagramillustrating configurat ions of a speech coding apparatus and speech decoding apparatus according to Embodiment 1 of the invention.
In FIG.l, speech coding apparatus 100 is mainly comprised of base layer coding section 101, base layer
decoding section 102, adding section 103, enhancement layer coding section 104, and multiplexing section 105. Speech decoding apparatus 150 is mainly comprised of demultiplexing section 151, base layer decoding section 152, enhancement layer decoding section 153, and adding
section 154 .
Base layer coding section 101 receives a speech or sound signal, codes the input signal using the CELP type speech coding method, and outputs base layer coded informat ion obtained by the coding, to base layer decoding
section 102 and multiplexing section 105.
Base layer decoding section 102 decodes the base layer coded information using the CELP type speech
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decoding method, and outputs a base layer decoded signal obtained by the decoding , to adding sect ion 1 0 3 . Further, base layer decoding section 102 outputs the pitch lag to enhancement layer coding section 104 as long term prediction information of the base layer.
The "long term prediction information" is information indicating long term correlation of the speech or sound signal . The "pitch lag" refers to position information specified by the base layer, and will be
described later in detail.
Adding section 103 inverts the polarity of the base layer decoded signal output from base layer decoding section 102 to add to the input signal, and outputs a residual signal as a result of the addition to enhancement
layer coding section 104.
Enhancement layer coding sect ion 104 calculates long term prediction coefficients using the long term prediction information output from base layer decoding section 102 and the residual signal output from adding
section 103, codes the long term predict ion coefficients, and outputs enhancement layer coded information obtained by coding to multiplexing section 105.
Multiplexing section 105 multiplexes the base layer coded information output from base layer coding section
101 and the enhancement layer coded information output from enhancement layer coding section 104 to output to demultiplexing section 151 as multiplexed information
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via a transmission channel.
Demultiplexing section 151 demultiplexes the multiplexed information transmitted from speech coding apparatus 100 into the base layer coded information and enhancement layer coded information, and outputs the demultiplexed base layer coded information to base layer decoding section 152, while outputting the demultiplexed enhancement layer coded information to enhancement layer decoding section 153.
Base layer decoding section 152 decodes the base layer coded information using the CELP type speech decoding method, and outputs a base layer decoded signal obtained by the decoding, to adding section 154.Further, base layer decoding section 152 outputs the pitch lag
to enhancement layer decoding section 153 as the long term prediction information of the base layer. Enhancement layer decoding section 153 decodes the enhancement layer coded information using the long term prediction information, and outputs an enhancement layer
decoded signal obtained by the decoding , to adding sect ion 154 .
Adding section 154 adds the base layer decoded signal output from base layer decoding section 152 and the enhancement layer decoded signal output from enhancement
layer decoding section 153, and outputs a speech or sound signal as a result of the addition, to an apparatus for subsequent processing.
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The internal configuration of base layer coding section 101 of FIG. 1 will be describedbelowwith reference to the block diagram of FIG.2.
An input signal of base layer coding section 101 5 is input to pre-processing section 200. Pre-processing section 200 performs high-pass filtering processing to remove the DC component, waveform shaping processing and pre-emphasis processing to improve performance of subsequent coding processing, and outputs a signal (Xin) subjected to the processing, to LPC analyzing section 201 and adder 204.
LPC analyzing section 201 performs linear predictive analysis using Xin, and outputs a result of the analysis (linear prediction coefficients) to LPC quantizing section 202. LPC quantizing section 202 performs quantization processing on the linear prediction coefficients (LPC) output from LPC analyzing sect ion 201, and outputs quantized LPC to synthesis filter 203, while outputting code (L) representing the quantized LPC, to 20 multiplexing section 213.
Synthesis filter 203 generates a synthesized signal by performing filter synthesis on an excitation vector output from adding section 210 described later using filter coefficients based on the quantized LPC, and outputs the synthesized signal to adder 204.
Adder 204 inverts the polarity of the synthesized signal, adds the resulting signal to Xin, calculates an
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error signal, and outputs the error signal to perceptual weighting section 211.
Adaptive excitation codebook 205 has excitation vector signals output earlier from adder 210 stored in a buffer, and fetches a sample corresponding to one frame from an earlier excitation vector signal sample specified by a signal output from parameter determining section 212 to output to multiplier 208.
Quantization gain generating section 206 outputs an adaptive excitation gain and fixed excitation gain specified by a signal output from parameter determining section 212 respectively to multipliers 208 and 209.
Fixed excitation codebook 207 multiplies a pulse
excitation vector having a shape specified by the signal
output from parameter determining section 212 by a spread
vector, and outputs the obtained fixed excitation vector
to multiplier 209.
Multiplier 208 multiplies the quantizat ion adaptive excitation gain output from quantization gain generating section 206 by the adaptive excitation vector output from adaptive excitation codebook 205 and outputs the result to adder 210. Multiplier 209 multiplies the quantization fixed excitation gain output from quantization gain generating section 206 by the fixed excitation vector output from fixed excitation codebook 207 and outputs the result to adder 210.
Adder 210 receives the adaptive excitation vector
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and fixed excitation vector both multiplied by the gain respectively input from multipliers 208 and 209 to add in vector, and outputs an excitation vector as a result of the addition to synthesis filter 203 and adaptive 5 excitation codebook 205. In addition, the excitation vector input to adaptive excitation codebook 205 is stored in the buffer.
Perceptual weighting section 211 performs perceptual weight ing on the error signal output from adder
204, and calculates a distortion between Xin and the
synthesized signal in a perceptual weighting region and
outputs the result to parameter determining section 212 .
Parameter determining section 212 selects the
adaptive excitation vector, fixed excitation vector and
quantization gain that minimize the coding distortion output from perceptual weighting section211 respectively from adaptive excitation codebook 205, fixed excitation codebook 207 and quantization gain generating section 206, and outputs adaptive excitation vector code (A),
excitation gain code (G) and fixed excitation vector code
(F) representing the result of the selection to
multiplexing section 213. In addition, the adaptive
excitation vector code (A) is code corresponding to the
pitch lag.
Multiplexing section 213 receives the code (L) representing quantized LPC from LPC quantizing section 202, further receives the code (A) representing the
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adaptive excitation vector, the code (F) representing the fixed excitation vector and the code (G) representing the quantization gain from parameter determining section 212 , and multiplexes these pieces of information to output 5 as base layer coded information.
The foregoing is explanations of the internal
configuration of base layer coding section 101 of FIG.l.
With reference to FIG.3, the processing will briefly
be described below for parameter determining section 212
to determine a signal to be generated from adaptive excitationcodebook205. In FIG.3, buffer 301 isthebuffer provided in adaptive excitation codebook 205, position 302 is a fetching position for the adaptive excitation vector, and vector 303 is a fetched adaptive excitation
vector. Numeric values "41" and "296" respectively correspond to the lower limit and the upper limit of a range in which fetching position 302 is moved.
The range for moving fetching position 302 is set at a range with a length of "256" (for example, from "41"
to "296") , assuming that the number of bits assigned to the code (A) representing the adaptive excitation vector is "8." The range for moving fetching position 302 can be set arbitrarily.
Parameter determining section 212 moves fetching
position 302 in the set range, and fetches adaptive excitation vector 303 by the frame length from each position. Then, parameter determining sect ion 2 12 obtains
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fetching position 302 that minimizes the coding distortion output from perceptual weighting section 211. Fetching position 302 in the buffer thus obtained by parameter determining section 212 is the "pitch lag" . The internal configuration of base layer decoding section 102 (152) of FIG.l will be described below with reference to FIG.4.
In FIG.4, the base layer coded information input to base layer decoding section 102 (152) is demultiplexed
to separate codes (L, A, GandF) by demultiplexing sect ion 401. The demultiplexed LPC code (L) is output to LPC decoding section 402, the demultiplexed adaptive excitation vector code (A) is output to adaptive excitation codebook 405, the demultiplexed excitation
gain code (G) is output to quantization gain generating section 406, and the demultiplexed fixed excitation vector code (F) is output to fixed excitation codebook 407 .
LPC decoding section 402 decodes the LPC from the
code (L) output from demultiplexing section 401 and outputs the result to synthesis filter 403.
Adaptive excitation codebook 405 fetches a sample corresponding to one frame from a past excitation vector signal sample designated by the code (A) output from
demultiplexing section 401 as an excitation vector and outputs the excitation vector to multiplier 408. Further, adaptive excitation codebook 405 outputs the pitch lag
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as the long term prediction information to enhancement layer coding section 104 (enhancement layer decoding section 153) .
Quantization gain generating section 406 decodes an adaptive excitation vector gain and fixed excitation vector gain designated by the excitation gain code (G) output from demultiplexing section 401 respectively and output the results to multipliers 408 and 409.
Fixed excitation codebook 407 generates a fixed excitation vector designated by the code (F) output from demultiplexing section 401 and outputs the result to adder 409 .
Multiplier 408 multiplies the adaptive excitation
vector by the adaptive excitation vector gain and outputs
the result to adder 410. Multiplier 409 multiplies the
fixed excitation vector by the fixed excitation vector
gain and outputs the result to adder 410.
Adder 410 adds the adaptive excitation vector and fixed excitation vector both multiplied by the gain respectively output from multipliers 408 and 409, generates an excitation vector, and outputs this excitation vector to synthesis filter 403 and adaptive excitation codebook 405.
Synthesis filter 4 03 performs filter synthesis using
the excitation vector output from adder 410 as an
excitation signal and further using the filter
coefficients decoded in LPC decoding section 402, and
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outputs a synthesized signal to post-processing section 404 .
Post-processing section 404 performs on the signal output from synthesis filter 403 processing for improving subjective quality of speech such as formant emphasis and pitch emphasis and other processing for improving subjective quality of stationary noise to output as a base layer decoded signal.
The foregoing is explanations of the internal
configuration of base layer decoding section 102 (152) of FIG.1.
The internal configuration of enhancement layer coding section 104 of FIG.l will be described below with reference to FIG.5.
Enhancement layer coding section 104 divides the residual signal into segments of N samples (N is a natural number), and performs coding for each frame assuming N samples as one frame. Hereinafter, the residual signal is represented by e(0) ~ e(X-l), and frames subject to
coding is represented by e(n) ~ e(n + N-l) . Herein, X is a length of the residual signal, and N corresponds to the length of the frame, n is a sample positioned at the beginning of each frame, and corresponds to an integral multiple of N. In addition, the method of predicting a
signal of some frame from previously generated signals is called long term prediction. A filter for performing long term prediction is called pitch filter, comb filter
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and the 1ike.
In FIG.5, long term prediction lag instructing section 501 receives long term prediction information t obtained in base layer decoding section 102, and based on the information, obtains long term prediction lag T of the enhancement layer to output to long term prediction signal storage 502. In addition, when a difference in sampling frequency occurs between the base layer and enhancement layer, the long term prediction lag T is
obtained from following equation (1). In addition, in equation (1) , D is the sampling frequency of the enhancement layer, and d is the sampling frequency of the base layer.
T = Dxt/d ... Equation. (1)
Long term prediction signal storage 502 is provided with a buffer for storing a long term prediction signal generated earlier. When the length of the buffer is assumed M, the buffer is comprised of sequence s(n-M-l) ~ s(n-l) of the previously generated long term prediction signal .
Upon receiving the long term prediction lag T from long term prediction lag instructing section 501, long term prediction signal storage 502 fetches long term prediction signal s(n-T) ~ s(n-T+N-l) the long term prediction lag T back from the previous long term
prediction signal sequence stored in the buffer, and outputs the result to long term prediction coefficient calculating section 503 and long term prediction signal
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generating section 506. Further, long term prediction signal storage 502 receives long term prediction signal s(n) ~ s(n + N-l) from long term prediction signal generating section 506, and updates the buffer by following equation (2).


In addition, when the long term prediction lag T is shorter than the frame length N and long t erm predict ion signal storage 502 cannot fetch a long term prediction
signal, the long term prediction lag T is multiplied by integrals until the T is longer than the frame length N, to enable the long term predict ion signal to be fetched. Otherwise, long term prediction signal s(n-T) s(n-T + N-l) the long term predict ion lag T back is repeated
up to the frame length N to be fetched.
Long term prediction coefficient calculating section 503 receives the residual signal e (n) ~ e(n + N-l) and long term prediction signal s (n-T) ~ s (n-T + N-1) , and using these signals in following equation (3) , calculates
a long term prediction coefficient (3 to output to long term prediction coefficient coding section 504.
AM
^ e(n + i)s(n-T + i)
P = ~r] ...Equation (3)
1=0
Long term predict ion coefficient coding section 504 codes the long term predict ion coefficient p, and outputs
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the enhancement layer coded information obtained by coding to long term prediction coefficient decoding section 505, while further outputting the information to enhancement layer decoding section 153 via the transmission channel. In addition, as a method of coding the long term prediction coefficient (3, there are known a method by scalar quantization and the like.
Long term prediction coefficient decoding section
505 decodes the enhancement layer coded information, and
outputs a decoded long term prediction coefficient (3q
obtained by decoding to long term prediction signal
generating section 506.
Long term prediction signal generating section 506
receives as input the decoded long term prediction
coefficient (3q and long term prediction signal s(n-T)
~ s(n-T+N-l), and, using the input, calculates long term
prediction signal s(n) ~ s(n+N-l) by following equation
(4) , and outputs the result to long term prediction signal
storage 5 02.
s(n + i) = paxs(n-T + \) {i = 0,---,N-X) ...Equation (4)
The foregoing is explanations of the internal configuration of enhancement layer coding section 104 of FIG.1.
The internal configuration of enhancement layer decoding section 153 of FIG.l will be described below with reference to the block diagram of FIG.6.
In FIG.6, long term prediction lag instructing
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section 601 obtains the long term prediction lag T of the enhancement layer using the long term prediction information output from base layer decoding section 152 to output to long term prediction signal storage 602. Long term prediction signal storage 602 is provided with a buffer for storing a long term prediction signal generated earlier. When the length of the buffer is M, the buffer is comprised of sequence s(n-M-l) ~ s(n-l) of the earlier generated long term prediction signal.
Upon receiving the long term prediction lag T from long term prediction lag instructing section 601, long term prediction signal storage 602 fetches long term prediction signal s(n-T) ~ s(n-T+N-l) the long term prediction lag T back from the previous long term
prediction signal sequence stored in the buffer to output to long term prediction signal generating section 604. Further, long term predict ion signal storage 602 receives long term prediction signals s(n) ~ s(n+N-l) from long term prediction signal generating section 604, and
updates the buffer by equation (2) as described above.
Long term prediction coefficient decoding section
603 decodes the enhancement layer coded information, and
outputs the decoded long term prediction coefficient |3q
obtained by the decoding, to long term prediction signal
generating section 604.
Long term prediction signal generating section 604 receives as its inputs the decoded long term prediction
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coefficient (3q and long term prediction signal s(n-T) ~ s(n-T + N-1) , and using the inputs, calculates long term prediction signal s(n) ~ s(n + N-1) by Eq. (4) as described above, and outputs the result to long term prediction signal storage 6 02 and adding section 153 as an enhancement layer decoded signal.
The foregoing is explanations of the internal configuration of enhancement layer decoding section 153 of FIG.1 .
Thus, by providing the enhancement layer to perform long term prediction and performing long term prediction on the residual signal in the enhancement layer using the long term correlation characteristic of the speech or sound signal, it is possible to code/decode the
speech/sound signal with a wide frequency range using less coded information and to reduce the computation amount.
At this point, the coded information can be reduced by obtaining the long term prediction lag using the long
term prediction information of the base layer, instead of coding/decoding the long term prediction lag.
Further, by decoding the base layer coded information, it is possible to obtain only the decoded signal of the base layer, and implement the function for
decoding the speech or sound from part of the coded information in the CELP type speech coding/decoding method (scalable coding).
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Furthermore, in the long term prediction, using the long term correlation of the speech or sound, a frame with the highest correlation with the current frame is fetched from the buffer, and using a signal of the fetched frame, a signal of the current frame is expressed. However, in the means for fetching the frame with the highest correlation with the current frame from the buffer, when there is no information to represent the long term correlation of speech or sound such as the pitch lag,
it is necessary to vary the fetching position to fetch a frame from the buffer while calculating the auto-correlation function of the fetched frame and the current frame to search for the frame with the highest correlation, and the calculation amount for the search
becomes significantly large.
However, by determining the fetching position uniquely using the pitch lag obtained in base layer coding section 101, it is possible to largely reduce the calculation amount required for general long term
prediction.
In addition, a case has been described above in the enhancement layer long term prediction method explained in this Embodiment where the long term prediction information output from the base layer decoding section
is the pitch lag, but the invention is not limited to this, and any information may be used as the long term prediction information as long as the information
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represents the long term correlation of speech or sound. Further, the case is described in this Embodiment where the posit ion for long term prediction signal storage 502 to fetch a long term prediction signal from the buffer is the long term prediction lag T, but the invention is applicable to a case where such a position is position T + a (a is a minute number and settable arbitrarily) around the long term prediction lag T, and it is possible to obtain the same effects and advantages as in this
Embodiment even in the case where a minute error occurs in the long term prediction lag T.
For example, long term prediction signal storage 502 receives the long term prediction lag T from long term predict ion lag instructing section 501, fetches long
term prediction signal s(n-T-a) ~ s(n-T-a+N-l) T+a back from the previous long term prediction signal sequence stored in the buffer, calculates a determination value C using following equation (5) , and obtains a that maximizes the determination value C, and encodes this.
Further, in the case of decoding, long term prediction signal storage 602 decodes the coded information of a, and using the long term prediction lag T, fetches long term prediction signal s(n-T-a) ~ s (n-T-a + N-1) .
N-y] e(n + i)s(n -T-a + i)

C =

^s(n-T-a + i)2

Equation (5)




Further, while a case has been described above in

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this Embodiment where long term prediction is carried out using a speech/sound signal, the invention is eventually applicable to a case of transforming a speech/sound signal from the time domain to the frequency domain using orthogonal transform such as MDCT and QMF, and performing long term prediction using a transformed signal (frequency parameter), and it is still possible to obtain the same effects and advantages as in this Embodiment. For example, in the case of performing
enhancement layer long term prediction using the frequency parameter of a speech/sound signal, in FIG.5, long term predict ion coefficient calculating section 503 is newly provided with a function of transforming long term prediction signal s(n-T) ~ s(n-T+N-l) from the time
domain to the frequency domain and with another function of transforming a residual signal to the frequency parameter, and long term prediction signal generating section 506 is newly provided with a function of inverse - transforming long term prediction signals s(n)
s(n+N-l) from the frequency domain to time domain. Further, in FIG.6, long term predict ion signal generating section 604 is newly provided with the function of inverse - transforming long term prediction signal s(n) ~ s(n+N-l) from the frequency domain to the time domain.
It is general in the general speech/sound coding/decoding method adding redundant bits for use in error detection or error correction to the coded
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information and transmitting the coded information containing the redundant bits on the transmission channel. It is possible in the invention to weight a bit assignment of redundant bits assigned to the coded information (A) output from base layer coding section 101 and to the coded information (B) output from enhancement layer coding section 104 to the coded information (A) to assign.
(Embodiment 2)
Embodiment 2 will be described with reference to a case of coding and decoding a difference (long term prediction residual signal) between the residual signal and long term prediction signal.
Configurations of a speech coding apparatus and
speech decoding apparatus of this Embodiment are the same as those in FIG.l except for the internal configurations of enhancement layer coding section 104 and enhancement layer decoding section 153.
FIG.7 is a block diagram illustrating an internal
configuration of enhancement layer coding section 104
according to this Embodiment. In addition, in FIG.7,
structural elements common to FIG.5 are assigned the same
reference numerals as in FIG.5 to omit descriptions.
As compared with FIG.5, enhancement layer coding
section 104 in FIG.7 is further provided with adding section 701, long term prediction residual signal coding section 702, coded information multiplexing section 703,
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long term prediction residual signal decoding section 704 and adding section 705.
Long term prediction signal generating section 506 outputs calculated long term prediction signal s(n) s(n+N-l) to adding sections 701 and 702.
As expressed in following equation (6) , adding section 701 inverts the polarity of long term prediction signal s (n) ~ s(n + N-1) , adds the result to residual signal e (n) ~e (n + N-1), andoutputslong term predict ion residual signal p(n) ~ p(n+N-l) as a result of the addition to long term prediction residual signal coding section 702 .

Long term prediction residual signal coding section 702 codes long term prediction residual signal p(n) ~ 15 p(n+N-l), and outputs coded information (hereinafter, referred to as "long term prediction residual coded information") obtained by coding to coded information multiplexing section 703 and long term prediction residual signal decoding section 704. In addition, the coding of the long term prediction residual signal is generally performed by vector quantizat ion.
A method of coding long term prediction residual
signal p(n) ~ p(n+N-l) will be described below using as
one example a case of performing vector quantization with
8 bits. In this case, a codebook storing beforehand
generated 256 types of code vectors is prepared in long
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term prediction residual signal coding section 702 . The code vector CODE(k) (0) ~ CODE(k) (N-l) is a vector with a length of N.k is an index of the code vector and takes values ranging from 0 to 255. Long term prediction 5 residual signal coding section 702 obtains a square error er between long term prediction residual signal p(n) -p(n + N-l) and code vector CODE (k) (0) ~ CODE(k) (N-l) using following equation (7).


Then, long term prediction residual signal coding section 702 determines a value of k that minimizes the square error er as long term prediction residual coded information.
Coded information multiplexing section 703
multiplexes the enhancement layer coded information input from long term prediction coefficient coding section 504 and the long term prediction residual coded information input from long term prediction residual signal coding section 702, and outputs the multiplexed information to
enhancement layer decoding section 153 via the transmission channel.
Long term prediction residual signal decoding section 704 decodes the long term prediction residual coded information, and outputs decoded long term
prediction residual signal pq(n) ~ pq(n+N-l) to adding section 7 05.
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Adding section 705 adds long term predict ion signal s(n) - s(n+N-l) input from long term prediction signal generating section 506 and decoded long term prediction residual signal pq(n) ~ pq(n+N-l) input from long term 5 prediction residual signal decoding section 704, and outputs the result of the addition to long term prediction signal storage 502. As a result, long term prediction signal storage 502 updates the buffer using following equation ( 8) .




The foregoing is explanations of the internal configuration of enhancement layer coding section 104 according to this Embodiment.
An internal configuration of enhancement layer decoding section 153 according to this Embodiment will be described below with reference to the block diagram in FIG.8. In addition, in FIG.8, structural elements common to FIG.6 are assigned the same reference numerals
as in FIG.6 to omit descriptions.
Compared with FIG.6, enhancement layer decoding section 153 in FIG.8 is further provided with coded information demultiplexing section 801, long term prediction residual signal decoding section 802 and
adding section 803.
Coded information demultiplexing section 801
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demultiplexes the multiplexed coded information received via the transmission channel into the enhancement layer coded information and long term prediction residual coded information, and outputs the enhancement layer coded information to long term predict ion coefficient decoding section 603, and the long term prediction residual coded information to long term prediction residual signal decoding section 802.
Long term prediction residual signal decoding
section 802 decodes the long term prediction residual coded information, obtains decoded long term prediction residual signal pq(n) ~ pq(n + N-l) , and outputs the signal to adding section 803.
Adding section 803 adds long term predict ion signal
s(n) - s(n+N-l) input from long term prediction signal generating section 604 and decoded long term prediction residual signal pq(n) ~ pq(n+N-l) input from long term prediction residual signal decoding section 802, and outputs a result of the addition to long term prediction
signal storage 602, while outputting the result as an enhancement layer decoded signal.
The foregoing is explanations of the internal configuration of enhancement layer decoding section 153 according to this Embodiment.
By thus coding and decoding the difference (long term prediction residual signal) between the residual signal and long term prediction signal, it is possible
29

2F04017 —PCT
to obtain a decoded signal with higher quality than previously described in Embodiment 1.
In addition, a case has been described above in this Embodiment of coding a long term prediction residual signal by vector quantization. However, the present invention is not limited in coding method, and coding may be performed using shape-gain VQ, split VQ, transform VQ or multi-phase VQ, for example.
A case will be described below of performing coding
by shape-gain VQ of 13 bits of 8 bits in shape and 5 bits in gain. Inthiscase, two types of codebooksare provided, a shape codebook and gain codebook. The shape codebook is comprised of 256 types of shape code vectors, and shape code vector SCODE(kl) (0) ~ SCODE(kl) (N-l) is a vector
with a length of N. kl is an index of the shape code vector and takes values ranging from 0 to 255 . The gain codebook is comprised of 32 types of gain codes, and gain code GCODE(k2) takes a scalar value. k2 is an index of the gain code and takes values ranging from 0 to 31. Long
term prediction residual signal coding section 702 obtains the gain and shape vector shape(0) ~ shape(N-l) of long term prediction residual signal p(n) ~ p(n+N-l) using following equation (9) , and further obtains a gain error gainer between the gain and gain code GC0DE(k2)
and a square error shapeer between shape vector shape(0) shape(N-l) and shape code vector SCODE(kl) (0) SCODE(kl) (N-l) .
30

2P04017 — PCT

^






Then, long term prediction residual signal coding section 702 obtains a value of k2 that minimizes the gain error gainer and a value of kl that minimizes the square error shapper, and determines the obtained values as long term prediction residual coded information.
A case will be described below where coding is performed by split VQ of 8 bits. In this case, two types of codebooks are prepared, the first split codebook and second split codebook. The first split codebook is comprised of 16 types of first
split code vectors SPCODE (k3) ( 0) ~ SPCODE(k3) (N/2 -1) , second split codebook SPCODE(k4) (0) ~ SPCODE(k4) (N/2-1) is comprised of 16 types of second split code vectors, and each code vector has a length of N/2. k3 is an index of the first split code vector and takes values ranging
from 0 to 15 k4 is an index of the second split code vector and takes values ranging from 0 to 15 . Long term predict ion residual signal coding section 702 divides long term prediction residual signal p(n) ~ p(n+N-l) into first
31

2F04017 —PCT

^

split vector spl (0) ~ spl (N/2~1) and second split vector sp2(0) ~ sp2(N/2 —1) using following equation (11), and obtains a square error splitter 1 between first split vector spl(0) ~ spl(N/2—1) and first split code vector SPCODE(k3) (0) ~ SPCODE(k3) (N/2 —1) , and a square error splitter 2 between second split vector sp2(0) - sp2(N/2
— 1) and second split codebook SPCODE(k4) (0) SPCODE(k4) (N/2 — 1) , using following equation (12).







Then, long term prediction residual signal coding section 702 obtains the value of k3 that minimizes the square error splitter 1 and the value of k4 that minimizes the square error splitter 2, and determines the obtained
values as long term prediction residual coded information.
A case will be described below where coding is performed by transform VQ of 8 bits us ing discrete Fourier transform. In this case, a transform codebook comprised
of 256 types of transform code vector is prepared, and transform code vector TC0DE(k5) (0) ~ TCODE(k5) (N/2-1) is a vector with a length of N/2. k5 is an index of the transform code vector and takes values ranging from 0
32

2F04017 —PCT
to 255. Long term prediction residual signal coding section 702 performs discrete Fourier transform of long term prediction residual signal p (n) ~ p(n + N-1) to obtain transform vector tp(0) -tp(N-l) using following equation 5 (13) , and obtains a square error transer between transform vector tp ( 0 ) -tp(N-l) and transform code vector TCODE(k5)(0) ~TCODE(k5)(N/2-1) usingfollowingequation (14) .




Then, long term prediction residual signal coding
section 7 02 obtains a value of k5 that minimizes the square
error transfer, and determines the obtained value as long
term prediction residual coded information.
A case will be described below of performing coding by two-phase VQ of 13 bits of 5 bits for a first stage and 8 bits for a second stage. In this case, two types of codebooks are prepared, a first stage codebook and second stage codebook. The first stage codebook is
comprised of 32 types of first stage code vectors PHCODE1 (k6) (0) ~ PHCODE1 (k6) (N-l) , the second stage codebook is comprised of 256 types of second stage code vectors PHC0DE2 (k7) (0) ~ PHC0DE2 (k7) (N-l) , and each code vector has a length of N/2.k6 is an index of the first
stage code vector and takes values ranging from 0 to 31.
33

2F04017 —PCT
k7 is an index of the second stage code vector and takes values ranging from 0 to 255. Long term prediction residual signal coding section 702 obtains a square error phaseer 1 between long term prediction residual signal p(n) ~ p(n+N-l) and first stage code vector PHCODE1 (k6) (0) ~ PHCODE1 (k6)(N-l) using following equation (15) , further obtains the value of k6 that minimizes the square error phaseer 1, and determines the value as Kmax.
^


Then, long term prediction residual signal coding section 702 obtains error vector ep(0)~ep (N-1) using following equation (16), obtains a square error phaseer 2 between error vector ep(0) ~ ep(N-l) and second stage
code vector PHCODE2 (k7 ) ( 0 ) ~ PHCODE2 (k7 ) (N-1) using following equation (17), further obtains a value of k7 that minimizes the square error phaseer 2, and determines the value and Kmax as long term prediction residual coded information.




(Embodiment 3)
FIG. 9 is ablock diagram illustrat ing configurations of a speech signal transmission apparatus and speech
34

2F04017-PCT
signal reception apparatus respectively having the speech coding apparatus and speech decoding apparatus described in Embodiments 1 and 2 .
In FIG.9, speech signal 901 is converted into an electric signal through input apparatus 902 and output to A/D conversion apparatus 903 . A/D conversion apparatus 903 converts the (analog) signal output from input apparatus 902 into a digital signal and outputs the result to speech coding apparatus 904. Speech coding apparatus
904 is installed with speech coding apparatus 100 as shown in FIG.l, encodes the digital speech signal output from A/D conversion apparatus 903, and outputs coded information to RF modulation apparatus 905. R/F modulation apparatus 905 converts the speech coded
information output from speech coding apparatus 904 into a signal of propagation medium such as a radio signal to transmit the information, and outputs the signal to transmission antenna 906. Transmission antenna 906 transmits the output signal output from RF modulation
apparatus 905 as a radio signal (RF signal) . In addition, RF signal 907 in FIG. 9 represents a radio signal (RF signal) transmitted from transmission antenna 906. The configuration and operation of the speech signal transmission apparatus are as described above.
RF signal 908 is received by reception antenna 909 and then output to RF demodulation apparatus 910. In addition, RF signal 908 in FIG.9 represents a radio signal
35

2F04017 —PCT
received by reception antenna 909, which is the same as RF signal 907 if attenuation of the signal and/or multiplexing of noise does not occur on the propagation path . RF demodulat ion apparatus 910 demodulates the speech coded information from the RF signal output from reception antenna 909 and outputs the result to speech decoding apparatus 911. Speech decoding apparatus 911 is installed with speech decoding apparatus 150 as shown in FIG.l,
decodes the speech signal from the speech coded information output from RF demodulation apparatus 910, and outputs the result to D/A conversion apparatus 912. D/A conversion apparatus 912 converts the digital speech signal output from speech decoding apparatus 911 into
an analog electric signal and outputs the result to output apparatus 913.
Output apparatus 913 converts the electric signal into vibration of air and outputs the result as a sound signal to be heard by human ear . Inaddition, inthefigure,
reference numeral 914 denotes an output sound signal. The configuration and operation of the speech signal reception apparatus are as described above.
It is possible to obtain a decoded signal with high quality by providing a base station apparatus and
communication terminal apparatus in a wireless communication system with the above-mentioned speech signal transmission apparatus and speech signal reception
36

2F04017-PCT
apparatus.
As described above, according to the present invention, it is possible to code and decode speech and sound signals with a wide bandwidth using less coded 5 information, and reduce the computation amount . Further, by obtaining a long term prediction lag using the long term prediction information of the base layer, the coded information can be reduced. Furthermore, by decoding the base layer coded information, it is possible to obtain
only a decoded signal of the base layer, and in the CELP type speech coding/decoding method, it is possible to implement the function of decoding speech and sound from part of the coded information (scalable coding).
This application is based on Japanese Patent
Application No.2003 — 125665 filed on April 30, 2003, entire content of which is expressly incorporated by reference herein.
Industrial Applicability The present invention is suitable for use in a speech coding apparatus and speech decoding apparatus used in a communication system for coding and transmitting speech and/or sound signals.
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2F04017-PCT
CLAIMS
1. A speech coding apparatus comprising:
a base layer coder that codes an input signal and
generates first coded information;
a base layer decoder that decodes the first coded
information and generates a first decoded signal, while
generating long term prediction information comprising
information representing long term correlation of speech
or sound;
an adder that obtains a residual signal representing
a difference between the input signal and the first decoded
signal; and
an enhancement layer coder that calculates a long
term prediction coefficient using the long term prediction informationand the residual signal, and codes
the long term prediction coefficient and generate second
coded information.
2. The speech coding apparatus according to claim 1,
wherein the base layer decoder uses information
specifying a fetching position where an adaptive excitation vector is fetched from an excitation vector signal sample, as as the long term prediction information.
3. The speech coding apparatus according to claim 1, wherein the enhancement layer coder comprises:
a section that obtains a long term prediction lag
38

2F04017 —PCT



a section that decodes the long term prediction residual coded information and calculates a decoded long term prediction residual signal; and
a section that adds the new long term prediction
signal and the decoded long term prediction residual
signal , and updates the buffer using a result of addition.
5. A speech decoding apparatus that receives first
coded information and second coded information from the
speech coding apparatus according to claim 1 and decodes speech, said speech decoding apparatus comprising:
a base layer decoder that decodes the first coded information to generate a first decoded signal, while generating long term prediction information comprising
information representing long term correlation of speech or sound;
an enhancement layer decoder that decodes the second coded information using the long term prediction information and generates a second decoded signal; and
an adder that adds the first decoded signal and the second decoded signal, and outputs a speech or sound signal as a result of addition.
6. The speech decoding apparatus according to claim
5, wherein the base layer decoder uses information
specifying a fetching position where an adaptive excitation vector is fetched from an excitation vector
40

2F04017 —PCT
of an enhancement layer based on the long term prediction informat ion;
a section that fetches a long term predict ion signal the long term prediction lag back from a previous long term prediction signal sequence stored in a buffer;
a section that calculates the long term prediction coefficient using the residual signal and the long term prediction signal;
a section that codes the long term prediction coefficient and generates the enhancement layer coded informat ion;
a section that decodes the enhancement layer coded information and generates a decoded long term prediction coefficient; and a section that calculates a new long term prediction signal using the decoded long term predict ion coefficient and the long term predict ion signal, and updates the buffer using the new long term prediction signal.
4. The speech coding apparatus according to claim 3,
wherein the enhancement layer coder further comprises:
a section that obtains a long term prediction
residual signal representing a difference between the
residual signal and the long term prediction signal;
a section that codes the long term prediction residual signal and generates the long term prediction residual coded information;
39

2F04017 —PCT
signal sample, as the long term prediction information.
7. The speech decoding apparatus according to claim
5, wherein the enhancement layer decoder comprises:
a section that obtains a long term prediction lag of an enhancement layer based on the long term prediction informat ion;
a section that fetches a long term predict ion signal the long term prediction lag back from a previous long term prediction signal sequence stored in a buffer;
a section that decodes the enhancement layer coded information and obtains a decoded long term prediction coefficient; and
a section that calculates a long term prediction signal using the decoded long term predict ion coefficient and the long term prediction signal, updates the buffer using the long term prediction signal,
wherein the enhancement layer decoder uses the long term prediction signal as an enhancement layer decoded 20 signal.
8. The speech decoding apparatus according to claim
7, wherein the enhancement layer decoder further
comprises:
a section that decodes the long term prediction residual coded information and obtains a decoded long term prediction residual signal; and
40

2F04017 —PCT
a section that adds the long term prediction signal and the decoded long term prediction residual signal, wherein the enhancement layer decoder uses a result of addition as an enhancement layer decoded signal.
9. A speech signal transmission apparatus provided with a speech coding apparatus, wherein the speech coding apparatus comprises:
a base layer coder that codes an input signal and generates first coded information;
a base layer decoder that decodes the first coded
information and generates a first decoded signal, while
generating long term prediction information comprising
information representing long term correlation of speech
or sound;
an adder that obtains a residual signal representing a difference between the input signal and the first decoded signal; and
an enhancement layer coder which calculates a long
term prediction coefficient using the long term
prediction information and the residual signal, codes
the long term prediction coefficient, and generates
second coded information.
10. A speech signal reception apparatus provided with a speech decoding apparatus that receives first coded information and second coded information from the speech

2F04017 —PCT
coding apparatus according to claim 1 and decodes speech, said signal reception apparatus comprising:
a base layer decoder that decodes the first coded
information and generates a first decoded signal, while
generating long term prediction information comprising
information representing long term correlation of speech
or sound;
an enhancement layer decoder that decodes the second
coded information using the long term prediction
information and generates a second decoded signal; and
an adder that adds the first decoded signal and the second decoded signal, and outputs a speech or sound signal as a result of addition.
11. A speech coding method comprising:
coding an input signal and generating first coded information;
decoding the first coded information and generating
a first decoded signal, while generating long term
prediction information comprising information
representing long term correlation of speech or sound;
obtaining a residual signal representing a
difference between the input signal and the first decoded
signal; and
calculatinga long term predict ion coefficient using
the long term prediction information and the residual
signal, coding the long term prediction coefficient, and
43

2F04017-PCT
generating second coded information.
12. A speech decoding method for decoding speech using first coded information and second coded information generated in the speech coding method according to claim 11, the method comprising:
decoding the first coded information to generate a first decoded signal, while generating long term prediction information comprising information representing long term correlation of speech or sound; decoding the second coded information using the long term prediction information and generating a second decoded signal; and
adding the first decoded signal and the second decoded signal, and outputting a speech or sound signal as a result of addition.
13. A speech coding apparatus, a speech decoding apparatus, a speech signal transmission apparatus, a speech signal reception apparatus, a speech coding method and a speech decoding method substantially as herein described with reference to the accompanying drawings.
Dated this 26th day of October, 2005

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ABSTRACT
Base layer coding section 101 encodes an input signal to obtain base layer coded information. Base layer decoding section 102 decodes the base layer coded information to obtain a base layer decoded signal and long term prediction information (pitch lag). Adding section 103 inverts the polarity of the base layer decoded signal to add to the input signal, and obtains a residual signal. Enhancement layer coding section 104 encodes a
long term prediction coefficient calculated using the long term prediction information and the residual signal to obtain enhancement layer coded information. Base layer decoding section 152 decodes the base layer coded information to obtain the base layer decoded signal and
long term prediction information. Using the long term prediction information, enhancement layer decoding section 153 decodes the enhancement layer coded information to obtain an enhancement layer decoded signal . Adding section 154 adds the base layer decoded signal
and enhancement layer decoded signal to obtain a speech/sound signal. It is thereby possible to implement scalable coding with small amounts of calculation and coded information.
45

Documents:

1219-mumnp-2005-abstract(28-10-2005).doc

1219-mumnp-2005-abstract(28-10-2005).pdf

1219-MUMNP-2005-ABSTRACT(8-10-2008).pdf

1219-mumnp-2005-abstract.doc

1219-mumnp-2005-abstract.pdf

1219-MUMNP-2005-CLAIMS(8-10-2008).pdf

1219-mumnp-2005-claims(granted)-(28-10-2005).doc

1219-mumnp-2005-claims(granted)-(28-10-2005).pdf

1219-mumnp-2005-claims.doc

1219-mumnp-2005-claims.pdf

1219-mumnp-2005-correspondance-received-ver-071205.pdf

1219-mumnp-2005-correspondance-received-ver-261205.pdf

1219-mumnp-2005-correspondance-received.pdf

1219-mumnp-2005-correspondence(08-10-2008).pdf

1219-MUMNP-2005-CORRESPONDENCE(19-1-2009).pdf

1219-MUMNP-2005-CORRESPONDENCE(8-10-2008).pdf

1219-mumnp-2005-correspondence(ipo)(24-11-2008).pdf

1219-MUMNP-2005-DECLARATION BY THE TRANSLATOR(19-1-2009).pdf

1219-mumnp-2005-description (complete).pdf

1219-MUMNP-2005-DESCRIPTION(COMPLETE)-(8-10-2008).pdf

1219-mumnp-2005-drawing(28-10-2005).pdf

1219-MUMNP-2005-DRAWING(8-10-2008).pdf

1219-mumnp-2005-drawings.pdf

1219-mumnp-2005-form 1(08-10-2008).pdf

1219-mumnp-2005-form 1(09-12-2005).pdf

1219-mumnp-2005-form 1(26-10-2005).pdf

1219-mumnp-2005-form 1(28-10-2005).pdf

1219-MUMNP-2005-FORM 1(8-10-2008).pdf

1219-mumnp-2005-form 13(19-1-2009).pdf

1219-mumnp-2005-form 18(27-12-2005).pdf

1219-mumnp-2005-form 2(28-10-2005).pdf

1219-mumnp-2005-form 2(granted)-(28-10-2005).doc

1219-mumnp-2005-form 2(granted)-(28-10-2005).pdf

1219-MUMNP-2005-FORM 2(TITLE PAGE)-(28-10-2005).pdf

1219-mumnp-2005-form 26(01-12-2008).pdf

1219-mumnp-2005-form 26(16-11-2005).pdf

1219-MUMNP-2005-FORM 26(19-1-2009).pdf

1219-mumnp-2005-form 3(08-10-2008).pdf

1219-mumnp-2005-form 3(26-10-2005).pdf

1219-MUMNP-2005-FORM 3(8-10-2008).pdf

1219-mumnp-2005-form pct-ib-304.pdf

1219-mumnp-2005-form pct-isa-210(28-10-2005).pdf

1219-mumnp-2005-form pct-search- report.pdf

1219-mumnp-2005-form-1.pdf

1219-mumnp-2005-form-18.pdf

1219-mumnp-2005-form-2.pdf

1219-mumnp-2005-form-26.pdf

1219-mumnp-2005-form-3.pdf

1219-mumnp-2005-form-5.pdf

1219-mumnp-2005-pct- others.pdf

1219-mumnp-2005-petition under rule 137(08-10-2008).pdf

1219-MUMNP-2005-PETITION UNDER RULE 137(8-10-2008).pdf

abstract1.jpg


Patent Number 225722
Indian Patent Application Number 1219/MUMNP/2005
PG Journal Number 07/2009
Publication Date 13-Feb-2009
Grant Date 24-Nov-2008
Date of Filing 28-Oct-2005
Name of Patentee MATSUHITA ELECTRIC INDUSTRIAL CO., LTD.
Applicant Address 1006, OAZA KADOMA, KADOMA-SHI, OSAKA-571-8501
Inventors:
# Inventor's Name Inventor's Address
1 KAORU SATO 1-32-4-503, CHUO, NISHI-KU,YOKOHAMA-SHI KANAGAWA-220-0051
2 TOSHIYUKI MORII 3-1-12-304, NIJIGAOKA, ASAO-KU, KAWASAKI-SHI, KANAGAWA-215-0015
PCT International Classification Number G10L19/04
PCT International Application Number PCT/JP2004/006294
PCT International Filing date 2004-04-30
PCT Conventions:
# PCT Application Number Date of Convention Priority Country
1 2003-125665 2003-04-30 Japan