JP2012145954A - Multichannel signal coding method, encoder using the same, program by the method and recording medium therefor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enhance coding efficiency.SOLUTION: A multichannel signal coding method includes: a step for generating a linear predictive coefficient and a predictive residual signal from a parent channel signal; a step for determining the linear predictive coefficient with respect to a child channel signal so as to minimize a reference value of difference between a residual signal of the child channel signal and the parent channel residual signal; a step for using the child channel linear predictive coefficient to generate a residual signal of the child channel; a step for generating a residual difference signal through weighted subtraction of the parent channel residual signal and the child channel residual signal; and a step for, when an absolute value of PARCOR coefficient corresponding to the child channel linear predictive coefficient is not equal to or greater than a predetermined value, encoding and outputting the parent channel residual signal, the parent channel linear predictive coefficient, the child channel linear predictive coefficient, the residual difference signal and a weight coefficient.

Description

  The present invention relates to a method for compressing and encoding a multi-channel audio signal, an apparatus therefor, a program for executing the method on a computer, and a recording medium therefor.

As shown in Non-Patent Document 1, in conventional compression coding of a multi-channel signal, for example, Levinson's signal is used so as to minimize a reference value (energy, etc.) of a linear prediction residual signal closed to each channel. Linear prediction analysis is performed by Durbin, etc., and the residual signal obtained through the filter using the linear prediction coefficients a _j (i = 0, 1,…, P), (a ₀ = 1) obtained by the analysis The weighted subtraction process was performed. The concept of the encoding device is shown in FIG. In FIG. 1, each of the left channel signal and the right channel signal is subjected to linear prediction analysis to generate respective residual signals. One residual signal is encoded, and the two residual signals are weighted and subtracted. The result is encoded. However, it is assumed that the linear prediction coefficients here are processed into N-sample frames for each channel, including those converted into PARCOR coefficients or quantized and inversely converted. For example, the left channel input signal is x ^L (n) (n = 1, 2,…, N), the residual signal is e ^L (n) (n = 1, 2,…, N), and the P ^L order The prediction coefficient is a _i ^L (i = 1, 2,…, P ^L ), the right channel input signal is x ^R (n) (n = 1, 2,…, N), and the residual signal is e ^R (n ) (n = 1, 2, ..., n), P and ^R order prediction coefficients ^{_{a i R (i = 1,}} 2, ..., when the P ^R), the residual signal of each channel,

It can be expressed as. However, it is assumed that a ₀ ^L = 1 and a ₀ ^R = 1. In the previous method, the prediction coefficients a _i ^L ,
a _i ^R is the following formula for each frame of N samples.

It was determined to minimize the reference value taking the residual signal energy of each channel as an example. Subtraction processing with the channel with the smaller reference value determined here as the parent channel (subtracted channel) and the larger channel as the child channel (subtracted channel)

To obtain a weighted difference signal, which is used as an encoding target instead of the residual signal of the child channel. With this method, the code amount is reduced by reducing the reference value of the child channel, compared to the case where the residual signal itself is the target of encoding. Here, the weighting factor γ is, for example, energy after subtraction processing

Asking.

  A specific procedure in the prior art described in Non-Patent Document 1 will be described with reference to FIG. Here, the parent channel is an R channel and the child channel is an L channel.

The linear prediction analysis unit 11R performs linear prediction analysis on the input parent channel original signal x ^R (n) by a conventional linear prediction analysis method (Levinson Durbin, etc.), and predictive coefficients a _i ^R (i = 1, 2,... , P ^R ). The conversion unit 12R converts the prediction coefficient a _i ^R (i = 1, 2,..., P ^R ) into a PARCOR coefficient k _i ^R (i = 1, 2,..., P ^R ). The quantization unit 13R rounds down the input PARCOR coefficient k _i ^R (i = 1, 2,..., P ^R ), and quantizes the quantized PARCOR coefficient ^ k _i ^R (i = 1, 2,..., P ^R ) is output. The inverse transform unit 14R converts the input quantized PARCOR coefficient ^ k _i ^R (i = 1, 2,..., P ^R ) into the quantized prediction coefficient ^ a _i ^R (i = 1, 2,..., P ^R ). The linear prediction filter 21R uses the quantized prediction coefficient ^ a _i ^R (i = 1, 2,..., P ^R ) as a filter coefficient and the input parent channel original signal x ^R (n) as

To obtain a prediction residual e ^R (n). However, ^ a ₀ ^R = 1. The residual encoding unit 22R entropy encodes the prediction residual e ^R (n), for example, and outputs a residual code C _e ^R. The coefficient encoding unit 23R entropy-encodes the quantized PARCOR coefficient ^ k _i ^R (i = 1, 2,..., P ^R ), for example, and outputs a coefficient code C _k ^R. The code combining unit 24R combines the residual code C _e ^R and the coefficient code C _k ^R , and outputs a parent channel combined code C _g ^R. The code composition may be simply code combination.

The linear prediction analysis unit 31L performs linear prediction analysis on the input child channel original signal x ^L (n) by a conventional linear prediction analysis method (Levinson Durbin, etc.), and predictive coefficients a _i ^L (i = 1, 2,... , P ^L ). The conversion unit 32L converts the prediction coefficient a _i ^L (i = 1, 2,..., P ^L ) into a PARCOR coefficient k _i ^L (i = 1, 2,..., P ^L ). The quantization unit 33L quantizes the input PARCOR coefficient k _i ^L (i = 1, 2,..., P ^L ), and the quantized PARCOR coefficient ^ k _i ^L (i = 1, 2,..., P ^L ). Is output. The inverse transform unit 34L converts the input quantized PARCOR coefficient ^ k _i ^L (i = 1, 2,..., P ^L ) into the quantized prediction coefficient ^ a _i ^L (i = 1, 2,..., P ^L ). The linear prediction filter 41L filters the input parent channel original signal x ^L (n) by the following expression using the quantized prediction coefficients ^ a _i ^L (i = 1, 2,..., P ^L ) as filter coefficients. Obtain the prediction residual e ^L (n). However, ^ a ₀ ^L = 1.

The residual encoding unit 42L encodes the prediction residual e ^L (n) and outputs a residual code C _e ^L. The coefficient encoding unit 43L encodes the quantized PARCOR coefficient ^ k _i ^L (i = 1, 2,..., P ^L ) and outputs a coefficient code C _k ^L. The code synthesis unit 44L synthesizes the residual code C _e ^L and the coefficient code C _k ^L , and outputs a normal child channel synthesis code C _g ^L.

The weight calculation unit 51 uses the prediction residual e ^R (n) and the prediction residual e ^L (n) to obtain a weight coefficient γ from the following equation.

The weight quantization unit 52 quantizes the weight coefficient γ to obtain a quantized weight coefficient ^ γ. The weighted subtraction processing unit 53 uses the prediction residual e ^R (n), the prediction residual e ^L (n), and the quantized weight coefficient ^ γ to calculate the difference signal ~ e ^M (n) from the following equation. obtain.

The residual encoding unit 61M encodes the residual difference signal ~ e ^M (n) and outputs a residual code C _e ^M. The weight encoding unit 62M encodes the quantized weight coefficient ^ γ and outputs a weight code C _w ^M. The code synthesis unit 63M synthesizes the residual code C _e ^M , the weight code C _w ^M, and the coefficient code C _k ^L obtained by the coefficient coding unit 43L, and outputs a subtractor channel synthesis code C _g ^M.

The code amount comparison unit 71 compares the code amounts of the normal child channel composite code C _g ^L and the subtractor channel composite code C _g ^M , and outputs the smaller one as a child channel code. This is the conventional method.

JP 2005-115267 A

Yu Kamamoto, Takehiro Moriya, Takuya Nishimoto, Shigeki Hiyama, “Reversible compression coding of multi-channel signals using inter-channel correlation”, Transactions of Information Processing Society of Japan (Vol.46, No.5, pp.1118- 1128)

  In the prior art, even when the input is two or more channels, the linear prediction coefficient calculated so that the energy of the linear prediction residual expressed by, for example, equations (3) and (4) becomes small for each channel. Was doing linear predictive analysis. However, the energy of the residual difference signal shown in Equation (10), which is to be encoded in the child channel, is not minimum, and the amount of code when the residual difference signal is entropy encoded is It cannot always be reduced, and it cannot be said that efficient encoding is performed.

  An object of the present invention is to provide a multi-channel signal encoding method capable of encoding more efficiently than before, an apparatus therefor, a program according to the method, and a recording medium for recording the program.

According to one aspect of the present invention, a multi-channel encoding method for generating a code corresponding to a signal of a plurality of channels input for each frame composed of a plurality of samples,
A first channel linear prediction analysis step of linearly predicting and analyzing a signal of at least one channel, hereinafter referred to as a first channel, to generate a first channel linear prediction coefficient and a first channel residual signal;
The second channel linear prediction coefficient so that the reference value of the difference between the residual signal and the first channel residual signal from the signal of at least one channel other than the first channel, hereinafter referred to as the second channel, is minimized. A linear prediction analysis step using inter-channel correlation that generates a residual signal of the second channel signal as a second channel residual signal based on the second channel linear prediction coefficient;
A weighted subtraction step of generating a residual difference signal by a weighted subtraction process between the first channel residual signal and the second channel residual signal;
The PARCOR coefficient corresponding to the first channel linear prediction coefficient and the first channel residual signal are encoded to output a first channel code, and at least the PARCOR coefficient corresponding to the second channel linear prediction coefficient and the residual difference are output. An encoding step of encoding a signal and outputting a second channel code;
A second channel linear prediction analysis step of generating a second channel second linear prediction coefficient and a second channel second residual signal by performing a linear prediction analysis on the second channel signal;
A second channel second encoding step of encoding the second channel second residual signal and the PARCOR coefficient corresponding to the second channel second linear prediction coefficient and outputting a second channel second code;
Code selection for outputting the second channel second code if at least one absolute value of the PARCOR coefficient corresponding to the second channel linear prediction coefficient is equal to or greater than a predetermined value, and outputting the second channel code otherwise. Steps,
including.

A second channel linear prediction analysis step of generating a second channel second linear prediction coefficient and a second channel second residual signal by performing a linear prediction analysis on the second channel signal;
A second channel second encoding step of encoding the second channel second residual signal and the PARCOR coefficient corresponding to the second channel second linear prediction coefficient and outputting a second channel second code;
Code selection for outputting the second channel second code if at least one absolute value of the PARCOR coefficient corresponding to the second channel linear prediction coefficient is equal to or greater than a predetermined value, and outputting the second channel code otherwise. Steps,
including.

  According to the present invention, since the linear prediction coefficient of the child channel is determined so that the child channel residual signal approaches the parent channel residual signal, it is possible to make the reference value of the residual difference signal smaller than that in the prior art. Thus, it is possible to perform more efficient coding with a small code amount of the child channel.

The block diagram which shows the concept of the conventional multichannel encoding. The block diagram which shows the example of the conventional multichannel encoding apparatus. The flowchart which shows the basic process sequence of the multichannel encoding method by this invention. 1 is a block diagram showing a first embodiment of a multi-channel encoding device according to the present invention. The block diagram which shows the modification 3 of Example 1 of this invention. The block diagram which shows the process which replaced the left-right channel signal in FIG. FIG. 7 is a block diagram showing a modified example 4 according to FIGS. 4 and 6. FIG. 9 is a block diagram showing a fifth modified example of the first example. FIG. 11 is a block diagram showing a sixth modified example of the first example. The block diagram which shows Example 1 by approximation. The figure which shows the deformation | transformation Example of Example 1 by approximation. The block diagram which shows the other modification of Example 1 by approximation. The block diagram which shows Example 2 by approximation. The block diagram which shows the modification of Example 2 by approximation. The graph which shows the effect of this invention.

Principle of the Invention According to the present invention, a total reference value (in other words, a reference value of an actually encoded signal), for example, a residual signal energy reference of a parent channel and a child channel residual signal energy reference after subtraction processing. Sum of

Is determined to be a linear prediction coefficient for obtaining a child channel residual signal. That is, the linear prediction coefficient may be calculated so that the child channel residual signal resembles the parent channel residual signal.

The process for obtaining the weighted residual signal child channel using the residual signal of the residual signal and the child channels Calculation examples parent channel of the linear prediction coefficients of the child channels, in practice the formula (5) or (10 ) May be performed instead of the one-tap subtraction process shown in FIG. 1 (Patent Document 1), but here a one-tap subtraction process is used for easy understanding. For the sake of explanation, it is assumed that the linear prediction coefficient of the R channel that is the parent of the subtraction process remains fixed and the number of channels is also two. Then, the L channel is used as a child channel of the subtraction process, and the linear prediction coefficient of the L channel is calculated by the new method adopted in the present invention. Under such conditions, the total energy of the two channels when the number of samples is N is

It is. Here, as described above, the weight coefficient γ is such that the energy after the subtraction process is minimized, as described above.

It becomes. In the present invention, so that this equation (13) is minimized, obtaining the linear prediction coefficient partial differential ∂E ^total / ∂a _i ^L becomes zero in a linear prediction coefficients of each order of equation (13) (where , I = 1, 2,…, P ^L ). If partial differentiation of equation (13) with the prediction coefficient a _i ^L on the child channel side, the term of E ^R in equation (13) is 0, so that the sum of the second term and the third term is minimized. A linear prediction coefficient is obtained. That is, a linear prediction coefficient is determined so as to make the child channel residual signal e ^L (n) close to the parent channel residual signal e ^R (n) in equation (11). Here, the autocorrelation R (τ) of the child channel signal and the cross-correlation C (τ) between the residual signal of the parent channel and the child channel signal are expressed as follows:

In order to determine the linear prediction coefficient a _k ^L that minimizes the equation (13), the equation (13) is partially differentiated by the coefficients a _i ^L (i = 1, 2,…, P ^L ),

It becomes. ∂E ^total / ∂a _i ^L = 0 (i = 1, 2,…, P ^L ) and a ₀ ^L = 1

It becomes. Solving Equation (17) with respect to the linear prediction coefficients a _i ^L (i = 1, 2,…, P ^L )

It becomes. By solving equation (18), it is possible to obtain the linear prediction coefficients a _i ^L (i = 1, 2,..., P ^L ) of the child channel that minimizes E ^total . This equation type can be solved using well-known algorithms such as Cholesky decomposition.

The term of the cross-correlation C (τ) contained in each element of the matrix of equation (18) is introduced by the present invention, and on the other hand, prediction is made so that the residual signal energy is minimized for each channel. The conventional method for determining the coefficient does not include such a term of the cross-correlation C (τ), and is expressed only by the term of the autocorrelation R (τ). Using the linear prediction coefficient a _i ^L (i = 1, 2,…, P ^L ) determined in this way,
7) Obtaining the residual signal of the child channel signal, obtaining the weighting coefficient γ of equation (9), and performing weighted subtraction processing of equation (10) enables encoding with higher compression efficiency than in the past. . Note that the linear channel prediction coefficient a _i ^R (i = 1, 2,..., P ^R ) is determined so as to minimize the residual signal energy of the parent channel signal, that is, Equation (4), as in the past. That's fine.

Basic Procedure of Multi-Channel Coding According to the Present Invention FIG. 3 shows an example of a basic encoding processing procedure of a multi-channel signal according to the present invention.

  In the present invention, when a multi-channel input signal is encoded, it may be determined in advance which channel signal is input as a parent channel signal or a child channel signal, or is determined by this encoding apparatus. (See Non-Patent Document 1 for details on how to determine parent and child). For example, it is assumed here that the right channel signal is input as a parent channel signal and the left channel signal is input as a child channel signal. First, the residual signal of the parent channel signal is obtained by, for example, equation (2) (step S1). A linear prediction coefficient for the child channel is determined so that the reference value of the difference signal from the child channel residual signal, for example, energy, is minimized with respect to the obtained parent channel residual signal (step S2). Specifically, this is obtained by solving the equation (18). A residual signal of the child channel signal is generated using the obtained prediction coefficient (step S3). A residual difference signal is generated by weighted subtraction processing of the parent channel residual signal and the child channel residual signal (step S4). The parent channel prediction coefficient, parent channel residual signal, child channel prediction coefficient, residual difference signal, and weighting coefficient are encoded (step S5).

Example 1
FIG. 4 shows a block diagram of an encoding apparatus when the present invention is applied to encoding of a stereo signal. 2 is different from the configuration of the prior art in FIG. 2 in that a linear prediction analysis unit 54M using inter-channel correlation is provided instead of the child channel linear prediction analysis unit 31L in FIG. 2, and a residual encoding unit 42L, a code synthesis unit 44L, that corresponding to the code amount comparison unit 71 is not provided. Also, the child channel conversion unit 32L, quantization unit 33L, inverse conversion unit 34L, linear prediction filter 41L, and coefficient encoding unit 43L in FIG. 2 are respectively replaced with the same configuration units 55M to 58M and 64M in FIG. ing.

  The configuration including the linear prediction analysis unit 11R, the conversion unit 12R, the quantization unit 13R, the inverse conversion unit 14R, and the linear prediction filter 21R in FIG. 4 corresponds to the first channel linear prediction analysis unit in claim 18. The configuration including the linear prediction analysis unit 54M, the conversion unit 55M, the quantization unit 56M, the inverse conversion unit 57M, and the linear prediction filter 58M using the inter-channel correlation in FIG. Corresponds to analysis means. The configuration including the weight calculation unit 51, the weight quantization unit 52, and the weighted subtraction processing unit 53 in FIG. 4 corresponds to the weighted subtraction means in claim 18. The configuration including the residual encoding unit 22R, the coefficient encoding unit 23R, and the code synthesis unit 24R in FIG. 4 corresponds to the first channel encoding means in claim 18. The configuration including the residual encoding unit 61M, the weight encoding unit 62M, the code synthesis unit 63M, and the coefficient encoding unit 64 in FIG. 4 corresponds to the second channel encoding means in claim 18. These correspondences also apply to the following embodiments.

The right channel original signal of a frame (N samples) is x ^R (n) (n = 1, 2,..., N), and the left channel original signal is x ^L (n) (n = 1, 2,. N). Here, the right channel is a parent channel and the left channel is a child channel.

The linear prediction analysis unit 11R converts the input parent channel signal x ^R (n) into a conventional linear prediction analysis method (
The prediction coefficient a _i ^R (i = 1, 2,..., P ^R ) is obtained by performing linear prediction analysis using Levinson Durbin et al. Conversion unit 12R prediction coefficients ^{_{a i R (i = 1,}} 2, ..., P R) PARCOR coefficients ^{_{k i R (i = 1,}} 2, ..., P R) to convert. PARCOR coefficient quantizer 13R is input ^{_{k i R (i = 1,}} 2, ..., P R) is quantized and quantized PARCOR coefficient ^{_{^ k i R (i = 1}} , 2, ..., P R) Is output. Inverse transform unit 14R is inputted quantized PARCOR coefficient ^{_{^ k i R (i = 1}} , 2, ..., P R) the quantized prediction coefficients ^{_{^ a i R (i = 1}} , 2, ..., P R ). The linear prediction filter 21R uses the quantized prediction coefficient ^ a _i ^R (i = 1, 2,..., P ^R ) as a filter coefficient to filter the input parent channel original signal x ^R (n) by Obtain the residual e ^R (n). However, ^ a ₀ ^R = 1.

The residual encoding unit 22R encodes the prediction residual e ^R (n) and outputs a residual code C _e ^R. The coefficient encoding unit 23R encodes the quantized PARCOR coefficient ^ k _i ^R (i = 1, 2,..., P ^R ) and outputs a coefficient code C _k ^R. The code combining unit 24R combines the residual code C _e ^R and the coefficient code C _k ^R , and outputs a parent channel combined code C _g ^R.

The linear prediction analysis unit 54M using the inter-channel correlation performs the following Step 1 to Step 3.
Step1: Child-channel signal is input x ^L (n) from using equation (14) P ^M autocorrelation up next R (τ) (τ = 0 , 1, ..., P M) is calculated.
Step2: correlation of the input child channel signal x ^L (n) and the prediction residuals e ^R (n) using Equation (15) to P ^M The following C (τ) (τ = 0 , 1, ..., P ^M ) is calculated.
Step 3: Using R (τ) (τ = 0, 1,…, P ^M ) obtained in Step 1 and C (τ) (τ = 0, 1,…, P ^M ) obtained in Step 2, Prediction coefficients a _i ^M (i = 1, 2,..., P ^M ) taking into account cross-correlation are obtained from the equation.

The conversion unit 55M converts the prediction coefficient a _i ^M (i = 1, 2,..., P ^M ) into a PARCOR coefficient k _i ^M (i = 1, 2,..., P ^M ). The quantization unit 56M quantizes the input PARCOR coefficient k _i ^M (i = 1, 2,..., P ^M ), and the quantized PARCOR coefficient ^ k _i ^M (i = 1, 2,..., P ^M ). Is output. The inverse transform unit 57M converts the input quantized PARCOR coefficients ^ k _i ^M (i = 1, 2,..., P ^M ) into quantized prediction coefficients ^ a _i ^M (i = 1, 2,..., P ^M ). The linear prediction filter 58M uses the quantized prediction coefficient ^ a _i ^M (i = 1, 2,..., P ^M ) as a filter coefficient, and predicts the input child channel signal x ^L (n) by the following expression. Obtain the residual e ^M (n). However, ^ a ₀ ^M = 1.

The weight calculation unit 51 obtains a weighting coefficient γ from the following equation using the prediction residual e ^R (n) of the parent channel and the prediction residual e ^M (n) considering the cross correlation.

The weight quantization unit 52 quantizes the weight coefficient γ to obtain a quantized weight coefficient ^ γ. The weighted subtraction processing unit 53 obtains a residual difference signal ~ e ^M (n) from the following equation using the prediction residuals e ^R (n), e ^M (n) and the quantized weight coefficient ^ γ. .

The residual encoding unit 61M encodes the residual difference signal ~ e ^M (n) and outputs a residual code C _e ^M. The coefficient encoding unit 64M encodes the quantized PARCOR coefficient ^ k _i ^M (i = 1, 2,..., P ^M ) and outputs a coefficient code C _k ^M. The weight encoding unit 62M encodes the quantized weight coefficient ^ γ and outputs a weight code C _w ^M. The code combining unit 63M combines the residual code C _e ^M , the weight code C _w ^M, and the coefficient code C _k ^M , and outputs a child channel combined code C _g ^M.

In the present invention, obtaining the linear prediction coefficient in consideration of the cross-correlation means that the cross-correlation C (τ) is introduced into at least one element of the matrix and the inverse matrix in the equation (18 ′). That is. In the equation (18 ′), one having a small cross-correlation C (τ) may be approximated to zero. For example, if the cross-correlation C (0), C (1), C (2) is expected to be large, C (1) ² ,
C (1) C (2), C (2) ² , C (0) C (1), C (0) C (2), etc. It is also good.

Modified Example 1
As processing of the weighted subtraction processing unit 53, for example, it is known to perform weighted subtraction processing of a plurality of taps or weighted subtraction processing of a plurality of taps considering a time difference (Patent Document 1). Also in the present invention, a signal after weighted subtraction processing of a plurality of taps (j = -1, 0, 1) in the equation (11),

And the signal after weighted subtraction with multiple taps taking into account the time difference (sample number interval τ),

The prediction coefficient may be obtained so that is minimized.

  As described above, according to the weighted subtraction process with a plurality of taps, the child channel residual signal can be controlled to be closer to the parent channel residual signal, so that the code amount can be reduced accordingly. For example, even when the sound source position of the left and right channel signals is shifted from the center to one side, the weight at the tap position according to the arrival time difference from the sound source to the two microphones can be controlled, so that the code compression rate can be reduced. Can be improved.

Modified Example 2
Equation (18 ′) may be modified as follows and solved as in the covariance method. Where the autocorrelation of equation (14) is

  According to the method of the second modified embodiment, the calculation amount is larger than that in the first embodiment, but there is an advantage that the analysis accuracy is increased.

Modified Example 3
In the example of FIG. 4, the case where the parent-child relationship has been determined has been described as an example. However, each prediction residual may be obtained once and the analysis may be performed using the smaller energy as the parent channel. A modified embodiment is shown in FIG. In this modified example, a linear prediction analysis unit 31L, a conversion unit 32L, a quantization unit 33L, an inverse conversion unit 34L, and a linear prediction filter 41L similar to those in FIG. 2 are added to the configuration in FIG. Corresponds to the second channel second linear prediction analysis means in claim 19), the same processing is performed on the left channel signal to obtain a residual signal e ^L (n). Further, a comparison unit 45L and an input switching unit 2 are provided. The energy of the residual signal e ^R (n) from the linear prediction filter 21R on the parent channel side and the energy of the child channel residual signal e ^L (n) are calculated by, for example, equations (4) and (3), and the smaller one is calculated. The input signal of the channel is determined as the parent channel signal, and the input signal of the larger channel is determined as the child channel signal, and the input switching unit 2 is switched and controlled accordingly. The subsequent processing is the same as in FIG. Note that the comparison by the comparison unit 45L shows a case where energy of residual signals is compared, but a sum of absolute values or a comparison of code amounts may be used.

Modified example 4
The code amount obtained in the embodiment of FIG. 4 and the right channel signal x ^R (n) in FIG. 4 as the input of the child channel and the left channel signal x ^L (n) as the input of the parent channel (ie, the parent-child relationship) It is also possible to perform the encoding again as shown in FIG. 6 and output the smaller one compared to the code amount in the case of FIG. For example, as shown in FIG. 7, the encoding device shown in the configuration of FIG. 4 (or FIG. 6) is the encoding unit 3 of this modified example, and the input switching unit 2 is provided on the input side of the encoding unit 3. The selection output unit 4 is provided on the output side. The selection output unit 4 includes storage units 4A and 4B that hold a set of codes from the code synthesis units 24R and 63M of FIG. 4 (or FIG. 6) constituting the encoding unit 3, and the storage units 4A and 4B. A code amount comparison unit 4C that calculates the code amount of the retained code set and determines which is smaller, and a selection unit 4D that selectively outputs the code set that is determined to be smaller are provided. .

First, the input switching unit 2 inputs the right channel signal as a parent channel signal and the left channel signal as a child channel signal to the encoding unit 3, and performs encoding processing as shown in FIG. The output codes C _g ^R and C _g ^M are held in the storage unit 4A, for example.

Next, the input switching unit 2 is switched so that the right channel signal is input to the encoding unit 3 as a parent channel signal and the right channel signal is input to a coding unit 3 as shown in FIG. Process). M used in a symbol representing a signal or code in FIG. 4 is changed to M2 in the process of FIG. The symbol γ in FIG. 4 is changed to γ ₂ . Output codes C _g ^L and C _g ^{M2 obtained} by the encoding process of FIG. 6 are held in the storage unit 4B.

The code amount of the code C _g ^R + C _g ^M held in the storage unit 4A and the code C _g ^L + C _g ^M2 held in the storage unit 4B are respectively calculated by the code amount comparison unit 4C. select the better the selection output section 4D small, a set of the selected code, any channel and outputs the information C ^C indicating whether a parent channel (or child channels).

  According to this method, it is possible to perform encoding with higher efficiency than in the case of determining the parent channel and the child channel by comparing the energy of the right channel residual signal and the right channel residual signal energy.

Modified Example 5
For the child channel, C _g ^L obtained by combining the coefficient code C _k ^L and the residual code C _e ^L obtained by performing normal linear prediction analysis, and C _g ^M obtained in the embodiment of FIG. It is also possible to output the smaller code amount by comparing them in the code amount comparison unit. A modified embodiment is shown in FIG. This modified embodiment is similar to the embodiment of FIG. 4 in that the linear prediction analysis unit 31L, the conversion unit 32L, the quantization unit 33L, the inverse conversion unit 34L, the linear prediction filter 41L, and the residual encoding unit 42L are the same as in FIG. A coefficient encoding unit 43L, a code synthesizing unit 44L, and a code amount comparing unit 71 are added, and the same processing as in the case of FIG. 2 is performed.

The linear prediction analysis unit 31L, the conversion unit 32L, the quantization unit 33L, the inverse conversion unit 34L in FIG.
The configuration including the linear prediction filter 41L corresponds to the second channel linear prediction analysis means in claim 21. The configuration including the residual encoding unit 42L, the coefficient encoding unit 43L, and the code combining unit 44L in FIG. 8 corresponds to the second channel second encoding means in claim 21.

The combined code C _g ^L from the code combining unit 44L and the combined code C _g ^M from the code combining unit 63M are given to the code amount comparing unit 71 and their code amounts are compared, and the smaller combined code is selected. It outputs as the code | symbol of a child channel with the information showing which was selected. According to this embodiment, when the code amount is smaller when the subtraction process is not performed, the result of the normal linear prediction analysis is used, so that the compression rate is not always deteriorated as compared with the conventional method.

Modified Example 6
In the embodiment of FIG. 4, if there is a PARCOR coefficient k _i ^M generated by the conversion unit 55M having an absolute value of 1 or more, linear prediction based on the linear prediction coefficient a _i ^M obtained by inversely converting those coefficients. The operation of the filter 58M may become unstable. Therefore, in the modified embodiment of FIG. 8, instead of comparing the code amounts of the composite codes C _g ^L and C _g ^{M by} the code amount comparison unit 71 and outputting the smaller one, the PARCOR coefficient obtained by the conversion unit 55M is output to the PARCOR coefficient. You may decide which to choose depending on. An example is shown in FIG. In the modified example of FIG. 9, a code selection unit 72 is provided instead of the code amount comparison unit 71 in the modified example of FIG. 8.

  The configuration including the linear prediction analysis unit 31L, the conversion unit 32L, the quantization unit 33L, the inverse conversion unit 34L, and the linear prediction filter 41L in FIG. 9 corresponds to the second channel linear prediction analysis unit in claim 22. The configuration including the residual encoding unit 42L, the coefficient encoding unit 43L, and the code synthesizing unit 44L in FIG. 9 corresponds to the second channel second encoding means in claim 22.

PARCOR coefficient P ^M pieces obtained code selecting section 72 by the conversion unit ^{_{55M k i M (i = 1}} , 2, ..., P M)
Of the at least any one of the absolute value the threshold value (e.g. 1) similar to the above case of the conventional composite code C _g ^L coefficients, otherwise outputs a composite code C _g ^M as a child channel code. When the former is selected, the quantization unit 56M, inverse transform unit 57M, linear prediction filter 58M, residual encoding unit 61M, weight encoding unit 62M, code synthesis unit 63M, coefficient encoding unit 64M, and the like are performed. Since there is no need, the amount of processing can be reduced.

Example 1 by approximation
FIG. 10 shows an implementation in the case where the calculation of the equation (18 ′) by the linear prediction analysis unit 54M using the correlation between channels in the embodiment of FIG. 4 is approximated by the following equation using the weight coefficient γ ₀ of the previous frame. An example is shown.

From this approximate expression, linear prediction coefficients a _i ^M (i = 1, 2,..., P ^M ) are obtained.

A different part from FIG. 4 is demonstrated using FIG. 10 further includes a weight coefficient holding unit 73 in addition to FIG. The weighting coefficient holding unit 73 gamma weighting factor of the previous frame is held as a provisional weighting coefficient gamma _0. Linear prediction analysis unit M using inter-channel correlation
54 performs the following Step 1 to Step 3.
Step1: From the input child channel signal x ^L (n), autocorrelation R (τ) is set to τ = 0, 1,… using equation (14)
, P ^M respectively.
Step 2: From the input child channel signal x ^L (n) and the prediction residual e ^R (n), using equation (15), the cross-correlation C (
The τ) τ = 0, 1, ..., are respectively calculated for P ^M.
Step3: Provisional weighting factor γ ₀ and R (τ) (τ = 0, 1,…, P ^M ) obtained in Step 1 and C (τ) (τ = 0, 1,…, P ^M ) obtained in Step 2 ) To obtain the prediction coefficient a _i ^M (i = 1, 2,..., P ^M ) from the equation (28).
The subsequent processing is the same as in FIG. According to this embodiment, the processing amount can be reduced as compared with the case of FIG. Note that the quantized weight coefficient ^ γ of the previous frame may be used as the temporary weight coefficient γ ₀ as indicated by a broken line as the weight coefficient of the previous frame.

Modification 1 of Example 1 by approximation
In FIG. 11, the provisional weighting coefficient γ ₀ is not based on that of the previous frame, but once with respect to the parent channel signal x ^R (n) and the child channel signal x ^L (n) according to the equations (1) and (2). An embodiment in the case where the provisional weight coefficient γ ₀ is obtained from a residual signal obtained by performing normal linear prediction will be described.

  A different part from FIG. 10 of the structure of FIG. 11 is demonstrated. In FIG. 11, a weight calculation unit 50 is provided instead of the weight coefficient holding unit 73 provided in FIG. In FIG. 11, a linear prediction analysis unit 31L, a conversion unit 32L, a quantization unit 33L, an inverse conversion unit 34L, and a linear prediction filter 41L are further added.

The linear prediction analysis unit 31L converts the input child channel signal x ^L (n) into a conventional linear prediction analysis method (
The prediction coefficient a _i ^L (i = 1, 2,..., P ^L ) is obtained by performing a linear prediction analysis using Levinson Durbin et al. The conversion unit 32L converts the prediction coefficient a _i ^L (i = 1, 2,..., P ^L ) into a PARCOR coefficient k _i ^L (i = 1, 2,..., P ^L ). The quantization unit 33L quantizes the input PARCOR coefficient k _i ^L (i = 1, 2,..., P ^L ), and the quantized PARCOR coefficient ^ k _i ^L (i = 1, 2,..., P ^L ). Is output. The inverse transform unit 34L converts the input quantized PARCOR coefficient ^ k _i ^L (i = 1, 2,..., P ^L ) into the quantized prediction coefficient ^ a _i ^L (i = 1, 2,..., P ^L ). The linear prediction filter 41L uses the quantized prediction coefficient ^ a _i ^L (i = 1, 2,..., P ^L ) as a filter coefficient, and filters the input parent channel signal x ^L (n) with the following expression for prediction. Obtain the residual e ^L (n). However, ^ a ₀ ^L = 1.

The weight calculation unit 50 obtains a temporary weight coefficient γ ₀ from the following equation using the prediction residual signals e ^R (n) and e ^L (n).

The linear prediction analysis unit 54M using the inter-channel correlation obtains a prediction coefficient by performing the same processing (Step 1 to Step 3) as in the first embodiment by the above approximation using the provisional weight coefficient γ ₀ . The subsequent processing is the same as in FIG. 4 and FIG.

According to the embodiment of FIG. 11, since the prediction residual is obtained from the child channel signal by the normal linear prediction analysis and the weighting coefficient is calculated using the prediction residual, the processing amount is increased and the processing time is also increased. However, since the provisional weighting coefficient γ ₀ having a more appropriate value can be determined as compared with the case of FIG. 10, the analysis accuracy in the linear prediction analysis unit 54M using the inter-channel correlation can be improved.

Modification 2 of Embodiment 1 by approximation
In the embodiment of FIG. 10, has been calculated by the equation (21) a weight coefficient gamma by the weight calculation unit 51, the weighting factor may be a fixed value gamma _0. An embodiment in that case is shown in FIG. In this embodiment, the weight calculation unit 51 in FIG. 10 is omitted, and a fixed value γ ₀ is held in advance as a weighting factor in the weighting factor holding unit 73. The weight coefficient γ ₀ is given to the linear prediction analysis unit 54M and the weight quantization unit 52 using the inter-channel correlation. The linear prediction analysis unit 54M using the inter-channel correlation calculates linear prediction coefficients a _i ^M (i = 1, 2,..., P ^M ) by using the fixed weight coefficient γ _{0 according} to the equation (28). The weighted subtraction processing unit 53 performs subtraction processing using a fixed quantization weight coefficient ^ γ ₀ in place of the weight coefficient ^ γ in equation (22). The weight encoding unit 62M encodes the quantization weight coefficient ^ γ ₀ .

In the embodiment of FIG. 12, if the value of the fixed weight coefficient γ ₀ is known in advance to the decoding side,
The weight encoding unit 62M is not necessary. Further, when the value of the weight coefficient γ ₀ is fixed to γ ₀ = 1, the linear prediction analysis unit 54M using the inter-channel correlation calculates the linear prediction coefficient with γ ₀ = 1 in the equation (28), and weights The subtraction processing unit 53 may perform subtraction with the weight coefficient ^ γ = 1 in the equation (22). Therefore, the weight coefficient holding unit 73, the weight quantization unit 52, and the weight encoding unit 62M are unnecessary.

Example 2 by approximation
In the embodiment based on the approximate correlation shown in FIG. 13, the child channel signal x ^L (n)
For the parent channel residual signal e ^R (n)

The weighted subtraction process is performed as follows. A prediction residual signal is obtained from the child channel signal x ^L (n) using a prediction coefficient obtained by performing linear prediction analysis on the signal ~ x ^M (n) subjected to such preprocessing. The provisional weighting coefficient γ ₀ here is the weighting coefficient γ of the previous frame.

  The configuration of the embodiment of FIG. 13 is the same as the linear prediction analysis unit 54M using the inter-channel correlation in the embodiment of FIG. 10 and the linear prediction using the approximate correlation between channels comprising the correlation approximating unit 54M1 and the linear prediction analyzing unit 54M2. It is replaced by the analysis unit 54M.

The weighting coefficient holding unit 73 gamma weighting factor of the previous frame is held as a provisional weighting coefficient gamma _0. The correlation approximating unit 54M1 uses the child channel signal x ^L (n), the parent channel residual signal e ^R (n), and the provisional weighting coefficient γ ₀ to calculate the difference signal ^ x ^M (n ) Is output. The provisional weighting coefficient γ ₀ is calculated as the weighting coefficient γ by the equation (21) in the previous frame. The numerator of formula (21) corresponds to the cross-correlation C (0) when τ = 0 in formula (15). Thus, this embodiment using equation (31) uses the cross-correlation C (0) of the previous frame instead of the cross-correlation C (0) of the current frame, ie approximated by the cross-correlation of the previous frame. It can be said. The linear prediction analysis unit 54M2 performs linear prediction analysis on the input difference signal ^ x ^M (n) by a conventional linear prediction analysis method (Levinson Durbin, etc.), and the prediction coefficient a _i ^M (i = 1, 2,…, P ^M ). The subsequent processing is the same as in FIG.

  According to this embodiment, since it is not necessary to solve the equation (18 '), the equation (27), or the equation (28), high-speed processing is possible. This embodiment may be applied to each of the embodiments shown in FIGS.

Modified Example of Second Embodiment by Approximation As shown in FIG. 14, the linear prediction analysis unit 54M using the approximate correlation using the linear prediction analysis unit 54M using the inter-channel correlation in the example of FIG. It may be replaced with 54M. The description of the operation is omitted. This embodiment may be applied to each of the embodiments shown in FIGS.

Example 3 by approximation
In the linear prediction analysis unit 54M using the inter-channel correlation shown in FIG. 4 or the like, the intra-frame energy {˜e of the difference signal between the parent channel residual signal and the child channel residual signal shown in Equation (11) as a reference value The linear prediction coefficient of the child channel signal was determined so that ^L (n)} ² was minimized.
The following formula as a reference value

It is conceivable to use the sum of absolute values (amplitude values) of difference signals as shown in FIG. However, in that case, the residual signal is a linear function of the prediction coefficient, so if the absolute value is differentiated by the prediction coefficient as in equation (16), it becomes a constant value or cannot be differentiated at the origin, and the absolute value of the residual difference signal The minimum value of the reference value J cannot be determined by the method of differentiating the value as it is. So, for example, the absolute value function

Approximate with a continuous function. Here, δ is a constant, and q is, for example, q = 2 for easy calculation. Therefore,

It becomes. When the equation (34) (e _n ^M -γe _n ^R) sufficiently larger than δ can be approximated as ^{_{E (e n M) = 2}} (e n M -γe n R). When (e _n ^M -γe _n ^R) is less than δ, since can be approximated by equation (35) from (e _n ^M -γe _n ^R) of the differential is a linear function ^{_{2 (e n M -γe n R}} ) (e _n ^M −γe _n ^R ) can be approximated by a quadratic function. The weighting factor γ
As in the second embodiment based on the approximation in FIG. 12, the weighting factor of the previous frame may be used, or the weighting factor calculated by the equation (6) may be used.

  The sum J (corresponding to the code amount) of the entire frame as a reference value based on the difference signal absolute value thus approximated is

Can be calculated by In order to minimize the approximate absolute value of the differential signal, solve the problem by setting the partial differentiation with respect to the prediction coefficient a _i ^M (i = 1, 2,…, P ^M ) to 0 as shown in the following equation (37). Good.

The provisional residual difference signal (e _n ^M −γe _n ^R ) is a function of the prediction coefficient a _i ^M as in the equation (1). That is, it is only necessary to solve P ^M simultaneous equations for a _i ^M of i = 1, 2,..., P ^M where dJ / da _i ^M = 0.

  According to this embodiment, although processing time is required, an improvement in compression rate can be expected, and therefore a reduction in code amount can be expected. This embodiment may be applied to each of the embodiments shown in FIGS.

Modified Example of Example 3 by Approximation In Example 3 by the above-described approximation, the prediction coefficient can also be obtained using the steepest descent method (gradient descent method) without setting Equation (38) to 0. That is, it is obtained by the following process using the input child channel signal x ^L (n), the parent channel residual signal e _n ^R, and the provisional weight coefficient γ.
Step 1: Obtain prediction coefficients a _i ^M (i = 1, 2,..., P ^M ) from child channel signals using normal linear prediction analysis. Where the coefficient vector is

It will be expressed as
Step2: Gradient according to equation (38)

Ask for.
Step3: Prediction coefficient is

Update with α (n) determines the distance of movement in the opposite direction of the gradient vector and is called step size or learning coefficient.
Step 4: The residual signal e _n ^M is obtained using the updated prediction coefficient W, and the absolute value sum J of Equation (32) is calculated.
Step 5: Determine whether J has converged by judging whether | W (n) -W (n-1) | is below a predetermined value. If not, W (n-1) ← W ( n) return to Step 2 and repeat the process.
If converged, W (n) is output as a prediction coefficient a _i ^M (i = 1, 2,..., P ^M ).

  This modification may be applied to each of the embodiments shown in FIGS. In addition, Newton's method, quasi-Newton's method, genetic algorithm, etc. can be used as a method for obtaining a prediction coefficient that minimizes the reference value.

Other Modifications In the above-described embodiments, for example, the case where the prediction coefficient a _i ^R obtained by the linear prediction analysis unit 11R is converted to the PARCOR coefficient k _i ^R by the conversion unit 12R has been described. Instead of the conversion unit, it may be replaced with a PARCOR coefficient calculation unit that directly obtains a PARCOR coefficient from the channel signal. The same applies to other sets of linear prediction units and conversion units.

  Each of the above-described embodiments has shown the case of a two-channel signal. However, when there are more channels than two channels, as shown in Non-Patent Document 1, for example, the energy of the residual signal or the sum of absolute values is calculated. A pair that becomes smaller may be determined, and the above-described encoding may be performed for each pair. In that case, one or a plurality of channels may be overlapped with another channel to form a plurality of pairs, or one or a plurality of channels may be encoded independently. In the case of lossless coding, a code representing the parent channel is also output. However, when the input is two channels, the parent-child relationship is explicit depending on the presence / absence of the weighting coefficient code, and therefore the code representing the parent channel may be omitted.

  The encoding method according to each embodiment of the present invention described above may be implemented as a computer-executable program. Alternatively, the program may be recorded on a readable recording medium, and the program read from the recording medium may be executed by a computer.

  FIG. 15 compares the average compression ratio when lossless encoding is performed on 38 commercially available music compact discs using the conventional method and the method according to FIG. 8 of the present invention. It is shown that the compression rate (data amount after encoding / data amount before encoding) is smaller in the encoding according to the present invention in any of the prediction orders 10, 30, and 50.

Claims (24)

A multi-channel encoding method for generating a code corresponding to a signal of a plurality of channels input for each frame composed of a plurality of samples,
A first channel linear prediction analysis step of linearly predicting and analyzing a signal of at least one channel, hereinafter referred to as a first channel, to generate a first channel linear prediction coefficient and a first channel residual signal;
The second channel linear prediction coefficient so that the reference value of the difference between the residual signal and the first channel residual signal from the signal of at least one channel other than the first channel, hereinafter referred to as the second channel, is minimized. A linear prediction analysis step using inter-channel correlation that generates a residual signal of the second channel signal as a second channel residual signal based on the second channel linear prediction coefficient;
A weighted subtraction step of generating a residual difference signal by a weighted subtraction process between the first channel residual signal and the second channel residual signal;
The PARCOR coefficient corresponding to the first channel linear prediction coefficient and the first channel residual signal are encoded to output a first channel code, and at least the PARCOR coefficient corresponding to the second channel linear prediction coefficient and the residual difference are output. An encoding step of encoding a signal and outputting a second channel code;
A second channel linear prediction analysis step of generating a second channel second linear prediction coefficient and a second channel second residual signal by performing a linear prediction analysis on the second channel signal;
A second channel second encoding step of encoding the second channel second residual signal and the PARCOR coefficient corresponding to the second channel second linear prediction coefficient and outputting a second channel second code;
Code selection for outputting the second channel second code if at least one absolute value of the PARCOR coefficient corresponding to the second channel linear prediction coefficient is equal to or greater than a predetermined value, and outputting the second channel code otherwise. Steps,
A multi-channel signal encoding method comprising:   2. The multi-channel signal encoding method according to claim 1, wherein a second channel second linear prediction analysis step of generating a second channel second residual signal by performing a linear prediction analysis on the second channel signal, and the first channel. A comparison control step of comparing a reference value of the residual signal with a reference value of the second channel second residual signal, and controlling switching of the first channel signal and the second channel signal based on the comparison result A multi-channel signal encoding method comprising:   The multi-channel signal encoding method according to claim 1, wherein the total code amount of the first channel code and the second channel code when the first channel signal and the second channel signal are not interchanged with each other A multi-channel signal encoding method further comprising a selection output step of comparing the total code amount, selecting and outputting the smaller one of the total code amounts, and outputting information indicating which one is selected.   4. The multi-channel signal encoding method according to claim 1, wherein the linear prediction analysis step using the inter-channel correlation includes: a residual signal of the second channel signal; and a first channel residual signal. The energy of the residual difference signal obtained by the weighted subtraction is expressed by an expression including the second channel linear prediction coefficient as a variable, and the expression is obtained by partial differentiation with each order coefficient of the second channel linear prediction coefficient. The equation is expressed using the autocorrelation of the second channel signal, the cross correlation between the first channel residual signal and the second channel signal, and the second channel linear prediction coefficient is solved by setting the equation to 0. A method for encoding a multi-channel signal, characterized in that 5. The multi-channel signal encoding method according to claim 4, wherein the first channel linear prediction analysis step includes the ^PR- order first channel linear prediction coefficient a _i ^R (i) from the first channel signal x ^R (n). = 1, 2,…, P ^R ), and the first channel residual signal is

Where a ₀ ^R = 1 and
In the linear prediction analysis step using the inter-channel correlation, τ is an integer from 0 to P ^M , the autocorrelation R (τ) of the second channel signal x ^L (n), and the first channel residual signal The cross-correlation C (τ) between e ^R (n) and the second channel signal x ^L (n) is

The following equation when, P ^M following the second channel linear prediction coefficients ^{_{a i M (i = 1,}} 2, ..., P M) are expressed in

And calculating the second channel residual signal e ^M (n) from the second channel signal x ^L (n) and the second channel linear prediction coefficient a _i ^M ,
In the weighted subtraction step, the weight coefficient γ is

And the difference between the second channel residual signal e ^M (n) and the first channel residual signal γe ^R (n) weighted based on the weighting factor γ as the residual difference. A multi-channel signal encoding method comprising a weighted subtraction step of calculating as signal ~ e ^M (n).   6. The multi-channel signal encoding method according to claim 5, wherein the linear prediction analysis step using the inter-channel correlation obtains the residual difference signal by weighted subtraction of a plurality of taps of the first channel difference signal. A multi-channel signal encoding method.   6. The multi-channel signal encoding method according to claim 5, wherein the linear prediction analysis step using the inter-channel correlation is performed by calculating the residual difference signal by weighted subtraction of a plurality of taps considering a time difference of the first channel difference signal. A multi-channel signal encoding method characterized by comprising: 5. The multi-channel signal encoding method according to claim 4, wherein the first channel linear prediction analysis step includes a ^PR order linear prediction coefficient a _i ^R (i = 1, 2) from the first channel signal x ^R (n). , ..., P ^R ), and the first channel residual signal is

Where a ₀ ^R = 1 and
Linear prediction analysis step using the correlation between the channels, and an integer of τ from 0 to P ^M, the second channel signal and x ^L (n), the autocorrelation of the second channel signal x ^L (n) R (τ) and the cross-correlation C (τ) between the first channel residual signal e ^R (n) and the second channel signal x ^L (n) are expressed as follows:

The following equation when, P ^M following the second channel linear prediction coefficients ^{_{a i M (i = 1,}} 2, ..., P M) are expressed in

And calculating the second channel residual signal e ^M (n) from the second channel signal x ^L (n) and the second channel linear prediction coefficient a _i ^M ,
In the weighted subtraction step, the weight coefficient γ is

And the difference between the second channel residual signal e ^M (n) and the first channel residual signal γe ^R (n) weighted based on the weighting factor γ as the residual difference. A multi-channel signal encoding method comprising a weighted subtraction step of calculating as signal ~ e ^M (n). 5. The multi-channel signal encoding method according to claim 4, wherein the first channel linear prediction analysis step includes the ^PR- order first channel linear prediction coefficient a _i ^R (i) from the first channel signal x ^R (n). = 1, 2,…, P ^R ), and the first channel residual signal is

Where a ₀ ^R = 1 and
In the linear prediction analysis step using the inter-channel correlation, τ is an integer from 0 to P ^M , the autocorrelation R (τ) of the second channel signal x ^L (n), and the first channel residual signal The cross-correlation C (τ) between e ^R (n) and the second channel signal x ^L (n) is

The following equation when, P ^M following the second channel linear prediction coefficients by using a weighting factor as a provisional weighting coefficient gamma ₀ of the previous frame ^{_{a i M (i = 1,}} 2, ..., P M) are expressed in

And calculating the second channel residual signal e ^M (n) from the second channel signal x ^L (n) and the second channel linear prediction coefficient a _i ^M ,
In the weighted subtraction step, the weight coefficient γ is

And the difference between the second channel residual signal e ^M (n) and the first channel residual signal γe ^R (n) weighted based on the weighting factor γ as the residual difference. A multi-channel signal encoding method comprising a weighted subtraction step of calculating as signal ~ e ^M (n). 5. The multi-channel signal encoding method according to claim 4, wherein the second channel linearity is generated as a second channel second residual signal e ^L (n) only from the second channel signal x ^L (n). From the prediction analysis step, the provisional weighting coefficient γ ₀ is calculated from the first channel residual signal e ^R (n) and the second channel residual signal e ^L (n) by the following equation:

A provisional weight coefficient calculation step obtained by:
The first channel linear predictive analysis step, the first channel signal x ^R (n) from P ^R following the first channel linear prediction coefficients ^{_{a i R (i = 1,}} 2, ..., P R) sought, Further, the first channel residual signal is expressed as

Where a ₀ ^R = 1 and
In the linear prediction analysis step using the inter-channel correlation, τ is an integer from 0 to P ^M , the autocorrelation R (τ) of the second channel signal x ^L (n), and the first channel residual signal The cross-correlation C (τ) between e ^R (n) and the second channel signal x ^L (n) is

, The second channel linear prediction coefficient a _i ^M (i = 1, 2,..., P ^M ) of the P ^M order is calculated using the temporary weight coefficient γ ₀ calculated in the provisional weight coefficient calculation step. formula

And calculating the second channel residual signal e ^M (n) from the second channel signal x ^L (n) and the second channel linear prediction coefficient a _i ^M ,
In the weighted subtraction step, the weight coefficient γ is

And the difference between the second channel residual signal e ^M (n) and the first channel residual signal γe ^R (n) weighted based on the weighting factor γ as the residual difference. A multi-channel signal encoding method comprising a weighted subtraction step of calculating as signal ~ e ^M (n).   4. The multi-channel signal encoding method according to claim 1, wherein the linear prediction analysis step using the inter-channel correlation uses the weight coefficient of the previous frame as a provisional weight coefficient and uses the second channel signal as the provisional weight coefficient. A correlation approximating step for generating a difference signal by performing weighted subtraction with the first channel residual signal; and a difference for performing linear prediction analysis on the difference signal and outputting a prediction coefficient obtained thereby as the second channel linear prediction coefficient And a signal linear prediction analysis step. The multi-channel signal encoding method according to any one of claims 1 to 3, wherein a second channel linear prediction analysis step for generating a residual signal as a second channel second residual signal from only the second channel signal; A provisional weighting factor calculating step for obtaining a provisional weighting factor from the first channel residual signal and the second channel residual signal;
In the linear prediction analysis step using the inter-channel correlation, the second channel signal is weighted by the first channel residual signal using the provisional weighting factor calculated in the provisional weighting factor calculation step as an approximation of cross-correlation. A correlation approximation step of generating a difference signal by subtraction processing, and a difference signal linear prediction analysis step of linearly predicting and analyzing the difference signal and outputting a prediction coefficient obtained thereby as the second channel linear prediction coefficient A multi-channel signal encoding method characterized by the above.   2. The multi-channel signal encoding method according to claim 1, wherein the linear prediction analysis step using the inter-channel correlation is obtained by weighted subtraction between the residual signal of the second channel signal and the first channel residual signal. A step of approximating the absolute value of the residual difference signal obtained by a continuous function, and the approximation formula is expressed by a formula including a second channel linear prediction coefficient as a variable, and the formula is a coefficient of each order of the second channel linear prediction coefficient Is obtained by using the autocorrelation of the second channel signal and the cross-correlation between the first channel residual signal and the second channel signal, and the second channel linear prediction by the equation. A multi-channel signal encoding method comprising a step of obtaining a coefficient.   14. The multi-channel signal encoding method according to claim 13, wherein the second channel linear prediction coefficient is obtained by solving the equation expressed by autocorrelation and cross-correlation as 0. .   14. The multi-channel signal encoding method according to claim 13, wherein the second channel linear prediction coefficient is obtained by a steepest descent method from the expressions expressed by the autocorrelation and the cross-correlation. A multi-channel encoding device that generates a code corresponding to a signal of a plurality of channels input for each frame composed of a plurality of samples,
First channel linear prediction analysis means for linearly predicting and analyzing a first channel signal of at least one channel, hereinafter referred to as a first channel, to generate a first channel linear prediction coefficient and a first channel residual signal;
The second channel linear prediction coefficient so that the reference value of the difference between the residual signal and the first channel residual signal from the signal of at least one channel other than the first channel, hereinafter referred to as the second channel, is minimized. Linear prediction analysis means using inter-channel correlation for generating a residual signal of the second channel signal as a second channel residual signal based on the second channel linear prediction coefficient;
Weighted subtraction means for generating a residual difference signal by weighted subtraction processing between the first channel residual signal and the second channel residual signal;
First channel encoding means for encoding a PARCOR coefficient corresponding to the first channel linear prediction coefficient and the first channel residual signal and outputting a first channel code;
Second channel encoding means for encoding a PARCOR coefficient corresponding to at least the second channel linear prediction coefficient and the residual difference signal and outputting a second channel code;
Second channel linear prediction analysis means for generating a second channel second linear prediction coefficient and a second channel second residual signal by performing linear prediction analysis on the second channel signal;
Second channel second encoding means for encoding the second channel second residual signal and the PARCOR coefficient corresponding to the second channel second linear prediction coefficient and outputting a second channel second code;
Code selection for outputting the second channel second code if at least one absolute value of the PARCOR coefficient corresponding to the second channel linear prediction coefficient is equal to or greater than a predetermined value, and outputting the second channel code otherwise. Means,
A multi-channel signal encoding apparatus comprising:   17. The multi-channel signal encoding apparatus according to claim 16, wherein second channel second linear prediction analysis means for generating a second channel second residual signal by performing linear prediction analysis on the second channel signal, and the first channel. A switching means capable of switching the signal and the second channel signal, a reference value of the first channel residual signal and a reference value of the second channel second residual signal are compared, and the switching is performed based on the comparison result. A multi-channel signal encoding apparatus, further comprising comparison control means for controlling the means.   17. The multi-channel signal encoding device according to claim 16, wherein the input switching means capable of switching the first channel signal and the second channel signal, and the input switching means include the first channel signal and the second channel signal. The total code amount of the first channel code and the second channel code when the code is not replaced is compared with the total code amount when the code is replaced, and the smaller total code amount is selected and output, and which one is selected A multi-channel signal encoding apparatus, further comprising selection output means for outputting information to be expressed.   The multi-channel signal encoding device according to any one of claims 16 to 18, wherein the linear prediction analysis means using the inter-channel correlation is a difference between the residual signal of the second channel signal and the first channel residual signal. The energy of the residual difference signal obtained by the weighted subtraction is expressed by an expression including the second channel linear prediction coefficient as a variable, and the expression is obtained by partial differentiation with each order coefficient of the second channel linear prediction coefficient. The equation is expressed using the autocorrelation of the second channel signal, the cross correlation between the first channel residual signal and the second channel signal, and the second channel linear prediction coefficient is solved by setting the equation to 0. A multi-channel signal encoding apparatus characterized by:   19. The multi-channel signal encoding apparatus according to claim 16, further comprising weight coefficient holding means for holding a weight coefficient of a previous frame as a temporary weight coefficient, and linear prediction using the inter-channel correlation. The analysis means uses the provisional weight coefficient from the weight coefficient holding means as a cross-correlation approximation to perform a weighted subtraction process on the second channel signal with the first channel residual signal to generate a difference signal. And a difference signal linear prediction analysis unit that performs linear prediction analysis on the difference signal and outputs a prediction coefficient obtained thereby as the second channel linear prediction coefficient. The multi-channel signal encoding device according to any one of claims 16 to 18, wherein a second channel linear prediction analysis unit that generates a residual signal as a second channel second residual signal from only the second channel signal; Provisional weight coefficient calculating means for obtaining a provisional weight coefficient from the first channel residual signal and the second channel residual signal;
The linear prediction analysis means using the inter-channel correlation uses the provisional weight coefficient from the provisional weight coefficient calculation means as an approximation of the cross-correlation to subtract the second channel signal by the first channel residual signal. A correlation approximation unit that generates a difference signal by processing, and a difference signal linear prediction analysis unit that performs linear prediction analysis of the difference signal and outputs a prediction coefficient obtained thereby as the second channel linear prediction coefficient. A characteristic multi-channel signal encoding apparatus.   The multi-channel signal encoding device according to any one of claims 16 to 18, wherein the linear prediction analysis means using the inter-channel correlation is a difference between the residual signal of the second channel signal and the first channel residual signal. The absolute value of the residual difference signal obtained by weighted subtraction is approximated by a continuous function, and the approximate expression is expressed by an expression including the second channel linear prediction coefficient as a variable, and the expression is expressed for each of the second channel linear prediction coefficients. An expression obtained by partial differentiation with the order coefficient is expressed using the autocorrelation of the second channel signal and the cross-correlation between the first channel residual signal and the second channel signal. A multi-channel signal encoding apparatus, characterized in that it is means for obtaining a channel linear prediction coefficient. A program for causing a computer to execute each step of the method according to any one of claims 1 to 15. A computer-readable recording medium on which the program according to claim 23 is recorded.

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