Abstract:
The present invention relates to method and device for coding speech and to method and device for inverse-quantizing signals coded by the speech coding method. The object of the present invention is to realize an improved coding accuracy and an improved predictive gain by using a correlation between frames of a spectrum, if necessary, in an coding step. A first filter uses a coefficient determined by a predictive coefficient analyzed in a previous frame. After an input speech signal is subjected to a inverse filtering process by the first filter, the first predictive residual signal obtained is subjected to a linear predictive coding to obtain a predictive coefficient. A second filter subjects the predictive coefficient to an inverse filtering process and the resultant second predictive residual signal is quantized.

Description:
BACKGROUND OF THE INVENTION 
     1) Field of the Invention 
     The present invention relates to a speech coding method which executes a linear predictive coding of an input speech signal and quantizes and transmits the predictive error signal and a device employing the same, and a speech decoding method which executes an inverse quantization of a signal coded by the speech coding method and a device employing the same. 
     2) Description of the Related Art 
     In recent years, a speech coding device which compresses speech signal at high efficiency and a speech decoding device which decodes the coded signal have been demanded for intracompany communications systems, digital mobile radio systems, speech store systems, and similar systems. 
     Conventional speech predictive coding device multiplexes and outputs a parameter (predictive coefficient) extracted through a linear predictive coding to every frame and a parameter of an excitation signal which drives a predictive synthesis filter having the predictive coefficients as coefficients. In the decoding device, a predictive synthesis filter receives the excitation signal to reproduce a speech signal. 
     The all-pole type model determined by a linear predictive coding is known to be a good model of a speech producing process. For the high efficiency speech signal coding, a device which transmits linear predictive coefficients determined through a linear predictive coding analysis and parameters relating to a voice source has been widely used. 
     FIG. 14 shows the configuration of a conventional speech coding device. Referring to FIG. 14, the speech coding device includes a linear predictive analyzing unit 101 for performing a linear predictive coding on an input signal to calculate predictive coefficients, a predictive coefficient quantizing unit 102 for quantizing predictive coefficients calculated in the linear predictive analyzing unit 101, an inverse filter 103 for executing an inverse filtering process based on the quantizing predictive coefficient from the predictive coefficient quantizing unit 102 to determine predictive residual signals, a residual signal quantizing unit 104 for quantizing the predictive residual signal from the inverse filter 103, and a multiplexing unit (MUX) 105 for multiplexing predictive residual signal quantizing codes and predictive coefficient quantizing codes to transmit the outcome to a speech decoding device. 
     FIG. 15 is a diagram showing the configuration of a conventional speech decoding device. The speech decoding device, shown in FIG. 15, includes a demultiplexing unit (DEMUX) 111 for demultiplexing a signal inputted from a speech coding device through a transmission line, a predictive coefficient inverse quantizing unit 112 for executing an inverse quantizing process to predictive coefficient quantizing codes from the speech coding device, demultiplexed in the demultiplexing unit 111, a residual signal inverse quantizing unit 113 for executing an inverse quantizing process on the predictive residual signal quantizing code from the speech coding device, and a filter 114 for reproducing speech signal by executing a filtering process on the inverse-quantized predictive residual signal based on the inverse-quantized predictive coefficients. 
     In the speech coding device and the speech decoding device with such a conventional configuration, a signal is sampled every fixed length of span (frame) of an input signal by executing a window process, and then the sampled signal is subjected to a linear predictive coding every frame unit. Generally, the spectrum envelope every speech frame in a short time has a high correlation between adjacent frames. 
     In the coding, the analysis order is usually a fixed value and signals except of the analyzing span are not used. The speech decoding device receives predictive coefficient quantizing codes and predictive residual signal quantizing codes from the speech coding device to subject them to an inverse quantizing process. Filter coefficients are determined based on the resultant quantized predictive coefficients and then a speech signals are reproduced by performing a filtering process on the quantized predictive residual signals. 
     In order to transmit efficiently a speech signal information, there are a code excited linear predictive coding device (CELP) which vector-quantizes excitation signals and transmits its indices, and a multi-pulse excitation coding device (MPC) which models excitation signals as finite numbr of pulses and transmits optimum pulse positions and pulse amplitudes. 
     As described above, the predictive coefficients analyzed every frame have a high correlation between the values analyzed on adjacent frames because of a small change in the spectrum in a speech stationary period. In order to improve the quantizing efficiency of the predictive coefficients by utilizing the interframe correlation to analyzed predictive coefficients, a predictive coding and a finite state vector quantizing are known. 
     The conventional speech coding device and speech decoding device do not utilize any interframe correlation in the analysis stage, but utilize an interframe correlation only at the quantizing stage. Therefore, there is a disadvantage in that the interframe correlation is not used to improve prediction gain. 
     The change in the spectrum is large in a transient speech period, and the correlation between analyzed values in adjacent frames is low. Hence, it is required that the predictive coefficients which are subjected to a linear predictive coding are not needed to utilize the interframe correlation during the above periods 
     SUMMARY OF THE INVENTION 
     The present invention is made to overcome the above mentioned problems. An object of the present invention is to provide a method and a device for coding speech, which realize an improved coding accuracy and an improved predictive gain by using a correlation between spectra of successive frames, if necessary, in an analysis stage. 
     Another object of the present invention is to provide a method and a device for decoding speech, which realize an improved coding accuracy and an improved predictive gain by using a correlation between spectra of successive frames, if necessary, in a coding step. 
     In order to achieve the above objects, a speech coding method of the present invention is characterized by the steps of performing an inverse filtering process on an input speech signal by a first filter, the first filter using coefficients obtained from predictive coefficients, the predictive coefficients being obtained by analyzing a previous frame; performing a linear predictive coding analysis on the first predictive residual signal obtained by the inverse filtering step to obtain predictive coefficients; performing an inverse filtering process by a second filter by using the predictive coefficients to obtain a second predictive residual signal; and quantizing the second predictive residual signal obtained by the inverse filtering process on the second filter. 
     According to the present invention, a speech coding device is characterized by a first filter for performing an inverse filtering process on an input speech signal and issuing a first predictive residual signal; a second filter for performing an inverse filtering process on the first predictive residual signal obtained from the first filter and issuing a second predictive residual signal; quantizing means for quantizing the second predictive residual signal received from the second filter; linear predictive analyzing means for performing a linear predictive coding based on the first predictive residual signal from the first filter and extracting predictive coefficients for the second filter to determine the filter characteristic of the second filter; and calculating means for the first filter for calculating predictive coefficients for the first filter to determine the filter characteristic of the first filter, using predictive coefficients of a previous frame, whereby the first filter determines its filter characteristic based on the predictive coefficients obtained by the calculating means, performs an inverse filtering process of an input speech signal using the filter characteristic, and issues the first predictive residual signal, and whereby the second filter determines a filter characteristic based on the second filter predictive coefficients obtained by the linear predictive analyzing means, performs an inverse filtering process on the first predictive residual signal using the filter characteristic, and issues the second predictive residual signal. 
     According to a speech coding device of the present invention, the order of the first filter is smaller than that of the second filter. 
     According to a speech coding device of the present invention, the calculating means for the first filter includes total predictive coefficients calculating means for determining total predictive coefficients from the first filter predictive coefficients and the second filter predictive coefficients of a previous frame; first converting means for converting the total predictive coefficients obtained by the total predictive coefficients calculating means into reflective coefficients; order truncating means for truncating the order of the first filter to the other reflective coefficients converted by the first converting means; and second converting means for converting the reflective coefficients into the first filter predictive coefficients processed by the order truncating means. 
     In a speech coding device according to the present invention, the calculating means for the first filter includes first selecting means for determining a plurality of predictive coefficient candidates for the first filter; and second selecting means for selecting an optimum predictive coefficient for the first filter from the predictive coefficient candidates selected by the first selecting means. 
     Moreover, a speech coding device according to the present invention is characterized in that the first selecting means includes total predictive coefficient calculating means for determining a plurality of total predictive coefficients from the first filter predictive coefficients and the second filter predictive coefficients of a previous frame; first converting means for converting the plurality of total predictive coefficients obtained by the total predictive coefficient calculating means into a plurality of corresponding reflective coefficients; order truncating means for truncating the corresponding order of the first filter with respect to the plurality of reflective coefficients converted by the first converting means; and second converting means for converting the plurality of reflective coefficients processed by the order truncating means into first filter predictive coefficient candidates. 
     A speech coding device according to the present invention also is characterized in that the first filter predictive coefficient candidates include coefficients which ensure that the first filter has a through-characteristic. 
     The second selecting means selects as said first filter predictive coefficients a predictive coefficient candidate minimizing the predictive residual signal power, from a predictive coefficient candidate selected by the first selecting means. 
     A speech coding device according to the present invention is characterized by a first filter for performing an inverse filtering process on an input speech signal and issuing a first predictive residual signal; by-pass route means for by-passing the first filter; a selector for selections the first filter or the by-pass route means; a second filter for performing an inverse filtering process on a signal selected by the selector and issuing a second predictive residual signal; quantizing means for quantizing the second predictive residual signal recovered from the second filter; linear predictive analyzing means for performing a linear predictive coding based on a signal selected by the selector and for extracting the second filter predictive coefficients to determine the filter characteristic of the second filter; calculating means for the first filter for calculating the first filter predictive coefficients using predictive coefficients of a previous frame to determine the filter characteristic of the first filter; and selector control means for switching the selector based on a predictive residual signal, whereby in the first filter, when the power of the predictive residual signal is smaller than a reference value, the first predictive residual signal is outputted after subjecting an input speech signal to an inverse filtering process to determine a filter characteristic, the first filter characteristic being determined based on the first filter predictive coefficients obtained by the calculating means for the first filter, and is selected by the selector and when the predictive residual signal power is larger than the reference value, the selector selects an input speech signal by way of the by-pass route means, while the second filter determines its filter characteristic based on the second filter predictive coefficient extracted by the linear predictive analyzing means, performs an inverse filtering process on the first predictive residual signal or the input speech signal from said selector in accordance with the obtained filter characteristic, and issues the second predictive residual signal. 
     A speech decoding method according to the present invention is characterized by the steps of performing an inverse quantization on a quantization predictive residual signal in accordance with a quantizing code sent from a quantizing means in a coding device; subjecting an inverse-quantized predictive residual signal to a composite filtering process using a third filter, the third filter using predictive coefficients sent from a linear predictive analyzing means in the coding device; and subjecting the output of the third filter to a composite filtering process using a fourth filter, the fourth filter determining a characteristic based on a predictive coefficient information sent from a predictive coefficient calculating means, the predictive coefficient calculating means calculating the other predictive coefficients from predictive coefficients of a previous frame in the coding device. 
     Moreover, a speech decoding device according to the present invention is characterized by inverse-quantizing means for inverse-quantizing a quantizing predictive residual signal in accordance with a quantizing code sent from quantizing means in a speech coding means; a third filter for determining its filter characteristic based on predictive coefficients sent from a linear predictive analyzing means in the speech coding device and for subjecting the predictive residual signal inverse-quantized by the inverse quantizing means to a filtering process in accordance with said filter characteristic; and a fourth filter for determining its filter characteristic based on predictive coefficients sent from predictive coefficients calculating means, the predictive coefficient calculating means calculating the other predictive coefficients from predictive coefficients in a previous frame in the speech coding device and subjecting an output signal from the third filter to a filtering process using the filter characteristic. 
     A speech decoding device according to the present invention is characterized by inverse-quantizing means for inverse-quantizing a quantizing predictive residual signal sent from quantizing means in a speech coding device; a third filter for determining its filter characteristic based on predictive coefficients sent from a linear predictive analyzing means in the speech coding device and subjecting the predictive residual signal inverse-quantized by the inverse quantizing means to a filtering process using the filter characteristic; a selector for switching in accordance with a selector switching information sent from selector control means in the speech coding means; a fourth filter connected to one switching route of said selector for subjecting the output of the selector into a filtering process; and a by-pass route means connected to another switching route of the selector for by-passing the fourth filter. 
     Furthermore, in a speech decoding device according to the present invention, the order of said fourth filter is lower than that of the third filter. 
     In the speech coding device of the present invention, the first filter executes an inverse filtering process on an input speech signal and outputs a first predictive residual signal, and the second filter executes an inverse filtering process on the first predictive residual signal and outputs a second predictive residual signal. 
     Next, the quantizing means quantizes the second predictive residual signal from the second filter. In order to determine the filter characteristic of the second filter, the linear predictive analyzing means performs a linear predictive coding based on the first predictive residual signal from the first filter and extracts the second filter predictive coefficients. 
     In order to determine the filter characteristic of the first filter, the calculating means for the first filter analyzes predictive coefficients in a previous frame, and calculates predictive coefficients for the first filter. 
     Furthermore, in the inverse filtering process of the first filter, the filter characteristic is determined based on a first filter predictive coefficient determined by the calculating means for the first filter and a first predictive residual signal is issued by subjecting the input speech signal to an inverse filtering process in accordance with the filter characteristic. 
     In the process of the second filter, the filter characteristic is determined based on the predictive coefficients for the second filter extracted by the linear predictive analyzing means and the second predictive residual signal is issued by performing an inverse filtering process of the first predictive residual signal in accordance with the filter characteristic. 
     The calculating means for the first filter can calculate the first filter predictive coefficients, as explained below. The total predictive coefficient calculating means determines total predictive coefficients from the first filter predictive coefficients and the second filter predictive coefficients of the previous frame. The obtained total predictive coefficients are converted to reflective coefficients by means of the first converting means. 
     Next, the order truncating means subjects the reflective coefficients converted to a truncating process based on the order of the first filter. The second converting means converts the reflective coefficients processed by the order truncating means into a first filter predictive coefficients and then outputs the outcome. 
     Moreover, the calculating means for the first filter can calculate the first filter predictive coefficients as follows: 
     The predictive coefficient candidate selecting means in the calculating means for the first filter determines a plurality of first filter predictive coefficient candidates. The selecting means selects the optimum first filter predictive coefficients from the predictive coefficient candidates selected by the predictive coefficient candidate selecting means. 
     In the above case, the predictive coefficient candidate selecting means calculates a predictive coefficient candidate as follows: 
     The total predictive coefficients calculating means determines a plurality of total predictive coefficients from the first filter predictive coefficients and the second filter predictive coefficients in the plurality of previous frames. The first converting means converts a plurality of total predictive coefficients obtained by the total predictive coefficient calculating means into a plurality of corresponding reflective coefficients. 
     Next, the order truncating means subjects a plurality of reflective coefficients converted by the first converting means to the truncating process in accordance with the order of the corresponding first filter. The second converting means converts a plurality of reflective coefficients processed by the order truncating means into predictive coefficient candidates for the first filter, and then produces them. 
     The predictive coefficient candidates for the first filter include a candidate which makes the first filter having a through characteristic. As described above, when the first filter is constituted as a variable order filter, the selecting means in the first predictive calculating means for the first filter selects as predictive coefficients for the first filter a predictive coefficient candidate which minimizes the predictive residual signal power from the predictive coefficient candidate selected by the predictive coefficient candidate selecting means. 
     The speech coding device according to the present invention can operate as follows: 
     The selector issues selectively a signal obtained by subjecting an input speech signal to an inverse filtering process by the first filter or a signal by-passing the first filter via a by-pass route means. 
     The second filter executes an inverse filtering process on a signal selected by the selector and outputs a second predictive residual signal. The quantizing means quantizes the second predictive residual signal from the second filter. 
     The second filter characteristic is determined by performing a linear predictive coding based on the first predictive residual signal from the first filter in the linear predictive analyzing means and extracting predictive coefficients for the second filter. 
     The filter characteristic of the first filter is determined by analyzing predictive coefficients of a previous frame by the calculating means for the first filter and then calculating predictive coefficients for the first filter. 
     The selector control means switches the selector in accordance with a predictive residual signal power. The switching operation is performed as follows: 
     In the first filter, when the predictive residual signal power is smaller than a reference value, the selector is switched so as to select the first predictive residual signal in accordance with a filter characteristic, the signal being obtained by subjecting an input speech signal to an inverse filtering process, the filter characteristic being determined based on the first filter predictive coefficient obtained by the calculating means for the first filter. When the predictive residual signal power is larger than the reference value, the selector is switched so as to select the input speech signal inputted via the by-pass route means. 
     In the inverse filtering process of the second filter, a filter characteristic is determined based on predictive coefficients for the second filter extracted by the linear predictive analyzing means. In accordance with the filter characteristic, an inverse filtering process is performed to the first predictive residual signal or the input speech signal in the selector to produce a second predictive residual signal. 
     The speech decoding device according to the present invention can separate as follows: 
     The inverse quantizing means inverse-quantizes the quantizing codes of the predictive coefficients sent from the quantizing means in a speech coding device. Sequentially, the third filter determines its filter characteristic based on the predictive coefficients sent from the linear predictive coefficient analyzing means in the speech coding device, and subjects the predictive residual signal inverse-quantized by the inverse quantizing means to a filtering process in accordance with the filter characteristic. 
     The fourth filter determines its filter characteristic based on an predictive coefficient information, the information being sent from the predictive coefficient calculating means which calculates the other predictive coefficients from predictive efficients of a previous frame in the speech coding device. The output signal from the third filter is subjected to a filtering process according to the filter characteristic. 
     Furthermore, the speech decoding device according to the present invention may separate in accordance with the following procedure. 
     The inverse quantizing means inverse-quantizes a predictive residual signal quantizing code sent from the quantizing means in the speech coding device. Next, the third filter determines its filter characteristic based on predictive coefficients sent from the linear predictive analyzing means in the speech coding device, and then subjects the predictive residual signal inverse-quantized by the inverse quantizing means to a filtering process, utilizing the filter characteristic. 
     The selector outputs selectively a signal processed by the third filter to either the fourth filter connected to one switching path thereof or the by-pass route means connected to the other switching path thereof, based on a selector switching information sent from the selector control means in the speech coding device. 
     When the selector is connected to one switching route, the fourth filter performs an inverse filtering process on the output signal of the selector. When the selector is connected to the other switching route, the fourth filter is by-passed. 
     According to the above configuration of the present invention, since the speech coding device transmits with bit information added, there are the following advantages as for speech signal reproduction: 
     (a) Since a small span of spectrum changes of an input speech signal, for example, a stationary voiced period is subjected to an additional linear predictive analysis by using the output from the first filter, the predictive gain becomes higher than that of the conventional configuration obtained by only the second filter, whereby the accuracy of the linear predictive coding can be improved. 
     (b) When an input speech signal has a large change in spectrum, the degradation of the predictive gain can be prevented by making the first filter in a through characteristic state. 
     (c) Since the first filter includes a plurality of candidates including a candidate with a through characteristic and an optimum coefficient is selected from them, the characteristic degradation can be eliminated even in the periods where the spectrum of an input signal is changing, whereby the accuracy of the linear predictive coding can be more improved. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram showing a speech coding device according to the first embodiment of the present invention; 
     FIG. 2 is a block diagram showing a pre-filter candidate calculating unit in the speech coding device according to the first embodiment of the present invention; 
     FIG. 3 is a block diagram showing an optimum coefficient selection unit of the speech coding device according to the first embodiment of the present invention; 
     FIG. 4 is a block diagram showing a speech decoding device according to the first embodiment of the present invention; 
     FIG. 5 is a block diagram showing a speech coding device according to the second embodiment of the present invention; 
     FIG. 6 is a block diagram showing a pre-filter candidate calculation unit according to the second embodiment of the present invention; 
     FIG. 7 is a block diagram showing the optimum coefficient selection unit according to the second embodiment of the present invention; 
     FIG. 8 is a block diagram showing a speech decoding device according to the second embodiment of the present invention; 
     FIG. 9 is a block diagram showing a speech coding device according to the third embodiment of the present invention; 
     FIG. 10 is a block diagram showing the optimum coefficient selection unit of a speech coding device according to the third embodiment of the present invention; 
     FIG. 11 is a block diagram showing a speech decoding device according to the third embodiment of the present invention; 
     FIG. 12 is a block diagram showing a speech coding device according to the fourth embodiment of the present invention; 
     FIG. 13 is a block diagram showing a speech decoding device according to the fourth embodiment of the present invention; 
     FIG. 14 is a block diagram showing a conventional speech coding device; and 
     FIG. 15 is a block diagram showing a conventional decoding device. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Referring to the attached drawings, an explanation will be made in detail as for preferred embodiments of the method and device for coding speech and method and device for decoding speech according to the present invention. 
     (a) Explanation of the First Embodiment 
     FIG. 1 is a block diagram showing a speech coding device according to the first embodiment of the present invention. Referring to FIG. 1, the speech coding device is constituted of a pre-filter 20a as a first filter, an inverse filter 21a as a second filter, a quantizing unit 22a as quantizing means, a linear predictive analyzing unit 24a as linear predictive analyzing means, a frame delay unit 25a as predictive coefficient calculating means for the first filter, a pre-filter coefficient candidate calculating unit 26a, a coefficient candidate code book 27a, an optimum coefficient selecting unit 28a, a predictive coefficient quantizing unit 23a, and a multiplexing unit (MUX) 29a. 
     The pre-filter 20a as the first filter executes an inverse filtering process on an input speech signal and outputs a pre-filter predictive residual signal r1(n). 
     The inverse filter 21a as the second filter executes an inverse filtering process on a pre-filter predictive residual signal r1(n) from the pre-filter 20a and outputs the outcome as a predictive residual signal r2(n). 
     The pre-filter 20a, for example, executes an inverse filtering process using a M-th order (M is a variable) filter coefficient and the in verse filter 21a executes an inverse filtering process using an N-th order filter coefficient. The M-th order of the pre-filter 20a is lower than N-th order of the inverse filter 21a. The quantizing unit 22a as quantizing means quantizes a predictive residual signal r2(n) from the inverse filter 21a to output the outcome to the multiplexing unit 29a. 
     The linear predictive analyzing unit 24a as linear predictive analyzing means extracts a predictive coefficient for the inverse filter 21a for determining the filter characteristic of the inverse filter 21a, based on a pre-filter predictive residual signal r1(n) from the pre-filter 20a. The predictive coefficient quantizing unit 23a quantizes predictive coefficients for the inverse filter from the linear predictive analyzing unit 24a to issue the outcome to the inverse filter 21a, the frame delay unit 25a and the multiplexing unit 29a. 
     The frame delay unit 25a extracts a predictive coefficient information and a pre-filter coefficient information of a previous frame which are used to calculate pre-filter coefficients to determine the filter characteristic of the pre-filter 20a. For example, the frame delay unit 25a extracts a predictive coefficient information and a pre-filter coefficient information of a frame earlier by one frame with respect to the current frame information. 
     The pre-filter coefficient candidate calculating unit (predictive coefficient candidate selecting means) 26a determines, for example, a plurality of pre-filter coefficient candidates with different orders. The pre-filter coefficient candidate calculating unit 26a, as shown in FIG. 2, is constituted of a convolutional operation unit (total predictive coefficient calculating means) 41a, a first coefficient converting unit (first converting means) 42a, an order truncating unit (order truncating means) 43a, and a second coefficient converting unit (second converting means) 44a. 
     In FIG. 2, the convolutional operation unit 41a determines a plurality of total predictive coefficients of a previous frame. In concrete, the total predictive coefficients are determined through the following calculation. 
     For example, when the previous predictive coefficient {bi} earlier by 1-frame to the current frame of the pre-filter 20a is given by the expression (1) and the previous predictive coefficient {ci} earlier by 1-frame to the current frame of the inverse filter 21a is given by the expression (2), the composite characteristic is given by the expression (3). The predictive coefficient, as given by the expression (4), is obtained by convoluting the predictive coefficients {bi} and {ci}. 
     
         {bi}=(b0, b1, . . . , bM)                                  (1) 
    
     
         {ci}=(c0, c1, . . . , cN)                                  (2) 
    
     
         H(z)=P(z)A(z)                                              (3) ##EQU1## The first coefficient converting unit 42a converts a plurality of total predictive coefficients from the convolutional operating unit 41a into a plurality of corresponding reflective coefficients. In concrete, the calculation is performed as follows: 
    
     For example, the convolutional operation unit 41a converts the above total predictive coefficient {an} into the reflective coefficient {kn} expressed by the expression (5). 
     
         ki=ai.sup.(i) 
    
     
         aj.sup.(i-1) =(aj.sup.(i) +ai.sup.(i) ai-j.sup.(i)) /(1-ki.sup.2) (1≦j≦j-1) 
    
     In this case, i decreases from p to p-1, . . . , 1, and is set first as expressed by the following expression: ##EQU2## 
     As described above, the convolutional operation unit 41a and the first coefficient converting unit 42a calculates and converts to obtain a plurality of (N+M)-th order refelective {kn}. The order truncating unit 43a truncates the (N+M)-th order reflective coefficient to make a M-th order reflective coefficient. That is, the expression, {kn}={k0, k1, . . . , KM, . . . , KM+N}, is obtained by truncating the expression, {kn}={k0, k1, . . . , KM}, to the coefficients kM+1˜kM+N. 
     The second coefficient converting unit 44a converts a reflective coefficient processed by the order truncating unit 43a to a predictive coefficient and issues the outcome as a pre-filter coefficient candidate. In concrete, the predictive coefficient is obtained through the following calculation. 
     The reflective coefficient {kn} processed by the order truncating unit 43a, for example, is converted to a predictive coefficient in accordance with the expression (6). ##EQU3## The above expressions are solved regarding i=1, 2, . . . , p. A predictive coefficient is determined by arranging the following expression (6) from the final coefficient set: 
     
         aj=aj.sup.(p)                                              (6) 
    
     As described above, in order to convert the (M+N)-th order predictive coefficient to a M-th order coefficient, the (M+N)-th order predictive coefficient is once converted to a reflective coefficient to truncate the order, and it is reconverted to a predictive coefficient. This is because it is impossible to truncate directly the predictive coefficient. 
     The coefficient code book 27a stores a plurality of pre-filter coefficient candidates calculated by the pre-filter coefficient candidate calculating unit 26a. There are two modes as a method of calculating a plurality of pre-filter coefficients stored. 
     In one mode, the pre-filter coefficient and the predictive coefficient of a plurality of previous frames are used as a fixed M-th order coefficient of the pre-filter 20a to accumulate and store the coefficient calculated as a pre-filter coefficient candidate. In the other mode, the pre-filter coefficient and the predictive coefficient of the previous frame preceding a frame, as a coefficient with a variable order of the pre-filter 20a, is used to store pre-filter coefficients candidates of various kinds of orders. 
     In either pre-filter coefficient candidate calculating method, the characteristic which passes an input speech signal through the pre-filter 20a without changing its signal characteristic (or which is a through characteristic making the pre-filter 20a OFF) is calculated and stored. Since the interframe correlation of a predictive coefficient is small in a span where an input speech signal has a large spectrum change, the degradation of the predictive gain is prevented due to the use of the pre-filter 20a. 
     The optimum coefficient selecting unit (selecting means) 28a, as shown in FIG. 3, selects a predictive coefficient candidate minimizing the predictive residual signal power as the optimum pre-filter coefficient from a plurality of pre-filter coefficient candidates determined by the pre-filter coefficient candidate calculating unit 26a. 
     In FIG. 3, the pre-filter 20a and the inverse filter 21a execute an inverse filtering process on each of pre-filter coefficient candidates of, for example, L in number stored in the coefficient code book 27a to makes a predictive residual signal r2(n)i, (i=1˜L). The square OR operation unit 51a determines a square OR of the predictive residual signal r2(n)i (where i=1˜L) to calculate the residual signal power. 
     The minimum value retrieving unit 52a retrieves the minimum value of L power values calculated by the square OR operation unit 51a. The pre-filter coefficient candidate based on the minimum operation value is outputted as the optimum pre-filter coefficient. 
     The minimum value retrieving unit 52a outputs a code number to the coefficient candidate code book 27a and outputs the corresponding pre-filter coefficient candidate information to the pre-filter 20a. 
     The optimum coefficient from the pre-filter coefficient candidate is determined every frame, for example, in a short time of about 20 ms. The code number showing the determined pre-filter coefficient information is outputted to the pre-filter 20a and the multiplexing unit 29a, and then is outputted to the speech decoding device through the transmission line. 
     The multiplexing unit 29a multiplexes the quantizing codes of predictive residual signals, the quantizing codes of predictive coefficients, and transmits the result to the speech decoding device through the transmission line. 
     FIG. 4 is a diagram showing a speech decoding device according to the first embodiment of the present invention. The speech decoding device, as shown in FIG. 4, executes substantially the procedure which is to the signal process in the speech coding device shown in FIG. 1. The speech decoding device includes an inverse quantizing unit 31a as an inverse quantizing means, a filter 33a as a third filter, a post process filter 34a as a fourth filter, a demultiplexing unit (DEMUX) 30a, a predictive coefficient inverse quantizing unit 32a, a frame delay unit 35a, and a coefficient calculating unit 36a. 
     The demultiplexing unit 30a demultiplexes a multiplexed signal inputted from the speech coding device via the transmission line. In this case, the multiplexed signal is separated into the quantizing codes of predictive residual signals, and the quantizing codes of predictive coefficients. 
     The inverse quantizing unit 31a inverse-quantizes a quantizing predictive residual signal based on a predictive residual signal quantizing code sent from the quantizing unit 22a in the speech coding device via the transmission. The predictive coefficient inverse quantizing unit 32a inverse-quantizes a quantizing predictive coefficient based on the predictive coefficient code sent from the predictive coefficient residual quantizing unit 23a via the transmission. 
     The filter 33a determines the filter characteristic based on a quantizing predictive residual coefficient obtained by the linear predictive analyzing unit 24a and the predictive coefficient quantizing unit 23a in the speech coding unit. The predictive residual signal from the inverse quantizing unit 31a is subjected to a filtering process using the resultant filter characteristic. 
     The post process filter 34a determines the filter characteristic based on a code number having a pre-filter coefficient information sent from the optimum coefficient selecting unit 28a in the speech coding device. The filter 33a executes a filtering process of the output signal in accordance with the resultant filter characteristic to output the outcome as a speech information. 
     The frame delay unit 35a inputs the predictive coefficient and the pre-filter coefficient inverse-quantized by the predictive coefficient inverse quantizing unit 32a to delay by 1-frame with respect to the current frame. 
     The coefficient calculating unit 36a inputs a code number showing a pre-filter coefficient information from the optimum coefficient selecting unit 28a and the predictive coefficient delayed from the frame delay unit 35a and calculates the filter coefficient of the post process filter 34a in the speech coding device. 
     When the code number as a pre-filter coefficient information from the optimum coefficient selecting unit 28a in the speech coding device has a characteristic which the pre-filter 20a passes an input speech signal without changing the signal characteristic, the post process filter 34a also has a characteristic which passes the input speech signal without any change in characteristic. 
     The speech coding device and the speech decoding device with the above configuration according to the first embodiment of the present invention will be explained below. 
     The pre-filter 20a executes an inverse filtering process of an input speech signal by using a desired pre-filter coefficient in a span where a change in the input spectrum is small and outputs the resultant a pre-filter predictive coefficient r1(n). 
     The inverse filter 21a executes an inverse filtering process on the pre-filter predictive residual signal r1(n) using a desired predictive coefficient to output a predictive residual signal r2(n). 
     Next, the quantizing unit 22a quantizes the predictive residual signal r2(n) and outputs the outcome to the multiplexing unit 29a. The predictive coefficient which determines the filter characteristic of the inverse-filter 21a is determined by inputting a pre-filter predictive residual signal r1(n) from the pre-filter 20a to the linear predictive analyzing unit 24a and then executing a linear predictive coding. 
     The pre-filter coefficients determining pre-filter characteristic of the prefilter 20a are determined as follows: 
     The frame delay unit 25a inputs the predictive coefficient information of a current frame and a pre-filter coefficient and extracts, for example, the predictive coefficient information and the pre-filter coefficient information of a frame preceding by 1-frame with respect to the current frame information. 
     The pre-filter coefficient candidate calculating unit 26a calculates a plurality of pre-filter coefficient candidates. Namely, the previous coefficient of the whole system including the pre-filter 20a is determined by subjecting the previous predictive coefficients and the pre-filter coefficients in an inputted previous frame to the convolutional operation given by the expression (4) in the convolutional operating unit 41a. 
     The first coefficients converting unit 42a converts the predictive coefficients of the whole system obtained by the convolutional operating unit 41a into the corresponding reflective coefficients. However, in concrete, the whole system predictive coefficients are determined by solving the expression (5). 
     The order truncating unit 43a truncates the lower coefficient of the (N+M)-th order reflective coefficients {kn} determined by the convolutional operating unit 41a and the first coefficient converting unit 42a to obtain the M-th order reflective coefficients. 
     The second coefficient converting unit 44a converts the reflective coefficients processed by the order truncating unit 43a into a predictive coefficient in accordance with the expression (6) to output the result as a pre-filter coefficient candidate. 
     The order converting operation using the above pre-filter coefficients means that the order cannot be truncated without processing the predictive coefficients. 
     There are two modes of the pre-filter coefficient candidate calculating methods. In one mode, the coefficient of the pre-filter 20a is a fixed M-th order and the pre-filter coefficient candidates calculated are accumulated and stored using the pre-filter coefficients and the predictive coefficients in plural past frames. The other mode, the coefficient of the pre-filter 20a is a variable order, and pre-filter coefficient candidates with various kinds of order are stored using the pre-filter coefficients and the predictive coefficients of, for example, the frame preceding by one frame. 
     The optimum coefficient selecting unit (selecting means) 28a selects a predictive coefficient candidate minimizing the predictive residual signal power as optimum predictive coefficients for the pre-filter from the plural pre-filter coefficient candidates determined by the pre-filter coefficient candidate calculating unit 26a and stored in the coefficient candidate code book 27a. 
     That is, in the optimum coefficient selecting unit 28a, the square OR operation unit 51a inputs a predictive residual signal r2(n) (where i=1˜L) and executes a square OR operation of the absolute value thereof. The predictive residual signal r2(n) is obtained by subjecting each of pre-filter coefficient candidates of, for example, L in number stored in the coefficient code book 27a to an inverse filtering process by the pre-filter 20a and the inverse filter 21a. 
     The minimum value retrieving unit 25a retrieves the minimum value in the L values calculated by the square OR operating unit 51a and selects the pre-filter coefficient candidate based on the retrieved minimum value as optimum pre-filter coefficients. 
     The pre-filter coefficients selected as pre-filter coefficients of the current frame is outputted as a code number showing a pre-filter coefficient information to the pre-filter 20a and the multiplexing unit 29a, and then transmitted to the speech decoding device via the transmission line. 
     The optimum coefficients from the pre-filter coefficient candidates is determined every frame, for example, in a short time of about 20 ms. In the input speech signal having a large change in spectrum, the multiplexing unit 29a inputs the quantizing predictive residual signal, the quantizing predictive coefficients. In this case, since the pre-filter 20a has filter coefficients which pass a speech signal without changing its characteristic, the input speech signal is outputted as a pre-filter predictive residual signal r1(n) without any change. 
     In the similar manner to the process of a speech signal with a small change in spectrum, the inverse filter 21a determines predictive coefficients to the pre-filter predictive residual signal r1(n), executes an inverse filtering process using the predictive coefficients, and outputs as a predictive residual signal r2(n). The quantizing unit 22a quantizes the predictive residual signal r2(n) and outputs the result to the multiplexing unit 29a. 
     The filter coefficient of the pre-filter 20a which has the characteristic passing a speech signal through the pre-filter 20a without changing its signal characteristic is calculated by the pre-filter coefficient candidate calculating means 26a, and stored the outcome in the coefficient candidate code book 27a. 
     In the speech coding device, when the multiplexing unit 29a inputs a quantizing predictive residual signal, quantizing predictive coefficients, and a code number and outputs to the speech decoding device via the transmission line, the speech decoding device reproduces speech by processing substantially in reverse flow to the process in the speech coding device. 
     The input signal through the transmission line is demultiplexed into the quantizing code of a predictive residual signal, and the quantizing code of a predictive coefficient, by using the demultiplexing unit 30a. The inverse-quantizing unit 31a inverse-quantizes using the quantizing code of a predictive residual signal to output a predictive residual signal. The predictive coefficient inverse quantizing unit 32a inverse-quantizes using the quantizing code of a predictive coefficient to output a predictive coefficient. 
     The filter 33a determines its filter characteristic based on a predictive coefficient from the predictive coefficient inverse-quantizing unit 32a and subjects the predictive residual signal from the inverse-quantizing unit 31a to a filtering process in accordance with the inverse characteristic of the inverse filter 21a, using the filter characteristic. The frame delay unit 35a extracts a predictive coefficient of a previous frame delayed by one frame from the current frame to output to the coefficient calculating unit 36a and outputs a code number as a pre-filter coefficient information from the optimum coefficient selecting unit 28a to the coefficient calculating unit 36a. 
     The coefficient calculating unit 36a determines the filter characteristic of the post process filter 34a of the current frame based on the above coefficient information. A filter process is performed to the output of the filter 33a based on the filter characteristic to reproduce speech signal. 
     In the speech coding device and the speech decoding device according to the first embodiment of the present invention, when the interframe correlation of predictive coefficients are small, the pre-filter 20a has a characteristic not to change the characteristic of an input speech signal (or so as to make the pre-filter 20a off). When the interframe correlation of predictive coefficients is large, the pre-filter 20a is controlled so as to be on. Thus a higher predictive gain can be obtained, comparing the use of the conventional N-th order analyzing filter, by selecting the optimum one from a plurality of pre-filter coefficient candidates, filtering inversely it, and executing an N-order linear predictive coding. Therefore an effective speech transmission and reproduction can be realized advantageously with a high predictive gain maintained. 
     When the pre-filter 20a is in an ON state, a high predictive gain can be obtained by adding only a code number (log2 L bit) as a side information corresponding the number of the pre-filter coefficient candidates, in addition to the conventional predictive residual signal and the predictive coefficients, to the speech decoding device from the speech coding device. 
     (b) Explanation of the Second Embodiment 
     FIG. 5 is a diagram showing a speech coding device according to the second embodiment of the present invention. Referring to FIG. 5, a speech coding device is constituted of a pre-filter 20b as a first filter, a bypass route 61b, a selector 62b, an inverse filter 21b as a second filter, a quantizing unit 22b as quantizing means, linear predictive analyzing means 24b, a frame delay unit 25b as predictive coefficient calculating means for the first filter, a coefficient candidate code book 27b, and an optimum coefficient selection unit (sharing the function as selector control means) 28b. 
     The pre-filter 20b, an inverse filter 21b, a quantizing unit 22b, a linear predictive analyzing unit 24b, a frame delay unit 25b, and a multiplexing unit 29b have the same functions as those of elements in the first embodiment. Hence the overlapped explanation is omitted here. 
     The bypass route 61 by-passes the pre-filter 20b. The selector 62b selects the pre-filter 20b or the bypass route 61b and outputs a pre-filter predictive residual signal. 
     The pre-filter coefficient calculating unit 26b determines, for example, a plurality of pre-filter coefficient candidates with different order. The pre-filter coefficient calculating unit 26b, as shown in FIG. 6, is formed of a convolutional operation unit 41b, a first coefficient converting unit 42b, an order truncating unit 43b, and a second coefficient converting unit 44b. 
     In the similar manner to that in the first embodiment, the pre-filter coefficient calculating unit 26b determines the above filter coefficient candidate by the convolutional operation unit 41b, the first coefficient converting unit 42b, the order truncating unit 43b, and the second coefficient converting unit 44b. However, the second embodiment differs from the first embodiment in that the filter coefficient with a characteristic which passes an input speech signal through the pre-filter 20b without a change in the signal characteristic is not calculated as a pre-filter coefficient candidate. 
     In the similar manner to that in the first embodiment, the coefficient code book 27b stores a plurality of pre-filter coefficient candidates calculated in the pre-filter coefficient candidate calculating unit 26b. There are two aspects to calculate a plurality of pre-filter coefficient candidates stored in the code book 27b, as seen similarly in the first embodiment. However, the filter coefficient which has a characteristic passing an input speech signal through the pre-filter 20b  without a change in the signal characteristic is not stored in the coefficient code book. 
     Like the optimum coefficient selecting unit 28a in the first embodiment, the optimum coefficient selecting unit 28b selects a predictive coefficient candidate minimizing a predictive residual signal from a plurality of pre-filter coefficient candidates determined by the pre-filter coefficient candidate calculating unit 26b. As shown in FIG. 7, the optimum coefficient selecting unit 28b is constituted of a square OR operation unit 51b, a minimum value retrieving unit 52b, and a comparing unit 53a. 
     The square OR operation unit 51b and the minimum value retrieving unit 52b have respectively the same functions as the square OR operation unit 51a and the minimum value retrieving unit 52a in the first embodiment. The comparing unit 53b compares the minimum value regarding a retrieved operating value with the reference value β in amplitude. 
     When the minimum value is smaller than the reference value β, a pre-filter coefficient candidate based on a predictive residual signal at the minimum value is selected as a optimum pre-filter coefficient and the corresponding code number is issued to the multiplexing unit 29b. At the same time, the selector 62b selects the pre-filter 20b to output a control signal as a selector selecting signal and a pre-filter ON information to the pre-filter coefficient candidate calculating unit 26b. 
     When the minimum value is larger than the reference value β, the comparing unit 53b outputs a control signal by which the selector 62b selects the bypass route 61b and outputs a pre-filter OFF information to the pre-filter coefficient candidate calculating unit 26b. 
     FIG. 8 is a diagram showing a speech decoding device according to the second embodiment of the present invention. The speech decoding device is constituted of an inverse quantizing unit 31b as inverse quantizing means, a filter 33b as the third filter, a post processing filter 34b as the fourth filter, a demultiplexing unit (DEMUX) 30b, a predictive coefficient inverse quantizing unit 32b, a frame delay unit 35b, a coefficient calculating unit 36b, a selector 64b for the post processing filter, a selector 64b for the coefficient calculating unit, a bypass route 65b for the post processing filter, and a bypass route 66b for the coefficient calculating unit. 
     The inverse quantizing unit 31b, the filter 33b, the post processing filter 34b, the demultiplexing unit (DEMUX) 30b, the predictive coefficient quantizing unit 32b, and the frame delay unit 35b correspond to the inverse quantizing unit 31a, the filter 33a, the post processing filter 34a, the demultiplexing unit (DEMUX) 30a, the predictive coefficient inverse-quantizing unit 32a, and the frame delay unit 35a in the first embodiment. Hence the duplicate explanation is omitted here. 
     The selector 63b for the post processing filter selects either the post processing filter 34b or the bypass route 65b for the post processing filter based on the code number from the optimum coefficient selecting unit 28b in the speech coding device. 
     The selector 64b for the coefficient calculation unit selects either the a previous coefficient information calculated by the coefficient calculating unit 36b or the bypass route 66b for the coefficient calculating unit in a through state where a coefficient is not inputted to the coefficient calculating unit 36b, based on the code number from the optimum coefficient selection unit 28b. 
     The speech coding device and the speech decoding device according to the second embodiment of the present invention have the above configuration and operate as follows: 
     When the input speech signal includes an input spectrum with a short changing span such as a stationary voiced periods, the square sum (power value) of the predictive residual signal from the optimum coefficient selecting unit 28b is smaller than the reference value. 
     Therefore in the speech coding device, the selector 62b selects the pre-filter 20b. This operation is similar to the inverse filtering process of the pre-filter 20a in the first embodiment. 
     In this case, in the decoding device, the selector 63b for the post processing filter selects the post processing filter 34b. The selector 64b for the coefficient calculating unit selects a previous coefficient information calculated by the coefficient calculating unit 36b. Therefore, the speech decoding device operates as the pre-filter 20a in the first embodiment performs an inverse filtering process. 
     In an input speech signal having a large spectrum input signal, when a square OR operation value of a predictive residual signal in the optimum coefficient selecting unit 28b is larger than a reference value, the selector 62b selects the bypass route 61b. 
     Like the pre-filter 20a in the first embodiment which outputs as a pre-filter predictive residual signal without any change in characteristic, a quantizing code of a predictive residual signal, a quantizing code of a predictive coefficient, and a code number including a pre-filter ON/OFF information are outputted. 
     The comparing unit 53b in the optimum coefficient selecting unit 28b outputs a control signal to select the bypass route 61b by the selector 62b. At the same time, the comparing unit 53b outputs a code number including a pre-filter OFF information to the multiplexing unit 29b and outputs a pre-filter OFF information to the pre-filter coefficient candidate calculating unit 26b. 
     In this case, in the speech decoding device, the selector for the post processing filter 63b selects the bypass route 65b for the post processing filter, and the selector 64b for the coefficient calculating unit selects the bypass route 66b for the coefficient calculating unit. Hence in the speech decoding device, the above same selectors operate in the similar manner that the pre-filter 20a in the first embodiment performs the filtering operation in accordance with a pre-filter coefficient passing through an input speech signal without a change in characteristic. 
     Thus, according to the speech coding device and a speech decoding device of the second embodiment of the present invention, when the interframe correlation of predictive coefficients are small, input speech signals are passed through the bypass route 61b by-passing the pre-filter 20b without a change in its characteristic (the pre-filter 20b is in off-state). When the interframe correlation of predictive coefficients is large, the pre-filter 20b is controlled so as to be in ON-state and the optimum candidate is selected from a plurality of pre-filter coefficient candidates. Sequentially the candidate is subjected to an inverse filtering process and then subjected to an N-th order linear predictive coding. As a result, a higher predictive gain is established comparing the use of only the conventional N-th order analyzing filter. There is an advantage in that an effective speech transmission and reproduction can be realized with a high predictive gain maintained. 
     When the pre-filter 20a is in an on state, a higher predictive gain can be obtained by adding only a code number as a side information in the speech coding device and the speech decoding device, the side information corresponding to the number of pre-filter coefficient candidates and including on/off information of the pre-filter 20b in addition of the conventional predictive residual signal and the predictive coefficient. 
     (c) Explanation of the Third Embodiment 
     FIG. 9 is a diagram showing a speech coding device according to the third embodiment of the present invention. The speech coding device shown in FIG. 9 is different from that of the first embodiment in that the optimum coefficient selecting unit 28c is of a different. 
     The optimum coefficient selecting unit 28c, as shown in FIG. 10, is formed of a square OR operation unit 51c and a minimum retrieving unit 52c. There is a difference in that the square OR operation unit 51a inputs each of pre-filter coefficient candidates of L in number stored in the coefficient code book 27a as pre-filter predictive residual signal r1(n)i(i=1˜L) subjected to a pre-filtering process by the pre-filter 20a and executes a square OR operation of the absolute value. The minimum value retrieving unit 52c functions similarly to that in the first embodiment. 
     FIG. 11 is a block diagram showing a speech decoding device according to the third embodiment of the present invention. Since the speech decoding device shown in FIG. 11 is similar to that in the first embodiment, the duplicate explanation will be omitted here. 
     According to the present invention, the speech coding device and the speech decoding device having the above configuration operates in the same manner to those in the first embodiment as the whole system. However, this embodiment is different from the first embodiment in a predictive residual signal inputted to the optimum coefficient selecting unit 28c. 
     In the speech coding device and the speech decoding device according to the third embodiment of the present invention, there is an advantage in that in order to select the optimum pre-filter coefficient in the optimum coefficient selecting unit 28c, even if a pre-filter predictive residual signal is inputted, an effective speech transmission and reproduction can be realized, like in the first and second embodiments, with a high predictive gain maintained, instead of a predictive residual signal from the inverse filter 21c. 
     In this case, when the pre-filter 20c is in ON state, the speech coding device adds only the code number as a side information corresponding to the number of the pre-filter coefficient candidates in addition to the conventional predictive residual signals and the predictive coefficients to the speech decoding device whereby a high predictive gain can be established. 
     (d) Explanation of the Fourth Embodiment 
     FIG. 12 is a diagram showing a speech coding device according to the fourth embodiment of the present invention. The speech coding device shown in FIG. 12 differs from that in the second embodiment in that there is no coefficient candidate code book 27b and a selector control unit 28d functioning only as selector control means in place of the optimum coefficient selecting unit 28b. Other elements are similar to those in the second embodiment. 
     That is, the pre-filter 20d is uniquely determined as a pre-filter coefficient from coefficient candidates calculated by the pre-filter coefficient calculating unit 26d. When the square OR operation value on the predictive residual signal r2(n) is smaller than the reference value β, the selector control unit 28d outputs a control signal so that the selector 62d is selectively connected to the pre-filter 20d. When the square OR operation value β is large, the selector 62d outputs a control signal and connects selectively to the by-pass route 61d. 
     In the speech coding device and the speech decoding device having the above configuration according to the fourth embodiment of the present invention, when the selector 62d selects the pre-filter 20d, the coefficient of the pre-filter 20d is uniquely determined as a pre-filter coefficient of a current frame in accordance with the M-th order coefficient of the previous frame. Other elements operate in the similar manner to those in the second embodiment. 
     According to the fourth embodiment of the present invention, when the interframe correlation of the predictive coefficient is small, the pre-filter 20b is by-passed by the bypass route 61b without changing the characteristic of the input speech signal (or the pre-filter 20b is made to an OFF state). When the interframe correlation of the predictive coefficient is large, the pre-filter 20b is made to an ON state and an N-th order linear predictive coding is performed. As a result, a higher predictive gain can be obtained as compared with the prior art using only an N-order coding filter. There is an advantage in that an effective speech transmission and reproduction can be realized with a high predictive gain maintained. 
     When the pre-filter 20b is in an ON state, a higher predictive gain can be advantageously obtained by adding an ON/OFF information of the pre-filter 20d in addition to an normal predictive residual signal and a predictive coefficient.