CA2144693A1 - Speech decoder - Google Patents
Speech decoderInfo
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- CA2144693A1 CA2144693A1 CA002144693A CA2144693A CA2144693A1 CA 2144693 A1 CA2144693 A1 CA 2144693A1 CA 002144693 A CA002144693 A CA 002144693A CA 2144693 A CA2144693 A CA 2144693A CA 2144693 A1 CA2144693 A1 CA 2144693A1
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Abstract
Short-term prediction code is produced through an analysis for a speech signal having a predetermined frame length and extraction of a spectral parameter of the speech signal. In an adaptive codebook each past excitation signal of a maximum integer lag length is stored. The excitation signals read out from the adaptive codebook is delayed in a predetermined pitch frequency range. Calculation of a delay value minimizing the weighted square error as a measure of the evaluation and gains corresponding to the delayed past excitations and searching an adaptive codevector as the optimum lag code representing the pitch correlation of the speech signals is performed. In an excitation codebook excitation codevectors as quantization codes representing residue signals after the long-term prediction is stored. The optimum excitation codevector is determined from the excitation codebook. The long-term prediction including lag code decimating and varying operation for varying the lag codes through decimating thereof.
Description
214~6g3 SPEECH CODER
BACKGROUND OF THE INVENTION
The present invention relates to a speech coder and, more particularly, to a CELP type speech coder for high quality coding of speech signals at as low bit rates as 8 to 4 kb/s.
Recently, digitalization of automobile telephones and cordless telephones through the use of radio waves have been in rapid advancement. The frequency band of the radio wave allocated for these kinds of telephone communications is limited, and development of low bit rate speech coding systems is important for the reduction of the frequency band.
As an example of well-known coding system of this type with a bit rate of about 8 to 4 kb/s, CELP
(Code-Excited LPC coding) has been proposed, as described in, for instance, M. Schroeder and B.S.
Atal, "Code-excited Linear Prediction: High Quality Speech at Low Bit Rates", ICASSP proceedings 85, pp.
937-940, 1985, published in U.S.A. (Literature 1).
In the CELP, which is a first prior art speech coder disclosed in Literature 1, the transmitting side executes the coding according to the following procedure. First, a short period prediction code representative of the frequency characteristics of the speech is extracted from the speech signal for each frame (for instance, 20 ms) (short term prediction). Then, the frame is divided into a 214469'~
-plurality of sub-frames having shorter length (of 5 ms, for instance). After extraction of a pitch parameter representative of a long-term correlation (i.e., pitch correlation) from a past excitation signal for each sub-frame, a speech signal of the sub-frame is long-term predicted from that pitch parameter. The long-term prediction is performed, by determining lag code representing the pitch correlation according to the following procedure, based on an adaptive codebook constituted by excitation signals (adaptive codevectors) obtained by delaying the past excitation signal for delay samples corresponding to various lag codes.
Adaptive codevectors corresponding to the respective lag codes are extracted by trying the lag codes in correspondence to the size of the codebook. Then, a synthesized signal is produced based on the extracted adaptive codevectors, and the error power between the synthesized signal and the speech signal is calculated. Next, the optimum lag code corresponding to the minimum calculated error power, the adaptive codevector corresponding to the optimum lag code and the corresponding gain are determined.
Subsequently, an excitation codevector minimizing the error power between the synthesized signal produced from the excitation vectors extracted from noise signals (excitation codebook) as quantization codes prepared in advance and a 214469~
.
residue signal obtained through the above long-term prediction, and the corresponding gain are determined (excitation codebook search). Thus determined adaptive codevector index and index representing the determined excitation codevector are transmitted together with the gains of the respective excitation signals and indexes representing kinds of the spectrum parameters.
The lag code of the adaptive codevector and the quantization code of the excitation codevector are searched according to the following method. First, a signal z(n) is calculated through performing the perceptual weighting and the subtraction of the past influence signal for the input speech signal x(n).
Next, a synthesis filter H, constituted by the spectral parameters obtained by the above short-term prediction, quantization and inverse quantization, is driven by codevector ej(n) of quantization code j to synthesize signal Hej(n). Then, the quantization code j minimizing the error power E
between the signal z(n) and Hej(n) are determined according to an equation (1).
N,- I .
(z[%]-~cj ~ tj[nD2 ( 1 ) neO
Here, N, represents the sub-frame length, H the matrix for realizing the synthesis filter, and g the gain of the codevector e;. In practice, the equation (1) is developed as follows:
214469~
~ zf~]2_Cjj (2) In the equation (2), the denumerator Cj represents cross-correlation, and the numerator Gj auto-correlation, which are developed from an equation(3) and (4).
Cj=~[~]~Cl~] (3) ~-1 Gj~L(~ [nD2 (4) The calculation of the auto- and cross-correlations Gj and Cj is performed through the driving of the synthesis filter, i.e., filtering, after calculation of the signal Hej(n). The operation of the filtering is performed to the extent corresponding to the codebook size as noted above. This means that a large amount of computations (i.e., number of times of multiplification and addition) is required for the frame under the process.
As a second prior art speech coder reducing the amount of computations for the long-term prediction, open and closed loop search of lag codes, which is disclosed in Japanese Patent Laid-open No. Hei 2-228581, entitled "Digital Speech Coder and Method for obtaining parameters used in the same Coder".
In this method, the preliminary selection of the lag code is performed by means of the open loop, and the search of the codes in the neighborhood of the lag code determined by the preliminary selection is performed by means of the closed loop. Thus, the long-term prediction is realized with prediction accuracy and with reduced operation amount.
Fig. 5 is a block diagram showing a CELP type speech coder which includes the above first and second prior art speech coders. The illustrated speech coder comprises a coder 1 for coding the input speech signal, a decoder 2 for decoding the coded signal, and a transmission line 3 for connecting the coder 1 and the decoder 2.
The coder 1 includes a buffer 11 for storing the speech signal supplied from an input terminal T1, an LPC analyzer 12 for calculating LPC
coefficients as the speech spectral parameter, a parameter quantizer 13 for quantizing the LPC
coefficients, a weighting circuit 14 for perceptual weighting the speech signal, an adaptive codebook 15 for storing past excitation signal, a long-term predictor 16 for searching an adaptive codevector as a lag code representing the pitch correlation, an excitation codebook 17 as a codebook including excitation codevector of sub-frame length representing the long-term prediction residue, an excitation codebook search circuit 18 for determining the optimum excitation codevector from the excitation codebook, a gain codebook 19 for storing parameters representing gains of the , adaptive codevector and the excitation codevector, a gain codebook search circuit 40 for determining quantization gains of the adaptive and excitation codevectors, and a multiplexer 41 for outputting the code series combination.
The excitation codebook 17 may be the noise codebook disclosed in Literature 1 or a learned codebook produced by means of learning with vector quantization (VQ) algorithm described in Japanese Patent Laid-open No. Hei 2-22955, or Japanese Patent Laid-open No. Hei 2-22956.
The decoder 2 comprises a de-multiplexer 21 for decoding the supplied transfer codes into predetermined code series, an adaptive codebook 22 which is the same as the adaptive codebook 15, an excitation codebook 23 which is the same as the excitation codebook 17, a gain codebook 24 which is the same as the gain codebook 19, a synthesis filter 25 for reproducing a speech signal based on the produced excitation and the speech synthesis filter, and a speech output terminal T0.
Fig. 6 is a block diagram showing the structure of the long-term predictor 16. This prior art long-term predictor 16 comprises a lag code generator 161 for varying the lag code by an amount corresponding to the adaptive codebook size, an adaptive codevector generator 162 for generating codevector ed(n) corresponding to the lag code d set 214~69~
in the lag code generator 161 based on the past signal stored in a codebook 166, a synthesis filter 163 for producing the weighted adaptive codevector H-ed(n) as a synthesized signal for the input of the adaptive codevector ed(n), an evaluation function calculator 164 for calculating an evaluation function representing the error power between the speech signal stored in the speech buffer and the synthesized signal H-ed(n), an optimum lag code determiner 165 for determining an optimum lag code CD based on the evaluation functions corresponding to all varied lag codes d, the codebook 166 as a buffer for storing such signals as the past excitation signal, residue signal, weighted signal or speech signal for the adaptive codebook search, and a speech buffer 167 for storing the speech signal in the coding interval and searching the lag code minimizing the error power for the speech signal.
Now, the processes of the speech coder in the prior art will be described with reference to Figs.
5 and 6. First in the coder 1, the speech signal is supplied from the input terminal T1 and stored in the buffer 11. The LPC analyzer 12 calculates the LPC coefficients of a predetermined sample speech signal stored in the buffer 11 by means of the short-term prediction analysis. The parameter quantizer 13 quantizes the LPC coefficients obtained in the LPC analyzer 12. Quantization code CL of the LPC coeffici~nt is thus supplied to the multiplexer 41, and is inversely quantized for a subsequent quantizing process.
The weighting circuit 14 performs the perceptual weighting for the speech signal stored in the buffer 11 using the quantized and inversely quantized LPC coefficients, and the perceptual weighted signal SW to the long-term predictor 16, excitation codebook search circuit 18 and codebook search circuit 40 to be used for subsequent codebook search.
Subsequently, codebook search of the signal SW
is performed by using the adaptive, excitation and gain codebooks 15, 17 and 19. First, the long-term predictor 16 performs the long-term prediction to determine the optimum lag code CD representing the pitch coorelation as will be described later and to generate the corresponding adaptive codevector, and the lag code CD is transferred to the multiplexer 41. The influence of the adaptive codevector is subtracted and the excitation codebook search circuit 18 performs the excitation codebook search to determine the quantization code CS and generates the excitation codevector. The quantized codevector CS is transferred to the multiplexer. After the adaptive and excitation codevectors are determined, the gain codebook search circuit 40 calculates the 21~4693 two excitations gains, and transfers the code CG
thereof to the multiplexer 41. In the multiplexer 41, the codes CL, CD, CS and CG are combined and converted into the transfer code CT, and the code CT
is transferred via the transmission line 3 to the decoder 2.
In the decoder 2, the de-multiplexer 21 decomposes the transfer code CT supplied from the transmission line 3 into the codes CL, CD, CS and CG. From the code CL corresponding to the LPC
coefficients, the filter coefficients are decoded to be transferred to the synthesis filter 25. From the lag code CD, the adaptive codevector is produced using the adaptive codebook 15. From the quantization code CS corresponding to the excitation, the excitation codevector is produced using the excitation codebook 17. From the code CG
corresponding to the gain, the gains of the adaptive and excitation codevectors are calculated. Each of the individual excitations is multiplied by the gain term to produce the synthesis filter input signals.
Finally, using the input signals the synthesis filter 25 synthesizes the speech signal which is to be output from the terminal T0.
Now, the operation of the long-term predictor 16 will be described with reference to Fig. 6.
First, the lag code generator 161 varies the lag code corresponding to the signal SW in the adaptive 214~693 codebook size, thus setting the lag code d. The delay code d preferably may be a code representative of the fractional lag, but it may be a code representative of the integral number lag as well.
After the adaptive codevector generator 162 produces the adaptive codevector ed(n) corresponding to the lag code d from the codebook 166, the synthesis filter 163 produces the weighted adaptive codevector H-ed(n) as a zero state synthesized signal with the input of the adaptive codevector ed(n). The evaluation function calculator 164 calculates the weighted adaptive codevector H-ed(n), cross-correlation Cd and auto-correlation Gd of the zero ~ input response subtraction signal z(n) stored in the speech buffer 167, and the evaluation function Cd2/Gd corresponding to the error power. The processes of the adaptive codevector generator 162, synthesis filter 163 and evaluation function calculator 164 are performed for all the lag codes as the subject of variation by the lag code generator 161. Then, the optimum lag code determiner 165 determines the lag code d corresponding to the maximum value of the evaluation function Cd/Gd as the optimum lag code CD.
SUMMARY OF THE INVENTION
The above first speech coder has a drawback that the codebook search in the long-term prediction requires a large amount of computations, so that it 214469~
is difficult to realize a speech coding with a low bit rate and enough quality.
The above second prior art speech coder also requires relatively huge amount of operations and provides difficulty in realizing the low bit rate and enough quality speech coder.
An object of the present invention is therefore to reduce the computation amount in the long-term prediction so as to realize a speech coder of as low bit rate as about 4 kb/s and enough speech quality.
According to the present invention, there is provided a speech coder comprising: speech analysis means for analyzing speech signal having a predetermined frame length to estimate a speech spectral parameter and generate a corresponding short-term prediction code, adaptive codebook storing means for storing each past excitation signal of a maximum integer lag length, long-term predicting means for delaying the excitation signals read out from the adaptive codebook storing means in a predetermined lag range, determining a lag value which minimizes the weighted square error as a measure of the evaluation and searches an adaptive codevector as the optimum lag code representing the pitch correlation of the speech signals, excitation codebook storing means for storing excitation codevectors as quantization codes representing residue signals after substracting output of the 214~69~
long-term prediction from the speech signal, and excitation codebook search means for determining the optimum excitation codevector from the excitation codebook, the long-term predicting means including lag code decimating and varying means for varying the delay codes through decimating thereof.
Here, the lag code decimating and varying means includes uniformlly decimating means for uniformly decimating the lag codes each for every predetermined number thereof. The uniformly decimating means may extract only odd lag codes.
The lag code decimating and varying means may include non-uniformly decimating means for decimating the lag codes according to a process of determining codes to be decimated by predetermined non-uniformly decimating. The non-uniformly ~ec;m~ting means may extract all lag codes with the short delays, whereas only even lag codes of long delays.
The long-term prediction means may further include sample decimating means for decimating with predetermined ratios the speech signal and weighted adaptive codevectors corresponding to the lag codes, and supplies the decimated speech signal and weighted adaptive codevectors to evaluation function calculating means for calculating the weighted square error. The sample decimating means may execute a down-sampling with a low-pass filter or simple decimating.
The long-term prediction means may include lag code candidate determining means for selecting a predetermined number of lag code candidates, and final lag code determining means for determining the optimum lag code among the lag code candidates.
Other objects and features will be clarified from the following description with reference to attached drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1 is a block diagram showing the structure of long-term predictor 16A according to a first embodiment of the present invention;
Fig. 2 is a block diagram showing the structure of long-term predictor 16B according to a second embodiment of the present invention;
Fig. 3 is a block diagram showing the structure of long-term predictor 16C according to a third embodiment of the present invention;
Fig. 4 is a block diagram showing the structure of long-term predictor 16D according to a fourth embodiment of the present invention;
Fig. 5 is a block diagram showing a CELP type speech coder including prior art speech coders; and Fig. 6 is a block diagram showing the structure of the long-term predictor 16 in the prior art speech coder.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
214g693 Fig. 1 is a block diagram showing the structure of long-term predictor 16A according to a first embodiment of the present invention. The long-term predictor 16A comprises the adaptive codevector generator 162, synthesis filter 163, evaluation function calculator 164, optimum delay code determiner 165, codebook 166 and speech buffer 167 in the prior art long-term predictor 16, and a uniformly decimated lag code genarator 168, which is provided in lieu of the lag code generator 161 and serves to vary the adaptive codebook lag code through the uniformly decimating thereof.
The operation of this embodiment will now be described with reference to Fig. 1. First, the uniformly decimated lag code genarator 168 varies the lag codes through the uniformly decimating thereof within the codebook size, thus setting lag codes d to be processed. For each lag code d, the adaptive codevector generator 162 generates the adaptive codevector ed(n), the synthesis filter 163 generates the weighted adaptive codevector H-ed(n), and the evaluation function calculator 164 calculates the evaluation function Cd/Gd. In the process of the uniformly decimating noted above, only odd delay codes are extracted. The processes of the adaptive codevector generation, the weighting adaptive codevector generation, the evaluation function calculation and the optimum lag code 214~693 determination as described above are like those in the prior art, and their detailed description is not given.
After the above processes for all the lag codes d to be varied, as in the prior art the optimum lag code determiner 165 determines and outputs the delay code d corresponding to the maximum value of the evaluation function Cd/Gd as the optimum lag code CD. As described above, in this embodiment the operation amount is reduced by decimating the lag code at the long-term prediction.
Fig. 2 is a block diagram showing the structure of a long-term predictor 16B according to a second embodiment of the present invention with constituent elements like those in Fig. 1 being designated by like reference numerals and symbols. The long-term predictor 16B is different from the long-term predictor 16A in the first embodiment in that it includes a non-uniformly decimated lag code generator 169, which is provided in lieu of the uniformly decimated lag code generator 168 and serves to vary adaptive codebook lag codes through non-uniformly decimating thereof.
The operation of this embodiment is the same as in the above first embodiment except for that the non-uniformly decimated lag code genarator 169 sets the lag code d to be processed by varying lag code through the non-uniformly decimating thereof within 214~693 the codebook size. In the process of the non-uniformly decimating, all lag codes with the short delays are extracted, whereas only even lag codes of long delays are extracted.
Fig. 3 is a block diagram showing the structure of long-term predictor 16C according to a third embodiment of the present invention, with constituent elements like those in Fig. 2 designated by like reference numerals. The long-term predictor 16C is different from the long-term predictor 16B in the second embodiment in that it includes, in addition to the non-uniformly decimated lag code genarator 169, sample decimation circuits 170 and 180 provided on the output side of the synthesis filter 163 and the speech buffer 167, respectively, for decimating the input signal to 1/D (a given integer).
In operation, as in the second embodiment, the non-uniformly decimated lag code generator 169 varies the lag codes through the non-uniformly decimating thereof in the codebook size, thus setting the delay codes d to be processed. For each lag d, the adaptive codevector generator 162 generates adaptive codevector ed(n), and the synthesis filter 163 generates the weighted adaptive codevector H-et(n). Then, the sample decimation circuit 170 executes sample decimating of the weighted adaptive codevector H-ed(n) to 1/D (D being D = 2, for instance) to generate decimated codevector H-ed(n)'. Likewise, the sample decimation circuit 180 executes the sample decimating of the coAi~g interval zero input response subtraction signal z(n) stored in the speech buffer 167 to 1/D
to generate the decimated input response subtraction signal z(n)'. The evaluation function calculator 164 calculates cross- and auto-functions Cd and Gd of the decimated codevector H-ed(n)' and the decimated zero input response subtraction signal z(n)'. As in the second embodiment, the evaluation function Cd/Gd is determined from the cross- and auto-correlations Cd and Gd. The sample decimating is executed through down-sampling with a low-pass filter or simple decimating. The other processes as noted above are executed in the same manner as in the second embodiment., In this embodiment, further computation amount reduction is realized by using the signal obtained through the sample decimating when executing the correlation calculation.
Fig. 4 is a block diagram showing the structure of long-term predictor 16D according to a fourth embodiment of the present invention, with constituent elements like those in Fig. 3 designated by like reference numerals and symbols. The long-term predictor 16D is different from the long-term predictor 16C in the third embodiment is 214~693 in that it includes a lag code candidate determiner 171, which preliminarily selects M lag code candidates, i.e., candidates of optimum lag code CD
based on the evaluation function Cd/Gd output from the evaluation function calculator 164 as reference, and a final lag code determiner 172, which is provided in lieu of the optimum lag code determiner 165 and determines the optimum lag code CD among the M lag code candidates.
In operation, the evaluation function Cd/Gd, obt~ine~ as a result of a process like that in the third embodiment for all the lag codes to be varied by the non-uniformly decimated lag code generator 169, is supplied to the lag code candidate determiner 171. The lag code candidate determiner 171 preliminarily selects M (M = 5, for instance) lag code candidates Dl to DM (i.e., DM=D5) with the evaluation function Cd/Gd. The final lag code determiner 172 determines the optimum lag code CD
among these lag code candidates Dl to D5 in a codebook search process as in the prior art.
In this embodiment, the sample decimating is used for the preliminary selection of the optimum lag code, and the lag codes corresponding to the preliminarily selected lag codes are used for retrieval as in the prior art. Thus, it is possible to reduce computation amount with the improved accuracy.
21446~3 While some preferred embodiments of the present invention have been described, they are by no means limitative, and various changes and modifications are possible.
For example, while the square of the cross-correlation divided by the auto-correlation has been used as the evaluation function, the similar effects may be obtained by utilizing only the square of the cross-correlation. Also, while the weighted adaptive codevector obtained based on the adaptive codevector has been used, it is possible to use as well the adaptive codevector itself without any synthesizing process to obtain the similar effects.
Further, instead of the signal stored in the speech buffer, the input speech signal, the residue signal or the perceptual weighted signal may be employed as the zero state subtraction signal. It is also possible to use the past input speech signal, the residue signal or the perceptual weighted signal instead of the past excitation signal as the codebook. Still further, while a process of direct filtering with the synthesis filter H has been used for the calculation of the cross- and auto-correlations, it is possible to use a process using an approximation equation as well to obtain the similar effects. For the approximation process, reference may be useful, for instance, IM. Trancoso and Atal, "Efficient Procedures for Finding the Optimum Innovation in Stocastic Coders", ICASSP
Proceedings 86, pp. 2375-2378, 1986, published in U.S.A. In lieu of selecting a single optimum lag code, a plurality of candidates may selected and the regular selection may be performed in the next step or simultaneous optimum lag code search may be performed to obtain the similar effects. Further, instead of using the LPC analyzer, it is possible as well to employ other analysis methods such as a BURG
method of extracting spectrum parameter to obtain the similar effects. It is obvious that other parameters such as PARCOR or LSP coefficients permit the similar effects to be obtained. Moreover, it is of course possible to construct the excitation codebook retrieval circuit as a multiple stage structure instead of the single stage structure without departing from the gist of the present invention.
As has been described in the foregoing, in the speech coder according to the present invention the long-term predictor comprising the lag code decimating and varying means for varying lag code through the decimating thereof. The decimating of the lag code reduces the number of lag codes to be retrieved, thus reducing the computation amount in the adaptive codebook search.
BACKGROUND OF THE INVENTION
The present invention relates to a speech coder and, more particularly, to a CELP type speech coder for high quality coding of speech signals at as low bit rates as 8 to 4 kb/s.
Recently, digitalization of automobile telephones and cordless telephones through the use of radio waves have been in rapid advancement. The frequency band of the radio wave allocated for these kinds of telephone communications is limited, and development of low bit rate speech coding systems is important for the reduction of the frequency band.
As an example of well-known coding system of this type with a bit rate of about 8 to 4 kb/s, CELP
(Code-Excited LPC coding) has been proposed, as described in, for instance, M. Schroeder and B.S.
Atal, "Code-excited Linear Prediction: High Quality Speech at Low Bit Rates", ICASSP proceedings 85, pp.
937-940, 1985, published in U.S.A. (Literature 1).
In the CELP, which is a first prior art speech coder disclosed in Literature 1, the transmitting side executes the coding according to the following procedure. First, a short period prediction code representative of the frequency characteristics of the speech is extracted from the speech signal for each frame (for instance, 20 ms) (short term prediction). Then, the frame is divided into a 214469'~
-plurality of sub-frames having shorter length (of 5 ms, for instance). After extraction of a pitch parameter representative of a long-term correlation (i.e., pitch correlation) from a past excitation signal for each sub-frame, a speech signal of the sub-frame is long-term predicted from that pitch parameter. The long-term prediction is performed, by determining lag code representing the pitch correlation according to the following procedure, based on an adaptive codebook constituted by excitation signals (adaptive codevectors) obtained by delaying the past excitation signal for delay samples corresponding to various lag codes.
Adaptive codevectors corresponding to the respective lag codes are extracted by trying the lag codes in correspondence to the size of the codebook. Then, a synthesized signal is produced based on the extracted adaptive codevectors, and the error power between the synthesized signal and the speech signal is calculated. Next, the optimum lag code corresponding to the minimum calculated error power, the adaptive codevector corresponding to the optimum lag code and the corresponding gain are determined.
Subsequently, an excitation codevector minimizing the error power between the synthesized signal produced from the excitation vectors extracted from noise signals (excitation codebook) as quantization codes prepared in advance and a 214469~
.
residue signal obtained through the above long-term prediction, and the corresponding gain are determined (excitation codebook search). Thus determined adaptive codevector index and index representing the determined excitation codevector are transmitted together with the gains of the respective excitation signals and indexes representing kinds of the spectrum parameters.
The lag code of the adaptive codevector and the quantization code of the excitation codevector are searched according to the following method. First, a signal z(n) is calculated through performing the perceptual weighting and the subtraction of the past influence signal for the input speech signal x(n).
Next, a synthesis filter H, constituted by the spectral parameters obtained by the above short-term prediction, quantization and inverse quantization, is driven by codevector ej(n) of quantization code j to synthesize signal Hej(n). Then, the quantization code j minimizing the error power E
between the signal z(n) and Hej(n) are determined according to an equation (1).
N,- I .
(z[%]-~cj ~ tj[nD2 ( 1 ) neO
Here, N, represents the sub-frame length, H the matrix for realizing the synthesis filter, and g the gain of the codevector e;. In practice, the equation (1) is developed as follows:
214469~
~ zf~]2_Cjj (2) In the equation (2), the denumerator Cj represents cross-correlation, and the numerator Gj auto-correlation, which are developed from an equation(3) and (4).
Cj=~[~]~Cl~] (3) ~-1 Gj~L(~ [nD2 (4) The calculation of the auto- and cross-correlations Gj and Cj is performed through the driving of the synthesis filter, i.e., filtering, after calculation of the signal Hej(n). The operation of the filtering is performed to the extent corresponding to the codebook size as noted above. This means that a large amount of computations (i.e., number of times of multiplification and addition) is required for the frame under the process.
As a second prior art speech coder reducing the amount of computations for the long-term prediction, open and closed loop search of lag codes, which is disclosed in Japanese Patent Laid-open No. Hei 2-228581, entitled "Digital Speech Coder and Method for obtaining parameters used in the same Coder".
In this method, the preliminary selection of the lag code is performed by means of the open loop, and the search of the codes in the neighborhood of the lag code determined by the preliminary selection is performed by means of the closed loop. Thus, the long-term prediction is realized with prediction accuracy and with reduced operation amount.
Fig. 5 is a block diagram showing a CELP type speech coder which includes the above first and second prior art speech coders. The illustrated speech coder comprises a coder 1 for coding the input speech signal, a decoder 2 for decoding the coded signal, and a transmission line 3 for connecting the coder 1 and the decoder 2.
The coder 1 includes a buffer 11 for storing the speech signal supplied from an input terminal T1, an LPC analyzer 12 for calculating LPC
coefficients as the speech spectral parameter, a parameter quantizer 13 for quantizing the LPC
coefficients, a weighting circuit 14 for perceptual weighting the speech signal, an adaptive codebook 15 for storing past excitation signal, a long-term predictor 16 for searching an adaptive codevector as a lag code representing the pitch correlation, an excitation codebook 17 as a codebook including excitation codevector of sub-frame length representing the long-term prediction residue, an excitation codebook search circuit 18 for determining the optimum excitation codevector from the excitation codebook, a gain codebook 19 for storing parameters representing gains of the , adaptive codevector and the excitation codevector, a gain codebook search circuit 40 for determining quantization gains of the adaptive and excitation codevectors, and a multiplexer 41 for outputting the code series combination.
The excitation codebook 17 may be the noise codebook disclosed in Literature 1 or a learned codebook produced by means of learning with vector quantization (VQ) algorithm described in Japanese Patent Laid-open No. Hei 2-22955, or Japanese Patent Laid-open No. Hei 2-22956.
The decoder 2 comprises a de-multiplexer 21 for decoding the supplied transfer codes into predetermined code series, an adaptive codebook 22 which is the same as the adaptive codebook 15, an excitation codebook 23 which is the same as the excitation codebook 17, a gain codebook 24 which is the same as the gain codebook 19, a synthesis filter 25 for reproducing a speech signal based on the produced excitation and the speech synthesis filter, and a speech output terminal T0.
Fig. 6 is a block diagram showing the structure of the long-term predictor 16. This prior art long-term predictor 16 comprises a lag code generator 161 for varying the lag code by an amount corresponding to the adaptive codebook size, an adaptive codevector generator 162 for generating codevector ed(n) corresponding to the lag code d set 214~69~
in the lag code generator 161 based on the past signal stored in a codebook 166, a synthesis filter 163 for producing the weighted adaptive codevector H-ed(n) as a synthesized signal for the input of the adaptive codevector ed(n), an evaluation function calculator 164 for calculating an evaluation function representing the error power between the speech signal stored in the speech buffer and the synthesized signal H-ed(n), an optimum lag code determiner 165 for determining an optimum lag code CD based on the evaluation functions corresponding to all varied lag codes d, the codebook 166 as a buffer for storing such signals as the past excitation signal, residue signal, weighted signal or speech signal for the adaptive codebook search, and a speech buffer 167 for storing the speech signal in the coding interval and searching the lag code minimizing the error power for the speech signal.
Now, the processes of the speech coder in the prior art will be described with reference to Figs.
5 and 6. First in the coder 1, the speech signal is supplied from the input terminal T1 and stored in the buffer 11. The LPC analyzer 12 calculates the LPC coefficients of a predetermined sample speech signal stored in the buffer 11 by means of the short-term prediction analysis. The parameter quantizer 13 quantizes the LPC coefficients obtained in the LPC analyzer 12. Quantization code CL of the LPC coeffici~nt is thus supplied to the multiplexer 41, and is inversely quantized for a subsequent quantizing process.
The weighting circuit 14 performs the perceptual weighting for the speech signal stored in the buffer 11 using the quantized and inversely quantized LPC coefficients, and the perceptual weighted signal SW to the long-term predictor 16, excitation codebook search circuit 18 and codebook search circuit 40 to be used for subsequent codebook search.
Subsequently, codebook search of the signal SW
is performed by using the adaptive, excitation and gain codebooks 15, 17 and 19. First, the long-term predictor 16 performs the long-term prediction to determine the optimum lag code CD representing the pitch coorelation as will be described later and to generate the corresponding adaptive codevector, and the lag code CD is transferred to the multiplexer 41. The influence of the adaptive codevector is subtracted and the excitation codebook search circuit 18 performs the excitation codebook search to determine the quantization code CS and generates the excitation codevector. The quantized codevector CS is transferred to the multiplexer. After the adaptive and excitation codevectors are determined, the gain codebook search circuit 40 calculates the 21~4693 two excitations gains, and transfers the code CG
thereof to the multiplexer 41. In the multiplexer 41, the codes CL, CD, CS and CG are combined and converted into the transfer code CT, and the code CT
is transferred via the transmission line 3 to the decoder 2.
In the decoder 2, the de-multiplexer 21 decomposes the transfer code CT supplied from the transmission line 3 into the codes CL, CD, CS and CG. From the code CL corresponding to the LPC
coefficients, the filter coefficients are decoded to be transferred to the synthesis filter 25. From the lag code CD, the adaptive codevector is produced using the adaptive codebook 15. From the quantization code CS corresponding to the excitation, the excitation codevector is produced using the excitation codebook 17. From the code CG
corresponding to the gain, the gains of the adaptive and excitation codevectors are calculated. Each of the individual excitations is multiplied by the gain term to produce the synthesis filter input signals.
Finally, using the input signals the synthesis filter 25 synthesizes the speech signal which is to be output from the terminal T0.
Now, the operation of the long-term predictor 16 will be described with reference to Fig. 6.
First, the lag code generator 161 varies the lag code corresponding to the signal SW in the adaptive 214~693 codebook size, thus setting the lag code d. The delay code d preferably may be a code representative of the fractional lag, but it may be a code representative of the integral number lag as well.
After the adaptive codevector generator 162 produces the adaptive codevector ed(n) corresponding to the lag code d from the codebook 166, the synthesis filter 163 produces the weighted adaptive codevector H-ed(n) as a zero state synthesized signal with the input of the adaptive codevector ed(n). The evaluation function calculator 164 calculates the weighted adaptive codevector H-ed(n), cross-correlation Cd and auto-correlation Gd of the zero ~ input response subtraction signal z(n) stored in the speech buffer 167, and the evaluation function Cd2/Gd corresponding to the error power. The processes of the adaptive codevector generator 162, synthesis filter 163 and evaluation function calculator 164 are performed for all the lag codes as the subject of variation by the lag code generator 161. Then, the optimum lag code determiner 165 determines the lag code d corresponding to the maximum value of the evaluation function Cd/Gd as the optimum lag code CD.
SUMMARY OF THE INVENTION
The above first speech coder has a drawback that the codebook search in the long-term prediction requires a large amount of computations, so that it 214469~
is difficult to realize a speech coding with a low bit rate and enough quality.
The above second prior art speech coder also requires relatively huge amount of operations and provides difficulty in realizing the low bit rate and enough quality speech coder.
An object of the present invention is therefore to reduce the computation amount in the long-term prediction so as to realize a speech coder of as low bit rate as about 4 kb/s and enough speech quality.
According to the present invention, there is provided a speech coder comprising: speech analysis means for analyzing speech signal having a predetermined frame length to estimate a speech spectral parameter and generate a corresponding short-term prediction code, adaptive codebook storing means for storing each past excitation signal of a maximum integer lag length, long-term predicting means for delaying the excitation signals read out from the adaptive codebook storing means in a predetermined lag range, determining a lag value which minimizes the weighted square error as a measure of the evaluation and searches an adaptive codevector as the optimum lag code representing the pitch correlation of the speech signals, excitation codebook storing means for storing excitation codevectors as quantization codes representing residue signals after substracting output of the 214~69~
long-term prediction from the speech signal, and excitation codebook search means for determining the optimum excitation codevector from the excitation codebook, the long-term predicting means including lag code decimating and varying means for varying the delay codes through decimating thereof.
Here, the lag code decimating and varying means includes uniformlly decimating means for uniformly decimating the lag codes each for every predetermined number thereof. The uniformly decimating means may extract only odd lag codes.
The lag code decimating and varying means may include non-uniformly decimating means for decimating the lag codes according to a process of determining codes to be decimated by predetermined non-uniformly decimating. The non-uniformly ~ec;m~ting means may extract all lag codes with the short delays, whereas only even lag codes of long delays.
The long-term prediction means may further include sample decimating means for decimating with predetermined ratios the speech signal and weighted adaptive codevectors corresponding to the lag codes, and supplies the decimated speech signal and weighted adaptive codevectors to evaluation function calculating means for calculating the weighted square error. The sample decimating means may execute a down-sampling with a low-pass filter or simple decimating.
The long-term prediction means may include lag code candidate determining means for selecting a predetermined number of lag code candidates, and final lag code determining means for determining the optimum lag code among the lag code candidates.
Other objects and features will be clarified from the following description with reference to attached drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
Fig. 1 is a block diagram showing the structure of long-term predictor 16A according to a first embodiment of the present invention;
Fig. 2 is a block diagram showing the structure of long-term predictor 16B according to a second embodiment of the present invention;
Fig. 3 is a block diagram showing the structure of long-term predictor 16C according to a third embodiment of the present invention;
Fig. 4 is a block diagram showing the structure of long-term predictor 16D according to a fourth embodiment of the present invention;
Fig. 5 is a block diagram showing a CELP type speech coder including prior art speech coders; and Fig. 6 is a block diagram showing the structure of the long-term predictor 16 in the prior art speech coder.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
214g693 Fig. 1 is a block diagram showing the structure of long-term predictor 16A according to a first embodiment of the present invention. The long-term predictor 16A comprises the adaptive codevector generator 162, synthesis filter 163, evaluation function calculator 164, optimum delay code determiner 165, codebook 166 and speech buffer 167 in the prior art long-term predictor 16, and a uniformly decimated lag code genarator 168, which is provided in lieu of the lag code generator 161 and serves to vary the adaptive codebook lag code through the uniformly decimating thereof.
The operation of this embodiment will now be described with reference to Fig. 1. First, the uniformly decimated lag code genarator 168 varies the lag codes through the uniformly decimating thereof within the codebook size, thus setting lag codes d to be processed. For each lag code d, the adaptive codevector generator 162 generates the adaptive codevector ed(n), the synthesis filter 163 generates the weighted adaptive codevector H-ed(n), and the evaluation function calculator 164 calculates the evaluation function Cd/Gd. In the process of the uniformly decimating noted above, only odd delay codes are extracted. The processes of the adaptive codevector generation, the weighting adaptive codevector generation, the evaluation function calculation and the optimum lag code 214~693 determination as described above are like those in the prior art, and their detailed description is not given.
After the above processes for all the lag codes d to be varied, as in the prior art the optimum lag code determiner 165 determines and outputs the delay code d corresponding to the maximum value of the evaluation function Cd/Gd as the optimum lag code CD. As described above, in this embodiment the operation amount is reduced by decimating the lag code at the long-term prediction.
Fig. 2 is a block diagram showing the structure of a long-term predictor 16B according to a second embodiment of the present invention with constituent elements like those in Fig. 1 being designated by like reference numerals and symbols. The long-term predictor 16B is different from the long-term predictor 16A in the first embodiment in that it includes a non-uniformly decimated lag code generator 169, which is provided in lieu of the uniformly decimated lag code generator 168 and serves to vary adaptive codebook lag codes through non-uniformly decimating thereof.
The operation of this embodiment is the same as in the above first embodiment except for that the non-uniformly decimated lag code genarator 169 sets the lag code d to be processed by varying lag code through the non-uniformly decimating thereof within 214~693 the codebook size. In the process of the non-uniformly decimating, all lag codes with the short delays are extracted, whereas only even lag codes of long delays are extracted.
Fig. 3 is a block diagram showing the structure of long-term predictor 16C according to a third embodiment of the present invention, with constituent elements like those in Fig. 2 designated by like reference numerals. The long-term predictor 16C is different from the long-term predictor 16B in the second embodiment in that it includes, in addition to the non-uniformly decimated lag code genarator 169, sample decimation circuits 170 and 180 provided on the output side of the synthesis filter 163 and the speech buffer 167, respectively, for decimating the input signal to 1/D (a given integer).
In operation, as in the second embodiment, the non-uniformly decimated lag code generator 169 varies the lag codes through the non-uniformly decimating thereof in the codebook size, thus setting the delay codes d to be processed. For each lag d, the adaptive codevector generator 162 generates adaptive codevector ed(n), and the synthesis filter 163 generates the weighted adaptive codevector H-et(n). Then, the sample decimation circuit 170 executes sample decimating of the weighted adaptive codevector H-ed(n) to 1/D (D being D = 2, for instance) to generate decimated codevector H-ed(n)'. Likewise, the sample decimation circuit 180 executes the sample decimating of the coAi~g interval zero input response subtraction signal z(n) stored in the speech buffer 167 to 1/D
to generate the decimated input response subtraction signal z(n)'. The evaluation function calculator 164 calculates cross- and auto-functions Cd and Gd of the decimated codevector H-ed(n)' and the decimated zero input response subtraction signal z(n)'. As in the second embodiment, the evaluation function Cd/Gd is determined from the cross- and auto-correlations Cd and Gd. The sample decimating is executed through down-sampling with a low-pass filter or simple decimating. The other processes as noted above are executed in the same manner as in the second embodiment., In this embodiment, further computation amount reduction is realized by using the signal obtained through the sample decimating when executing the correlation calculation.
Fig. 4 is a block diagram showing the structure of long-term predictor 16D according to a fourth embodiment of the present invention, with constituent elements like those in Fig. 3 designated by like reference numerals and symbols. The long-term predictor 16D is different from the long-term predictor 16C in the third embodiment is 214~693 in that it includes a lag code candidate determiner 171, which preliminarily selects M lag code candidates, i.e., candidates of optimum lag code CD
based on the evaluation function Cd/Gd output from the evaluation function calculator 164 as reference, and a final lag code determiner 172, which is provided in lieu of the optimum lag code determiner 165 and determines the optimum lag code CD among the M lag code candidates.
In operation, the evaluation function Cd/Gd, obt~ine~ as a result of a process like that in the third embodiment for all the lag codes to be varied by the non-uniformly decimated lag code generator 169, is supplied to the lag code candidate determiner 171. The lag code candidate determiner 171 preliminarily selects M (M = 5, for instance) lag code candidates Dl to DM (i.e., DM=D5) with the evaluation function Cd/Gd. The final lag code determiner 172 determines the optimum lag code CD
among these lag code candidates Dl to D5 in a codebook search process as in the prior art.
In this embodiment, the sample decimating is used for the preliminary selection of the optimum lag code, and the lag codes corresponding to the preliminarily selected lag codes are used for retrieval as in the prior art. Thus, it is possible to reduce computation amount with the improved accuracy.
21446~3 While some preferred embodiments of the present invention have been described, they are by no means limitative, and various changes and modifications are possible.
For example, while the square of the cross-correlation divided by the auto-correlation has been used as the evaluation function, the similar effects may be obtained by utilizing only the square of the cross-correlation. Also, while the weighted adaptive codevector obtained based on the adaptive codevector has been used, it is possible to use as well the adaptive codevector itself without any synthesizing process to obtain the similar effects.
Further, instead of the signal stored in the speech buffer, the input speech signal, the residue signal or the perceptual weighted signal may be employed as the zero state subtraction signal. It is also possible to use the past input speech signal, the residue signal or the perceptual weighted signal instead of the past excitation signal as the codebook. Still further, while a process of direct filtering with the synthesis filter H has been used for the calculation of the cross- and auto-correlations, it is possible to use a process using an approximation equation as well to obtain the similar effects. For the approximation process, reference may be useful, for instance, IM. Trancoso and Atal, "Efficient Procedures for Finding the Optimum Innovation in Stocastic Coders", ICASSP
Proceedings 86, pp. 2375-2378, 1986, published in U.S.A. In lieu of selecting a single optimum lag code, a plurality of candidates may selected and the regular selection may be performed in the next step or simultaneous optimum lag code search may be performed to obtain the similar effects. Further, instead of using the LPC analyzer, it is possible as well to employ other analysis methods such as a BURG
method of extracting spectrum parameter to obtain the similar effects. It is obvious that other parameters such as PARCOR or LSP coefficients permit the similar effects to be obtained. Moreover, it is of course possible to construct the excitation codebook retrieval circuit as a multiple stage structure instead of the single stage structure without departing from the gist of the present invention.
As has been described in the foregoing, in the speech coder according to the present invention the long-term predictor comprising the lag code decimating and varying means for varying lag code through the decimating thereof. The decimating of the lag code reduces the number of lag codes to be retrieved, thus reducing the computation amount in the adaptive codebook search.
Claims (8)
1. A speech coder comprising:
speech analyzing means for analyzing speech signal having a predetermined frame length to extract a spectral parameter of the speech signal and generate a corresponding short-term prediction code;
adaptive codebook storing means for storing each past excitation signal;
long-term predicting means for delaying the excitation signals read out from the adaptive codebook storing means in a predetermined lag range, determining a lag value which minimizes the weighted square error as a measure of the evaluation and retrieves an adaptive codevector as the optimum lag code, excitation codebook storing means for storing excitation codevectors as quantization codes representing residue signals after subtracting output of the long-term prediction from the speech signal; and excitation codebook search means for determining the optimum excitation codevector from the excitation codebook, the long-term predicting means including lag code decimating and varying means for varying the lag codes through decimating thereof.
speech analyzing means for analyzing speech signal having a predetermined frame length to extract a spectral parameter of the speech signal and generate a corresponding short-term prediction code;
adaptive codebook storing means for storing each past excitation signal;
long-term predicting means for delaying the excitation signals read out from the adaptive codebook storing means in a predetermined lag range, determining a lag value which minimizes the weighted square error as a measure of the evaluation and retrieves an adaptive codevector as the optimum lag code, excitation codebook storing means for storing excitation codevectors as quantization codes representing residue signals after subtracting output of the long-term prediction from the speech signal; and excitation codebook search means for determining the optimum excitation codevector from the excitation codebook, the long-term predicting means including lag code decimating and varying means for varying the lag codes through decimating thereof.
2. The speech coder according to claim 1, wherein the lag code decimating and varying means includes uniformly decimating means for uniformly decimating the lag codes each for every predetermined number thereof.
3. The speech coder according to claim 1, wherein the uniformly decimating means extracts only odd lag codes.
4. The speech coder according to claim 1, wherein the lag code decimating and varying means includes non-uniform decimating means for decimating the lag codes according to a process of determining codes to be decimated by predetermined non-uniform decimating.
5. The speech coder according to claim 1, wherein the non-uniform decimating means extracts all lag codes with the short delays, whereas only even lag codes of long delays.
6. The speech coder according to claim 1, wherein the long-term predicting means further includes sample decimating means for decimating with predetermined ratios the speech signal corresponding to the lag code, and supplies the decimated speech signal and decimated weighted adaptive codevectors to evaluation function calculating means for calculating the weighted square error.
7. The speech coder according to claim 1, wherein the sample decimating means execute a down-sampling with a low-pass filter or simple decimating.
8. The speech coder according to claim 1, wherein the long-term predicting means includes:
lag candidate determining means for selecting a predetermined number of lag candidates; and final lag code determining means for determining the optimum lag codes among the lag candidates.
lag candidate determining means for selecting a predetermined number of lag candidates; and final lag code determining means for determining the optimum lag codes among the lag candidates.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP18325794A JP3230380B2 (en) | 1994-08-04 | 1994-08-04 | Audio coding device |
| JP183257/1994 | 1994-08-04 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA2144693A1 true CA2144693A1 (en) | 1996-02-05 |
Family
ID=16132509
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA002144693A Abandoned CA2144693A1 (en) | 1994-08-04 | 1995-03-15 | Speech decoder |
Country Status (2)
| Country | Link |
|---|---|
| JP (1) | JP3230380B2 (en) |
| CA (1) | CA2144693A1 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| GB9911737D0 (en) * | 1999-05-21 | 1999-07-21 | Philips Electronics Nv | Audio signal time scale modification |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3249144B2 (en) * | 1991-03-29 | 2002-01-21 | 株式会社東芝 | Audio coding device |
-
1994
- 1994-08-04 JP JP18325794A patent/JP3230380B2/en not_active Expired - Lifetime
-
1995
- 1995-03-15 CA CA002144693A patent/CA2144693A1/en not_active Abandoned
Also Published As
| Publication number | Publication date |
|---|---|
| JPH0844396A (en) | 1996-02-16 |
| JP3230380B2 (en) | 2001-11-19 |
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