Speech coding by code-edited linear prediction

• US 5,787,391 A
• Filed: 06/05/1996
• Issued: 07/28/1998
• Est. Priority Date: 06/29/1992
• Status: Expired due to Term

• Current Assignee: Nippon Telegraph and Telephone Corporation
• Original Assignee: Nippon Telegraph and Telephone Corporation
• Inventors: Hayashi, Shinji, Kataoka, Akitoshi, Omuro, Hitoshi, Moriya, Takehiro, Miki, Satoshi, Mano, Kazunori
• Primary Examiner(s): MacDonald, Allen R.
• Assistant Examiner(s): Opsasnick, Michael N.
• Application Number:
  US08/658,303
• Time in Patent Office: 783 Days
• Field of Search: 395/2.09, 395/2.1, 395/2.14-2.18, 395/2.28-2.32, 395/2.35-2.37, 395/2.39
• US Class Current: 704/225
• CPC Class Codes: G10L 19/005 Correction of errors induced by the transmission channel, if related to the coding algorithm
• CPC Class Codes: G10L 19/06 Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients
• CPC Class Codes: G10L 19/07 Line spectrum pair [LSP] vocoders
• CPC Class Codes: G10L 19/08 Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
• CPC Class Codes: G10L 19/083 the excitation function being an excitation gain G10L25/90 takes precedence
• CPC Class Codes: G10L 19/12 the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
• CPC Class Codes: G10L 19/135 Vector sum excited linear prediction [VSELP]
• CPC Class Codes: G10L 2019/0001 Codebooks
• CPC Class Codes: G10L 2019/0002 Codebook adaptations
• CPC Class Codes: G10L 2019/0003 Backward prediction of gain
• CPC Class Codes: G10L 2019/0005 Multi-stage vector quantisation

Abstract

In a speech coding method of the present invention, initially, a plurality of samples of speech data are analyzed by a linear prediction analysis and thereby prediction coefficients are calculated. Then, the prediction coefficients are quantized, and the quantized prediction coefficients are set in a synthesis filter. Moreover, a pitch period vector is selected from an adaptive codebook in which a plurality of pitch period vectors are stored, and the selected pitch period vector is multiplied by a first gain which is obtained, at the same time, with a second gain. In addition, a noise waveform vector is selected from a random codebook in which a plurality of the noise waveform vectors are stored, and is multiplied by a predicted gain and the second gain. Then, the speech vector is synthesized by exciting the synthesis filter with the pitch period vector multiplied by the first gain, and with the noise waveform vector multiplied by the predicted gain and the second gain. Consequently, speech data comprising a plurality of samples are coded as a unit of a frame operation. Furthermore, the predicted gain multiplied by the noise waveform vector which is selected in a subsequent frame operation, is predicted based on the current noise waveform vector which is multiplied by the predicted gain and the second gain at the current frame operation, and also the previous waveform vector which is multiplied by the predicted gain and the second gain in the previous frame operation.

Claims

1. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

selecting one vector from among a plurality of stored vectors in a storing means;

multiplying a ratio constant (g) of a weighted mean by said selected one vector and outputting a fourth product;

multiplying a ratio constant (1-g ) of the weighted mean by a vector selected during processing of the frame immediately preceding the current frame operation and outputting a fifth product;

obtaining said quantized LSP parameter by adding the fourth product to the fifth product;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector which will minimize the distortion data at the time of selecting the one vector;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein the step of encoding encodes the selected another vector.

7. A method in accordance with any one of claims 1-6 wherein a ratio constant (g, 1-g, gk, 1-gk, g1, g2, 1-g1, 1-g2) of the weighted mean differs with each vector element by which said ratio constant is multiplied.

8. A method in accordance with claim 7, wherein each vector is expressed by the sum of a plurality of vectors comprising different dimensions.

9. A method in accordance with claim 8, wherein the step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and selects a prediction gain based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

10. A method in accordance with claim 7, wherein said step for selecting said another vector to minimize the distortion data within said quantizing step comprises, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p-dimensional vector (w1, w2, w3, . . . wp-2, wp-1, wp) selected from said vector storing means, adjusting said parameters when the relationship 0<

w1<

w2<

w3<

. . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

11. A method in accordance with claim 10, wherein the step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and selects a prediction gain based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

12. A method in accordance with claim 7, wherein said step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

13. A method in accordance with any one of claims 1-6, wherein each vector is expressed by the sum of a plurality of vectors comprising different dimensions.

14. A method in accordance with claim 13, wherein said step for selecting said another vector to minimize the distortion data within said quantizing step comprises, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p-dimensional vector (w1, w2, w3, . . . wp-2, wp-1, wp) selected from said vector storing means, adjusting said parameters when the relationship 0<

w1<

w2<

w3<

. . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

15. A method in accordance with claim 14, wherein the step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and selects a prediction gain based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

16. A method in accordance with claim 13, wherein said step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and selects a prediction gain based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of;

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

17. A method in accordance with one of claims 1-6, wherein said step for selecting said another vector to minimize the distortion data within said quantizing step comprises, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p-dimensional vector (w1, w2, w3, . . . wp-2, wp-1, wp) selected from said vector storing means, adjusting said parameters when the relationship 0<

w1<

w2<

w3<

. . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

18. A method in accordance with claim 17, wherein the step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis and selects a prediction gain based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth product, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

19. A method in accordance with any one of claims 1-6, wherein said step of calculating a prediction gain includes the step of calculating the prediction gain by linear prediction analysis based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation, and wherein said step of multiplying and outputting a second product comprises the steps of:

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth products, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product.

2. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

selecting one vector from among a plurality of stored vectors in a storing means;

obtaining the sum of vectors selected in the current frame operation and in n previous frame operations;

obtaining said quantized LSP parameter by means of dividing the sum of vectors by n+1;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector which will minimize the distortion data at the time of selecting the one vector;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein the step of encoding encodes the selected another vector.

3. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

selecting a first vector from among a plurality of vectors in a storing means;

selecting a second vector from among a plurality of vectors stored in a separate vector storing means;

obtaining the sum of vectors selected in current frame operation and n previous frame operations;

obtaining said quantized LSP parameter by dividing the sum of vectors by n+2;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector which will minimize the distortion data at a time of selecting the first and second vectors;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein the step of encoding encodes the first and second vectors.

4. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

multiplying a ratio constant (gk) of a weighted mean by a plurality of stored vectors in a storing means;

selecting one vector from among said multiplied vectors in a storing means;

multiplying a ratio constant (1-gk) of the weighted mean by said selected vector during processing of the frame immediately preceding the current frame operation and outputting a fourth product;

obtaining said quantized LSP parameter by adding the selected vector and the fourth product;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector which will minimize the distortion data at a time of selecting a vector;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein the step of encoding encodes the selected another vector.

5. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

selecting one vector from among a plurality of vectors in a storing means;

multiplying a ratio constant (g1) of a first weighted mean by said one selected vector and outputting a fourth product;

multiplying a ratio constant (g2) of a second weighted mean by said selected one vector and outputting a fifth product;

selecting either one of the fourth product or the fifth product;

multiplying a ratio constant (1-g2) of a third weighted mean by a product selected during processing of the frame operation immediately preceding the current frame operation and outputting a sixth product;

multiplying a ratio constant (1-g2) of a fourth weighted mean by a product selected during processing of the frame operation immediately preceding the current frame operation and outputting a seventh product;

selecting one of the sixth and seventh products;

obtaining said quantized LSP parameter by means of adding the selected first or second product and the selected third or fourth product;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector to minimize the distortion data;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein said encoding step encodes the selected another vector.

6. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation, wherein said quantizing step comprises the steps of;

selecting one vector from among a plurality of vectors stored in a storing means;

multiplying a ratio constant (g1) of a first weighted mean by said one vector and outputting a fourth product;

multiplying a ratio constant (g2) of a second weighted mean by said one vector and outputting a fifth product;

selecting either one of the fourth and fifth products;

processing each frame operation from the frame operation immediately preceding the current frame operation to previous frame operations, in which said processing comprises the steps of;

multiplying a first ratio constant of a predetermined weighted mean by one vector selected during processing of a previous frame operation and outputting a sixth product;

multiplying a second ratio constant of a predetermined weighted mean by a vector selected during processing of a previous frame operation and outputting a seventh product;

selecting either the sixth or seventh product;

summing the vectors selected during the processing step;

obtaining said quantized LSP parameter by adding the selected fourth or fifth product and the summed vectors;

calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter; and

selecting another vector to minimize the distortion data;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding, wherein the step of encoding encodes the another vector, first or second product, and summed vectors.

20. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

vector storing means for storing a plurality of vectors;

selecting means for selecting one vector from among a plurality of vectors stored in said vector storing means;

first multiplying means for multiplying a ratio constant of a weighted mean by said one vector selected by said selecting means;

second multiplying means for multiplying a ratio constant of the weighted mean by a vector selected by said selecting means during processing of the frame operation immediately preceding the current frame operation;

adding means for obtaining said quantized LSP parameter by adding an output vector of said first multiplying means and an output vector of said second multiplying means;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data at the time of selecting a vector by said selecting means; and

supply means for supplying identification information of a vector selected by said selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

26. A speech coding apparatus in accordance with one of claims 20-25, wherein said ratio constant (g, 1-g, gk, 1-gk, g1, g2, 1-g1, 1-g2) of the weighted mean differs for each vector by which said ratio constant is multiplied.

27. A speech coding apparatus in accordance with claim 26, wherein each vector stored in said vector storing means is expressed by the sum of a plurality of vectors comprising different dimensions.

28. A speech coding apparatus in accordance with claim 27, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

29. A speech coding apparatus in accordance with claim 26, wherein said control means, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p dimensional vector {w1, w2, w3, . . . wp-2, wp-1, wp} selected from said vector storing means, adjusts said parameters when the relationship 0<

w1<

w2<

w3 . . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

30. A speech coding apparatus in accordance with claim 29, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

31. A speech coding apparatus in accordance with claim 26, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

32. A speech coding apparatus in accordance with one of claims 20-25, wherein each vector stored in said vector storing means is expressed by the sum of a plurality of vectors comprising different dimensions.

33. A speech coding apparatus in accordance with claim 32, wherein said control means, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p dimensional vector {w1, w2, w3, . . . wp-2, wp-1, wp} selected from said vector storing means, adjusts said parameters when the relationship 0<

w1<

w2<

w3 . . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

34. A speech coding apparatus in accordance with claim 33, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

35. A speech coding apparatus in accordance with claim 32, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

36. A speech coding apparatus in accordance with one of claims 20-25, wherein said control means, with regard to parameters w1, w2, w3, . . . wp-2, wp-1, wp comprising p dimensional vector {w1, w2, w3, . . . wp-2, wp-1, wp} selected from said vector storing means, adjusts said parameters when the relationship 0<

w1<

w2<

w3 . . . wp-2<

wp-1<

wp<

p is not satisfied, so as to satisfy said relationship.

37. A speech coding apparatus in accordance with claim 36, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

38. A speech coding apparatus in accordance with one of claims 20-25, wherein said gain adapting means calculates said prediction gain by conducting linear prediction analysis based on a power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation, and wherein said gain multiplying means comprises:

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means.

21. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

vector storing means for storing a plurality of vectors;

selecting means for selecting one vector from among a plurality of vectors stored in said vector storing means;

adding means for summing vectors selected by said selecting means for the current frame operation and for each of n frame operations previous to the current frame operation;

dividing means for calculating said quantized LSP parameter by dividing an output vector of said adding means by n+1;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data calculated by said distortion data calculating means at the time of selecting a vector by said selecting means; and

supply means for supplying a vector selected by said selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

22. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

first vector storing means for storing a plurality of vectors;

first selecting means for selecting one vector from among a plurality of vectors stored in said first vector storing means;

second vector storing means for storing a plurality of vectors;

second selecting means for selecting one vector from among a plurality of vectors stored in said second vector storing means;

first adding means for summing vectors selected by said first selecting means for the current frame operation and for each of n frame operations previous to the current frame operation for each vector;

second adding means for adding an output vector of said first adding means and said vector selected by said second selecting means;

dividing means for obtaining said quantized LSP parameter by dividing on output vector of said second adding means by n+2;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data calculated by said distortion data calculating means at the time of selecting vectors by said first selecting means and said second selecting means; and

supply means for supplying vectors selected by said first selecting means and said second selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

23. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

vector storing means for storing a plurality of vectors;

multiplying means for multiplying a ratio constant of the weighted mean by each vector stored in said vector storing means;

selecting means for selecting one vector from among said multiplied vectors;

multiplying means for multiplying a ratio constant of the weighted mean by said vector selected by said selecting means during processing of the frame operation immediately preceding the current frame operation;

adding means for obtaining said quantized LSP parameter by adding an output vector of said selecting means and an output vector of said multiplying means;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data calculated by said distortion data calculating means at the time of selecting a vector by said selecting means; and

supply means for supplying a vector selected by said selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting mean;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

24. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

vector storing means for storing a plurality of vectors;

first selecting means for selecting one vector from among a plurality of vectors stored in said vector storing means;

first multiplying means for multiplying a ratio constant of a first weighted mean by said one vector selected by said first selecting means;

second multiplying means for multiplying a ratio constant of a second weighted mean by said one vector selected by said first selecting means;

second selecting means for selecting one vector from among an output vector of said first multiplying means and an output vector of said second multiplying means;

third multiplying means for multiplying a ratio constant of a third weighted mean by said vector selected by said first selecting means during processing of the frame operation immediately preceding the current frame operation;

fourth multiplying means for multiplying a ratio constant of a fourth weighted mean by said vector selected by said first selecting means during processing of the frame operation immediately preceding the current frame operation;

third selecting means for selecting one vector from among an output vector of said third multiplying means and an output vector of said fourth multiplying means;

adding means for obtaining said quantized LSP parameter by adding an output vector of said second selecting means and an output vector of said third selecting means;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data calculated by said distortion data calculating means at the time of selecting the vectors by said first selecting means, said second selecting means and said third selecting means; and

supply means for supplying identification information of the vectors selected by said first selecting means, said second selecting means and said third selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

25. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process, wherein said vector quantizing means comprises;

vector storing means for storing a plurality of vectors;

first selecting means for selecting one vector from among a plurality of vectors stored in said vector storing means;

first multiplying means for multiplying a ratio constant of a first weighted mean by said one vector selected by said first selecting means;

second multiplying means for multiplying a ratio constant of a second weighted mean by said one vector selected by said first selecting means;

second selecting means for selecting one vector from among an output vector of said first multiplying means and an output vector of said second multiplying means;

multistage weighting means processing means for conducting processing of each frame operation from the frame operation immediately preceding the current frame operation to a frame operation n frame operations previous to the current frame operation, said processing means comprising;

multiplying means for multiplying a ratio constant of a predetermined weighted mean by a vector selected by said first selecting means during processing of a previous frame operation;

separate multiplying means for multiplying a ratio constant of the predetermined weighted mean by a vector selected by said first selecting means during processing of a previous frame operation; and

selecting means for selecting a vector from among output vectors of said multiplying means;

first adding means for obtaining the sum of n vectors selected by said multistage weighting means;

second adding means for obtaining said quantized LSP parameter by adding an output vector of said second selecting means and an output vector of said first adding means;

distortion data calculating means for calculating the distortion data between an LSP parameter before quantization and said quantized LSP parameter;

control means for selecting a vector which will minimize the distortion data calculated by said distortion data calculating means at the time of selecting a vector by said selecting means; and

supply means for supplying a vector selected by said selecting means to said code outputting means;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.

39. A method for coding speech data in units of frames comprising the steps of:

forming a vector from speech signals comprising a plurality of samples as a unit of frame operation;

storing said vector as a speech input vector;

sequentially checking, one frame at a time, an amplitude of each speech input vector, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

conducting linear prediction analysis and calculating a linear prediction coefficient (LPC) for each checked speech input vector;

converting each calculated LPC coefficient into a line spectrum pair (LSP) parameter;

quantizing said LSP parameter using a vector quantizing process, the quantized LSP parameter being expressed by a weighted mean vector of a plurality of vectors from a current frame operation and at least one previous frame operation;

converting said quantized LSP parameter into a quantized LPC coefficient;

synthesizing a synthetic speech vector based on an external driving vector and said quantized LPC coefficient;

selecting a first pitch period vector from among a plurality of pitch period vectors;

selecting a first noise waveform vector from among a plurality of noise waveform vectors;

calculating a prediction gain for the first noise waveform vector using linear prediction analysis based on the power of the first product multiplied by a gain during processing of said second product for the current frame operation, and the power of the first product multiplied by a gain during the processing of said second product for the at least one previous frame operation;

multiplying said prediction gain by said first noise waveform vector and outputting a first product;

multiplying a gain selected from among a plurality of gains by said first pitch period vector and outputting a second product, wherein said step of multiplying and outputting a second product comprises the steps of;

multiplying a first gain selected from among a plurality of gains stored in a first predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a third product;

multiplying a second gain selected from among a plurality of gains stored in a second predetermined gain storing means by half of the selected first pitch period vector and half of said first product thereby obtaining a fourth product;

summing the third and fourth products, and outputting the sum as the second product; and

summing the first product multiplied by the first gain and the first product multiplied by the second gain and outputting the sum as the third product;

multiplying said selected gain by said first product and outputting a third product;

adding the second and third products, and supplying the sum as said driving vector;

calculating distortion data by subtracting said synthetic speech vector from said checked speech input vector;

weighting said calculated distortion data;

calculating a distortion power of said distortion data with regard to the weighted distortion data;

selecting a second pitch period vector that will provide a minimum distortion power from among the plurality of pitch period vectors;

selecting a second noise waveform vector that will provide a minimum distortion power from among the plurality of noise waveform vectors; and

encoding the second pitch period vector and second noise waveform vector into bit series, adding as necessary error correctional coding.

40. A speech coding apparatus comprising:

a buffer for forming a vector from speech signals comprising a plurality of samples as a unit of frame operation, and storing said vector as a speech input vector;

amplitude limiting means for sequentially checking, one frame at a time, the amplitude of each speech input vector stored in said buffer, and compressing said amplitude when the absolute value of said amplitude exceeds a predetermined value;

linear prediction coefficient (LPC) analyzing means for conducting linear prediction analysis and calculating an LPC coefficient for each speech input vector outputted by said amplitude limiting means;

LPC parameter converting means for converting each LPC coefficient calculated by said LPC analyzing means into a line spectrum pair (LSP) parameter;

vector quantizing means for quantizing each of said LSP parameters by using a vector quantizing process;

LPC coefficient converting means for converting said quantized LSP parameters into quantized LPC coefficients;

synthesizing means for synthesizing a synthetic speech vector based on a driving vector and said quantized LPC coefficient;

pitch period vector selecting means for storing a plurality of pitch period vectors, and for selecting one pitch period vector from among said plurality of stored pitch period vectors;

noise waveform vector selecting means for storing a plurality of noise waveform vectors, and for selecting one noise waveform vector from among said plurality of stored noise waveform vectors;

gain adapting means for calculating a prediction gain for each noise waveform vector selected by said noise waveform vector selecting means by conducting linear prediction analysis based on a power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for the current frame operation, and the power of an output vector of a prediction gain multiplying means multiplied by a gain during the processing of gain multiplying means for a past frame operation;

prediction gain multiplying means for multiplying said prediction gain calculated by said gain adapting means by said noise waveform vector selected by said noise waveform vector selecting means;

gain multiplying means for storing a plurality of gains, and for respectively multiplying a gain selected from among said plurality of stored gains by said pitch period vector selected by said pitch period vector selecting means and an output vector of said prediction gain multiplying means, wherein said gain multiplying means comprises;

a first subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by half of the pitch period vector selected by said pitch period vector selecting means and half of an output vector of said prediction gain multiplying means;

a second subgain multiplying means for multiplying a gain selected from among a plurality of gains stored therein by the remaining half of the pitch period vector selected by said pitch vector selecting means and the remaining half of the output vector of said prediction gain multiplying means;

a first summing means for supplying to said adding means the sum of a pitch period vector multiplied by a gain by said first subgain multiplying means and a pitch period vector multiplied by a gain by said second subgain multiplying means, as a pitch period vector multiplied by a gain by said gain multiplying means; and

a second summing means for supplying to said adding means the sum of an output vector of said prediction gain multiplying means multiplied by a gain by said first subgain multiplying means and an output vector of said prediction gain multiplying means multiplied by a gain by said second subgain multiplying means, as an output vector of said prediction gain multiplying means multiplied by a gain by said gain multiplying means;

adding means for adding two multiplication results obtained by said gain multiplying means, and supplying the sum to said synthesizing means as said driving vector;

distortion data calculating means for calculating distortion data by subtracting said synthetic speech vector outputted by said synthesizing means from said speech input vector outputted by said amplitude limiting means;

perceptual weighting means for weighting said distortion data obtained by of said distortion data calculating means;

distortion power calculating means for calculating the distortion power of said distortion data with regard to each distortion data weighted by said perceptual weighting means;

control means for selecting a vector to minimize said distortion power when selecting a pitch period vector by said pitch period vector selecting means and when selecting a noise waveform vector by said noise waveform vector selecting means, and selecting a gain by said gain multiplying means; and

code output means for encoding data selected by said control means into a bit series, adding as necessary error correctional coding, and then transmitting said encoded bit series;

wherein said LSP parameter quantized by said vector quantizing means is expressed by a weighted mean vector of a plurality of vectors from the current frame operation and previous frame operations.