Claims
- 1. A speech encoding method by which an input speech signal vector is encoded using an index assigned to a code vector that, among predetermined code vectors, is closest in distance to said input speech signal vector, comprising the steps of:
- a) storing a plurality of differential code vectors having a tree structure;
- b) multiplying each of said differential code vectors by a matrix of a linear predictive filter;
- c) evaluating a power amplification ratio of each differential code vector multiplied by said matrix;
- d) reordering the differential code vectors, each multiplied by said matrix, in decreasing order of said evaluated power amplification ratio;
- e) selecting from among said reordered vectors a prescribed number of vectors in decreasing order of said evaluated power amplification ratio, the largest ratio first the number of the selected vectors being smaller than a number of the reordered vectors;
- f) evaluating the distance between said input speech signal vector and each of linear-predictive-filtered code vectors that are to be formed by sequentially adding and subtracting said selected vectors through the tree structure; and
- g) determining the code vector for which said evaluated distance is the smallest.
- 2. A method according to claim 1, wherein each of said differential code vectors is normalized.
- 3. A method according to claim 1, wherein
- said step f) includes: calculating a cross-correlation R.sub.XC between said input speech signal vector and each of said linear-predictive- filtered code vectors by calculating the cross-correlation between said input speech signal vector and each of said selected vectors and by sequentially performing additions and subtractions through the tree structure; calculating an autocorrelation R.sub.CC of each of said linear-predictive- filtered code vectors by calculating the autocorrelation of each of said selected vectors and the cross-correlation of every possible combination of different vectors and by sequentially performing additions and subtractions through the tree structure; and calculating the quotient of a square of the cross-correlation R.sub.XC by the autocorrelation R.sub.CC, R.sub.XC.sup.2 /R.sub.CC, for each of said code vectors, and
- said step g) includes determining the code vector that maximizes the value of R.sub.XC.sup.2 /R.sub.CC, as the code vector that is closest in distance to said input speech signal vector.
- 4. A speech encoding apparatus by which an input speech signal vector is encoded using an index assigned to a code vector that, among predetermined code vectors, is closest in distance to said input speech signal vector, comprising:
- means for storing a plurality of differential code vectors having a tree structure;
- means for multiplying each of said differential code vectors by a matrix of a linear predictive filter;
- means for evaluating a power amplification ratio of each differential code vector multiplied by said matrix;
- means for reordering the differential code vectors, each multiplied by said matrix, in decreasing order of said evaluated power amplification ratio;
- means for selecting from among said reordered vectors a prescribed number of vectors in decreasing order of said evaluated power amplification ratio, the largest ratio first, the number of the selected vectors being smaller than a number of the reordered vectors;
- means for evaluating the distance between said input speech signal vector and each of linear-predictive- filtered code vectors that are to be formed by sequentially adding and subtracting said selected vectors through the tree structure; and
- means for determining the code vector for which said evaluated distance is the smallest.
- 5. An apparatus according to claim 4, wherein each of said differential code vectors is normalized.
- 6. An apparatus according to claim 4, wherein
- said distance evaluation means includes: means for calculating a cross-correlation R.sub.XC between said input speech signal vector and each of said linear-predictive- filtered code vectors by calculating the cross-correlation between said input speech signal vector and each of said selected vectors and by sequentially performing additions and subtractions through the tree structure; means for calculating an autocorrelation R.sub.CC of each of said linear-predictive- filtered code vectors by calculating the autocorrelation of each of said selected vectors and the cross-correlation of every possible combination of different vectors and by sequentially performing additions and subtractions through the tree structure; and means for calculating the quotient of a square of the cross-correlation R.sub.XC by the autocorrelation R.sub.CC, R.sub.XC.sup.2 /R.sub.CC, for each of said code vectors, and
- said code vector determining means includes means for determining the code vector that maximizes the value of R.sub.XC.sup.2 /R.sub.CC, as the code vector that is closest in distance to said input speech signal vector.
- 7. A variable-length speech encoding method by which an input speech signal vector is variable-length encoded using a variable-length code assigned to a code vector that, among predetermined code vectors, is closest in distance to said input speech signal vector, comprising the steps of:
- a) storing a plurality of differential code vectors having a tree structure;
- b) evaluating a distance between said input speech signal vector and each of code vectors that are to be formed by sequentially performing additions and subtractions with regard to differential code vectors the number of which corresponds to a variable code length, working from a root of the tree structure;
- c) determining a code vector for which said evaluated distance is the smallest; and
- d) determining a code, of the variable code length, to be assigned to said determined code vector.
- 8. A method according to claim 7, further comprising the step of multiplying each of said differential code vectors by a matrix in a linear predictive filter, wherein in said step b) the distance is evaluated between said input speech signal vector and each of linear-predictive- filtered code vectors that are to be formed by sequentially adding and subtracting the differential code vectors, each multiplied by said matrix, through the tree structure.
- 9. A method according to claim 8, wherein
- said step b) includes: calculating a cross-correlation R.sub.XC between said input speech signal vector and each of said linear-predictive- filtered code vectors by calculating the cross-correlation between said input speech signal vector and each of said differential code vectors multiplied by said matrix and by sequentially performing additions and subtractions through the tree structure; calculating an autocorrelation R.sub.CC of each of said linear-predictive- filtered code vectors by calculating the autocorrelation of each of said differential code vectors multiplied by said matrix and the cross-correlation of every possible combination of different vectors and by sequentially performing additions and subtractions through the tree structure; and calculating the quotient of a square of the cross-correlation R.sub.XC by the autocorrelation R.sub.CC, R.sub.XC.sup.2 /R.sub.CC, for each of said code vectors, and
- said step c) includes determining the code vector that maximizes the value of R.sub.XC.sup.2 /R.sub.CC, as the code vector that is closest in distance to said input speech signal vector.
- 10. A method according to claim 9, further comprising the steps of:
- evaluating a power amplification ratio of each differential code vector multiplied by said matrix; and
- reordering the differential code vectors, each multiplied by said matrix, in decreasing order of said evaluated power amplification ratio;
- wherein in said step b) the additions and subtractions are performed in the thus reordered sequence through the tree structure.
- 11. A method according to claim 10, further comprising the step of selecting from among said reordered vectors a prescribed number of vectors in decreasing order of said evaluated power amplification ratio, the largest ratio first, wherein in said step b) the additions and subtractions are performed on said selected vectors through the tree structure.
- 12. A method according to claim 7, wherein a code is assigned to said code vector in such a manner as to be associated with a code vector corresponding to the parent thereof in the tree structure when one bit is dropped from any of said code vectors.
- 13. A variable-length speech encoding apparatus by which an input speech signal vector is variable-length encoded using a variable-length code assigned to a code vector that, among predetermined code vectors, is closest in distance to said input speech signal vector, comprising:
- means for storing a plurality of differential code vectors having a tree structure;
- means for evaluating a distance between said input speech signal vector and each of the code vectors that are to be formed by sequentially performing additions and subtractions with regard to differential code vectors the number of which corresponds to a variable code length, working from a root of the tree structure;
- means for determining a code vector for which said evaluated distance is the smallest; and
- means for determining a code, of the variable code length, to be assigned to said determined code vector.
- 14. An apparatus according to claim 13, further comprising means for multiplying each of said differential code vectors by a matrix in a linear predictive filter, wherein said distance evaluating means evaluates the distance between said input speech signal vector and each of linear-predictive- filtered code vectors that are to be formed by sequentially adding and subtracting the differential code vectors, each multiplied by said matrix, through the tree structure.
- 15. An apparatus according to claim 14, wherein
- said distance evaluating means includes: means for calculating a cross-correlation R.sub.XC between said input speech signal vector and each of said linear-predictive- filtered code vectors by calculating the cross-correlation between said input speech signal vector and each of said differential code vectors multiplied by said matrix and by sequentially performing additions and subtractions through the tree structure; means for calculating an autocorrelation R.sub.CC of each of said linear-predictive- filtered code vectors by calculating the autocorrelation of each of said differential code vectors multiplied by said matrix and the cross-correlation of every possible combination of different vectors and by sequentially performing additions and subtractions through the tree structure; and means for calculating the quotient of a square of the cross-correlation R.sub.XC by the autocorrelation R.sub.CC, R.sub.XC.sup.2 /R.sub.CC, for each of said code vectors, and
- said code vector determining means includes means for determining the code vector that maximizes the value of R.sub.XC.sup.2 /R.sub.CC, as the code vector that is closest in distance to said input speech signal vector.
- 16. An apparatus according to claim 15, further comprising:
- means for evaluating a power amplification ratio of each differential code vector multiplied by said matrix; and
- means for reordering the differential code vectors, each multiplied by said matrix, in decreasing order of said evaluated power amplification ratio;
- wherein said distance evaluating means performs the additions and subtractions in the thus reordered sequence through the tree structure.
- 17. An apparatus according to claim 15, further comprising means for selecting from among said reordered vectors a prescribed number of vectors in decreasing order of said evaluated power amplification ratio, the largest ratio first, wherein said distance evaluating means performs the additions and subtractions on said selected vectors through the tree structure.
- 18. An apparatus according to claim 13, wherein a code is assigned to said code vector in such a manner as to be associated with a code vector corresponding to a parent thereof in the tree structure when one bit is dropped from any of said code vectors.
Priority Claims (1)
Number |
Date |
Country |
Kind |
4-246491 |
Sep 1992 |
JPX |
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Parent Case Info
This application is a continuation of application Ser. No. 08/244,068, filed as PCT/JP93/01323, Sep. 16, 1993 published as WO94/07239, Mar. 31, 1994 now abandoned.
US Referenced Citations (2)
Number |
Name |
Date |
Kind |
5323486 |
Taniguchi et al. |
Jun 1994 |
|
5359696 |
Gerson et al. |
Oct 1994 |
|
Foreign Referenced Citations (10)
Number |
Date |
Country |
59-012499 |
Jan 1984 |
JPX |
61-184928 |
Aug 1986 |
JPX |
2-055400 |
Feb 1990 |
JPX |
4-039679 |
Jun 1992 |
JPX |
4-352200 |
Dec 1992 |
JPX |
4-344699 |
Dec 1992 |
JPX |
5-088698 |
Apr 1993 |
JPX |
5-158500 |
Jun 1993 |
JPX |
5-210399 |
Aug 1993 |
JPX |
5-232996 |
Sep 1993 |
JPX |
Continuations (1)
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Number |
Date |
Country |
Parent |
244068 |
May 1994 |
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