CN1244903C - Quick algorithm for searching weighted quantized vector of line spectrum in use for encoding voice - Google Patents

Quick algorithm for searching weighted quantized vector of line spectrum in use for encoding voice Download PDF

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CN1244903C
CN1244903C CNB2003101032035A CN200310103203A CN1244903C CN 1244903 C CN1244903 C CN 1244903C CN B2003101032035 A CNB2003101032035 A CN B2003101032035A CN 200310103203 A CN200310103203 A CN 200310103203A CN 1244903 C CN1244903 C CN 1244903C
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王波涛
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BEIJING SHOUXIN Co Ltd
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Abstract

The present invention relates to a line spectrum pair LSP weighting quantization vector fast search algorithm for voice encoding, which is a convenient and practical fast search algorithm for the problem of searching an LSP optimal quantization value. The fast search algorithm is characterized in that a code word vector which has a smallest distance away from a vector to be quantized is searched in a distance codebook and position indexes thereof according to a minimum distance criterion so as to obtain a preliminary search result; within a definite range of the preliminary search result, a search is executed according to a weighting minimum distance criterion to obtain a final search result, namely an optimal quantization vector. The initialization operation of the fast search algorithm comprises the step that the distances between each code word vector in each codebook of line spectrum pair parameter vectors and a grid origin are calculated, and the distances are prioritized to built the distance codebook and the position indexes thereof. The method of the present invention can reduce the complexity of a reduce algorithm and greatly raise efficiency; tone quality after optimization is basically unchanged, and thus, the realization cost and volume of a hardware system are reduced.

Description

The line spectrum pair weight quantization vector method for fast searching that is used for voice coding
Technical field
The present invention relates to a kind of line spectrum pair weight quantization vector method for fast searching that is used for voice coding, belong to the encoding and decoding speech technical field in the telephone communication.
Background technology
In mobile communication, audio coder ﹠ decoder (codec) is called as vocoder, generally adopts digital signal processor (DSP, digital signal processor) to realize.Owing in mobile communication system,, improve the execution efficient of speech coding algorithm to the demand of vocoder big (such as base station system), thus reduce system cost and volume particularly important.
The TIA/EIA/IS-127 standard is the voice coding standard that 3-G (Generation Three mobile communication system) CDMA2000 1X system adopts.The enhancing variable rate voice codec (EVRC, Enhanced VariableRate Codec) that it adopts has variable bit rate and the high characteristics of speech quality.The speech frame time span that its adopts is 20ms, adopts the output of encoding of three kinds of different speed respectively according to the noise situations difference of every frame: full rate, 1/2 speed and 1/8 speed.This enhancing variable rate voice codec is to be made of filtering, noise remove, model parameter estimation, code rate judgement, parameter coding (having comprised line spectrum pair weight vectors quantization modules) and six modules of decoding.The complexity of EVRC algorithm is about 30MIPS (million instructionper second), i.e. 3,000 ten thousand instructions of per second, more complicated.The EVRC algorithm at first carries out high-pass filtering to the speech frame of input, removes direct current and crosses low-frequency signal.Need remove noise to the speech frame after the high-pass filtering, improve quality of speech signal.Again the voice signal of removing noise is calculated 10 linear predictor coefficients (LPC, Linear predictive coefficient), and this LPC coefficient is converted to 10 line spectrum pairs (LSP, line spectrum pairs) parameter.Then the LSP parameter is weighted vector quantization, earlier 10 LSP parameters is divided into several groups, every group quantizes with a code book, and each code book contains the code word vector (each code word vector is made up of several components) of some.The number of 10 LSP parameter groupings is determined have three kinds of code rates available: full rate, 1/2 speed, 1/8 speed by code rate.When full rate, the LSP parameter quantification is divided into 4 groups and adopts 4 code books (each code book has 64,64,512,128 code word vectors respectively); When 1/2 speed, the LSP parameter quantification is divided into 3 groups and adopts 3 code books (each code book has 128,128,256 code word vectors respectively); When 1/8 speed, the LSP parameter quantification is divided into 2 groups and adopts 2 code books (each code book has 16,16 code word vectors respectively).When the LSP parameter is weighted vector quantization, 10 LSP parameters are divided into several groups, every group quantizes with a code book, and each code book contains the code word vector of some.Search for each code book and can obtain a quantized value, it is the code word vector, calculate the error of this quantized value and LSP parameter again according to Weighted distance square, select the quantized value of the quantized value of error minimum wherein or Weighted distance minimum, and the code book index of this quantized value correspondence is preserved as the LSP parameter.
When search optimal quantization value, what use at present is full-search algorithm, and it is all searched for each code word vector of each code book, therefore, in order to obtain the optimal quantization value, the code word vector number that the LSP parameter need be searched under full rate is 64+64+512+128=768, and efficiency ratio is lower.Under other speed, situation is also similar, but the search of LSP parameter weighting vector quantization is the most time-consuming under the full rate.
Because LSP parameter weighting vector quantization module is to adopt the algorithm of full search in whole EVRC algorithm, it is many to expend time in.And, in the process of search optimal quantization value, must determine weighted value as the case may be, therefore, how to optimize this algorithm, so that improve its efficient, become the problem that the insider pays close attention to.
Summary of the invention
The purpose of this invention is to provide a kind of line spectrum pair weight quantization vector method for fast searching that is used for voice coding, this method is a kind of easy, practical method for fast searching that proposes at LSP optimal quantization value search problem, can reduce the complexity of EVRC algorithm, under worst case, when full rate, can make in theory to reduce to original 14.6% search time, raise the efficiency greatly; And the tonequality after optimizing is constant substantially, meets corresponding TIA/EIA/IS-718 testing standard, thereby reduces implement of hardware system cost and volume.
The object of the present invention is achieved like this: a kind of line spectrum pair weight quantization vector method for fast searching that is used for voice coding, it is characterized in that: this method comprises the following steps:
(1) calculating line spectral, makes up apart from code book and location index thereof according to sorting apart from size of each code word vector in each code book and true origin each code word vector in each code book of parameter vector and the distance of true origin; Described distance is meant the root sum square value that square adds up of each component difference in the line spectrum pair LSP code word vector of any two same dimension or the line spectrum pair LSP parameter vector to be quantified;
(2) in distance code book and location index thereof, search for earlier and the code word vector of vector distance minimum to be quantified according to minimum distance criterion, obtain a preliminary Search Results, again in the certain limit of this preliminary Search Results, search for the weighted minimum distance criterion, obtain final Search Results, i.e. the optimal quantization vector; Described weighted minimum distance be in the line spectrum pair LSP code word vector of any two same dimension or the line spectrum pair LSP parameter vector to be quantified each component difference square with the root sum square value that adds up of corresponding weighted value product in minimum value.
Described step (2) further comprises following two operation stepss:
(21) calculate the line spectrum pair LSP parameter vector of voice coding to be quantified and the distance of true origin, and described with this range search apart from code book, obtain minimum code word vector Y j, the code word vector Y that this is minimum jTo the distance of true origin and LSP parameter vector to be quantified to true origin apart from the difference minimum between the two; Described search is to adopt dichotomy;
(22) search for the pairing code word vector of sequence number in the following location index according to the weighted minimum distance criterion, obtain the optimal codes vector; Sequence number in the described following location index all is in described location index, with the code word vector Y of described minimum jSequence number in this location index is the center, all is not more than a sequence number of setting numerical value r with the difference of this center sequence number.
Described employing dichotomizing search is according to a minute principle apart from code book, vector distance to be quantified and the described pairing numerical value in centre position apart from code book is carried out recycle ratio, until obtaining minimum code word vector Y jOperation.
Described method comprises following concrete calculating operation step:
Suppose that X is a vector to be quantified, i.e. one group of parameter of the line spectrum pair LSP of voice coding; X kBe k the component of X, i.e. the single parameter of LSP; Y iBe i code word vector in the codebook vectors of LSP, Y IkBe Y iK component, k=1,2 ..., n, n are the numbers of vector component, i.e. the number of parameters of inclusion in one of LSP group of parameter; D (X) is the distance of X and true origin, and d (i) is Y iDistance with true origin;
(A) each code word vector Y in each code book of calculating LSP parameter vector iEach component Y IkWith true origin apart from d (i), its computing formula is: d ( i ) = Σ k = 1 n Y ik 2 ;
(B) according to aforementioned calculation obtain apart from d (i), according to from small to large or order from big to small the code word vector in each code book is sorted, foundation is corresponding apart from code book NewCB-1 and location index NewCB-2 thereof with this code book, wherein stores each code word vector Y apart from code book iWith true origin apart from d (i), the index code book is stored apart from each code word vector Y in the code book iLocation index or sequence number in original code book;
(C) calculate LSP parameter vector X to be quantified and true origin apart from d (X), its computing formula is:
d ( X ) = Σ k = 1 n X k 2 ;
(D) with dichotomy described table look-up on apart from code book NewCB-1 relatively to search for d (X) numerical value differ minimum code word vector Y j,, vector distance to be quantified and the described pairing numerical value in centre position apart from code book are carried out recycle ratio, until obtaining minimum code word vector Y promptly according to a minute criterion j
(E) search for the pairing code word vector of sequence number in the following location index according to the weighted minimum distance criterion, obtain the optimal codes vector; Sequence number in the described following location index all is in described location index, with the code word vector Y of described minimum jSequence number in this location index is the center, all is not more than a sequence number of setting numerical value r with the difference of this center sequence number.
The value of a setting numerical value r is as follows in the described step (E):
When full rate, r gets 5 for first code book, gets 5 for second code book r, gets 20 for the 3rd code book r, gets 10 for the 4th code book r;
When 1/2 speed, r gets 8 for first code book, gets 8 for second code book r, gets 8 for the 3rd code book r;
When 1/8 speed, r gets 5 for first code book, gets 5 for second code book r.
A value of setting numerical value r can select to determine its numerical values recited as required in the described step (E); It selects to adjust principle: the value of r is big more, and then search efficiency reduces gradually, and the tonequality loss reduces gradually; The value of r is more little, and then search efficiency improves gradually, and the tonequality loss increases gradually.
The present invention be directed to a kind of easy and practical method for fast searching that LSP optimal quantization value search problem proposes, has following advantage: at first be to have improved search efficiency, after adopting method for fast searching of the present invention, under worst case, the search number that the LSP parameters optimal weight vectors of every frame voice quantizes when full rate reduces to 112 by original 768, search number after the optimization approximately is original 14.6%, raises the efficiency greatly.If method of the present invention and former algorithm all use C code floating-point to realize under the full rate situation, then the former searching times can be the latter searching times 12.3%.When full rate, method of the present invention makes complexity reduce about 1.17MIPS.In addition, the call voice tonequality after the optimization of employing the inventive method remains unchanged substantially with the tonequality of original algorithm, meets the TIA/EIA/IS-718 testing standard whether the EVRC algorithm that is specifically designed to each producer's research and development of test meets related request.Practice shows that the inventive method is an easy and practical method, will bring the comparison remarkable economic efficiency.
Description of drawings
Fig. 1 is the process flow diagram of the initialization operation step of the inventive method.
Fig. 2 is the process flow diagram of the operation steps of the inventive method.
Embodiment
The present invention is a kind of line spectrum pair weight quantization vector method for fast searching that is used for voice coding, this method is search in distance code book and location index thereof according to minimum distance criterion earlier and the code word vector of vector distance minimum to be quantified, obtain a preliminary Search Results, again in the certain limit of this preliminary Search Results, search for the weighted minimum distance criterion, obtain final Search Results, i.e. the optimal quantization vector.
Referring to Fig. 1, introduce the initialization operation step of the inventive method:
11, each code word vector in each code book of input LSP parameter vector;
12, calculate the distance of each code word vector and true origin;
13,, make up apart from code book NewCB-1 according to the sorting of each code word vector and true origin apart from size;
14, make up the location index NewCB-2 of each code word vector in distance code book NewCB-1.
Referring to Fig. 2, introduce the concrete operations step of the inventive method:
21, input LSP parameter vector X to be quantified;
22, calculate LSP parameter vector X to be quantified and true origin apart from d (X);
23, with step 22 calculate apart from d (X) detection range code book NewCB-1, obtain with apart from the distance of d (X) difference minimum and at this apart from the sequence number among the code book NewCB-1;
24, find the manipulative indexing of this sequence number in location index NewCB-2 according to the sequence number in the step 23 apart among the code book NewCB-1;
25, find this corresponding code word vector in original code book with the index in the step 24, be the minimum code word vector Y j
26, according to the minimum weight distance criterion with the minimum code word vector Y jBe search optimal codes vector, i.e. optimum weighting quantization vector in the certain limit at center;
27, output optimum weighting quantization vector and in original code book corresponding index.
The concrete calculation procedure of following brief description method for fast searching of the present invention:
Suppose that X is a vector to be quantified, i.e. one of LSP group of parameter, X hBe k the component of X, i.e. the single parameter of LSP, Y iBe i code word vector in the codebook vectors of LSP, Y IkBe Y iK component, k=1,2 ..., n, n are the numbers of vector component, i.e. the number of parameters that comprises in one of LSP group of parameter, d (X) is the distance of X and true origin (being zero point), d (i) is Y iDistance with true origin (being zero point).
(1) at first calculates each code word vector Y in each code book of LSP iEach component Y IkWith true origin apart from d (i), computing formula is as follows: d ( i ) = Σ k = 1 n Y ik 2 ;
(2) according to aforementioned calculation obtain apart from d (i), according to from small to large or order from big to small the code word vector in each code book is sorted, set up one with this code book corresponding apart from code book NewCB-1 and location index NewCB-2 thereof, wherein store each code word vector Y apart from code book NewCB-1 iWith true origin apart from d (i), location index NewCB-2 stores apart from each code word vector Y in the code book iLocation index or sequence number in original code book;
(3) calculate LSP parameter vector X to be quantified and true origin apart from d (X), computing formula is as follows:
d ( X ) = Σ k = 1 n X k 2 ;
(4) with dichotomy described table look-up on apart from code book NewCB-1 relatively to search for d (X) numerical value differ minimum code word vector Y j,, vector distance to be quantified and the described pairing numerical value in centre position apart from code book are carried out recycle ratio, until obtaining minimum code word vector Y promptly according to a minute criterion j
(5) search for the pairing code word vector of sequence number in the following location index according to the weighted minimum distance criterion, obtain the optimal codes vector; Sequence number in the described following location index all is in described location index, with the code word vector Y of described minimum jSequence number in this location index is the center, all is not more than a sequence number of setting numerical value r with the difference of this center sequence number.
Wherein the value of a setting numerical value r is as follows:
When A, full rate, r gets 5 for first code book, gets 5 for second code book r, gets 20 for the 3rd code book r, gets 10 for the 4th code book r;
When B, 1/2 speed, r gets 8 for first code book, gets 8 for second code book r, gets 8 for the 3rd code book r;
When C, 1/8 speed, r gets 5 for first code book, gets 5 for second code book r;
The value of D, r also can select to adjust it as required, and the principle of its adjustment is: the value of r is big more, and then search efficiency reduces gradually, and the tonequality loss reduces gradually, and the value of r is more little, and then search efficiency improves gradually, and the tonequality loss increases gradually.
Method of the present invention can be used for the EVRC vocoder that 3-G (Generation Three mobile communication system) CDMA20001X system adopts, and also can be used for the speech coding algorithm that other is suitable for this fast search algorithm.
The present invention implements test and test on the EVRC optimization vocoder of realizing with single-chip digital signal processor DSP (the chip model is TMS320C6211, dominant frequency 150MHZ) that comprises fast algorithm module of the present invention.Test result shows that the codec after the optimization of employing the inventive method is than reducing about 11% approximately before optimizing total processing time.From the data that can retrieve, the EVRC algorithm is gone up realization at digital signal processor DSP (the chip model is TMS320C6211, dominant frequency 150MHZ) and has been reached the level that can handle 5 road speeches in every frame time.And after the present invention adopted optimized Algorithm based on LSP parameter weighting vector quantization fast search algorithm, when EVRC voice code optimization algorithm is realized on single-chip digital signal processor TMS320C6211, reach the level that to handle 8 road speeches in every frame time, reached further the good effect of reduce cost (8 tunnel compare cost with 5 tunnel can reduce about 50%) and reduction system volume.
In addition, also embodiment has been carried out acoustical testing, its result is as follows:
1, (it is 4660ms that this segment data continues duration to the raw tone of test usefulness for the subsidiary segment standard test data sample of EVRC algorithm, adopt the 8000HZ sampling rate, through mu-law companding, content is: The thinthimble to my mad, she said she is dolman.), this raw tone is adopted the algorithm before and after optimizing carry out encoding and decoding respectively.Decoded result is confirmed through many people auditory experiment, not significantly difference of decoding tonequality before and after optimizing, distortion is less.
2, adopt ITU-T P.862 standard two kinds of decoded results (comparing with raw tone) of above-mentioned raw tone carried out acoustical testing find, constant substantially (differ is 0.001 for the tonequality of method for fast searching of the present invention and the voice quality of original algorithm under the situation of encoding and decoding, very little, can ignore).Under the situation of secondary coding-decoding (cascade), the voice quality of the inventive method is better than the voice quality of original algorithm.
3, method for fast searching of the present invention is checked with other subsidiary standard testing data sample of EVRC algorithm, and effect is also relatively good, has passed through the test of TIA/EIA/IS-718 testing standard.

Claims (6)

1, a kind of line spectrum pair weight quantization vector method for fast searching that is used for voice coding, it is characterized in that: this method comprises the following steps:
(1) calculating line spectral, makes up apart from code book and location index thereof according to sorting apart from size of each code word vector in each code book and true origin each code word vector in each code book of parameter vector and the distance of true origin; Described distance is meant the root sum square value that square adds up of the line spectrum pair LSP code word vector of any two same dimension or each component difference in the line spectrum pair LSP parameter vector to be quantified;
(2) in distance code book and location index thereof, search for earlier and the code word vector of vector distance minimum to be quantified according to minimum distance criterion, obtain a preliminary Search Results, again in the certain limit of this preliminary Search Results, search for the weighted minimum distance criterion, obtain final Search Results, i.e. the optimal quantization vector; Described weighted minimum distance be in the line spectrum pair LSP code word vector of any two same dimension or the line spectrum pair LSP parameter vector to be quantified each component difference square with the root sum square value that adds up of corresponding weighted value product in minimum value.
2, method for fast searching according to claim 1 is characterized in that: described step (2) further comprises following two operation stepss:
(21) calculate the line spectrum pair LSP parameter vector of voice coding to be quantified and the distance of true origin, and described with this range search apart from code book, obtain minimum code word vector Y i, the code word vector Y that this is minimum iTo the distance of true origin and LSP parameter vector to be quantified to true origin apart from the difference minimum between the two; Described search is to adopt dichotomy;
(22) search for the pairing code word vector of sequence number in the following location index according to the weighted minimum distance criterion, obtain the optimal codes vector; Sequence number in the described following location index all is in described location index, with the code word vector Y of described minimum iSequence number in this location index is the center, all is not more than a sequence number of setting numerical value r with the difference of this center sequence number.
3, method for fast searching according to claim 2, it is characterized in that: adopting dichotomizing search is according to a minute principle apart from code book, vector distance to be quantified and the described pairing numerical value in centre position apart from code book are carried out recycle ratio, until obtaining minimum code word vector Y iOperation.
4, method for fast searching according to claim 1 is characterized in that: described method comprises following concrete calculating operation step:
Suppose that X is a vector to be quantified, i.e. one group of parameter of the line spectrum pair LSP of voice coding; X kBe k the component of X, i.e. the single parameter of LSP; Y iBe i code word vector in the codebook vectors of LSP, Y IkBe Y iK component, k=1,2 ..., n, n are the numbers of vector component, i.e. the number of parameters that comprises in one of LSP group of parameter; D (X) is the distance of X and true origin, and d (i) is Y iDistance with true origin;
(A) each code word vector Y in each code book of calculating LSP parameter vector iEach component Y IkWith true origin apart from d (i), its computing formula is: d ( i ) = ∑ k = 1 n Y ik 2 ;
(B) according to aforementioned calculation obtain apart from d (i), according to from small to large or order from big to small the code word vector in each code book is sorted, foundation is corresponding apart from code book NewCB-1 and location index NewCB-2 thereof with this code book, wherein stores each code word vector Y apart from code book iWith true origin apart from d (i), the index code book is stored apart from each code word vector Y in the code book iLocation index or sequence number in original code book;
(C) calculate LSP parameter vector X to be quantified and true origin apart from d (X), its computing formula is:
d ( X ) = ∑ k = 1 n X k 2 ;
(D) with dichotomy described table look-up on apart from code book NewCB-1 relatively to search for d (X) numerical value differ minimum code word vector Y j,, vector distance to be quantified and the described pairing numerical value in centre position apart from code book are carried out recycle ratio, until obtaining minimum code word vector Y promptly according to a minute criterion j
(E) search for the pairing code word vector of sequence number in the following location index according to the weighted minimum distance criterion, obtain the optimal codes vector; Sequence number in the described following location index all is in described location index, with the code word vector Y of described minimum jSequence number in this location index is the center, all is not more than a sequence number of setting numerical value r with the difference of this center sequence number.
5, method for fast searching according to claim 4 is characterized in that: the value of a setting numerical value r is as follows in the described step (E):
When full rate, r gets 5 for first code book, gets 5 for second code book r, gets 20 for the 3rd code book r, gets 10 for the 4th code book r;
When 1/2 speed, r gets 8 for first code book, gets 8 for second code book r, gets 8 for the 3rd code book r;
When 1/8 speed, r gets 5 for first code book, gets 5 for second code book r.
6, method for fast searching according to claim 4 is characterized in that: a value of setting numerical value r can select to determine its numerical values recited as required in the described step (E).
CNB2003101032035A 2003-10-30 2003-10-30 Quick algorithm for searching weighted quantized vector of line spectrum in use for encoding voice Expired - Fee Related CN1244903C (en)

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