CA2103785C - Speech coder and method having spectral interpolation and fast codebook search - Google Patents
Speech coder and method having spectral interpolation and fast codebook searchInfo
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- CA2103785C CA2103785C CA002103785A CA2103785A CA2103785C CA 2103785 C CA2103785 C CA 2103785C CA 002103785 A CA002103785 A CA 002103785A CA 2103785 A CA2103785 A CA 2103785A CA 2103785 C CA2103785 C CA 2103785C
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Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
- G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
- G10L19/083—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being an excitation gain
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
- G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
- G10L19/12—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L2019/0001—Codebooks
- G10L2019/0012—Smoothing of parameters of the decoder interpolation
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L2019/0001—Codebooks
- G10L2019/0013—Codebook search algorithms
- G10L2019/0014—Selection criteria for distances
Abstract
A novel spectral interpolation (500, 600) and efficient excitation codebook search method (700) developed for a Code-Ex-cited Linear Predictive (CELP) speech coder (100) is set forth. The interpolation is performed on an impulse response of the spec-tral synthesis filter. As the result of using this new set of interpolation parameters, the computations associated with an excitation codebook search in a CELP coder are considerably reduced. Furthermore, a coder utilizing this new interpolation approach pro-vides noticeable improvement in speech quality coded at low bit-rates.
Description
WO 92/16930 1 PCT/I~S92/01299 ~1~37g~ -SPEECH CODER Ai~D METHOD HAVING SPECTRAL
INTERPOLATION AND FAST CO~E~OOK SEARCH
5 Field of the Invention The present invention relates ~enerally to the hi~h quality and low bit rate codin~ of communication signals and, more particularly, to more efficient coding of speech sisnals in the linear pf~i.,ti~, codins le~l", ,!es and in speech coders.
R~round of the Invention Code-Excited Linear ~Iv~ n (CELP) is a widely used low bit-rate speech coding It~ . Typically, a speech coder utilizing CELP achieves efficient coding of speech 15 si~nals by l , lc ,9 long-term and short term linear p,.~ ia~s to remove redundancy of a speech . ~f~"", and by utilizins a vector qJdnli.dlion technique to reduca a bit-rate required for r~p,~.3i,nli"~ p,. 'i~'ion residual signals that are also referred to the e,~cildlion signal. CELP-type speech 20 coders typically include a codebooi~ conldi, ,~ a set of excitation cod~ h~rs, a gain adjuster, a long-term synthesis filter, and a short-term ay~ si:, filter. Indices of selected excitation codeYectors, quantized gains and parameters of the ~ong-term and short-term :,~nl~)~sis fiiters are l,dns"~ d or 25 stored for reproducin~ a digital coded signal. The pa~d~ lul:~
of the short-term ~y"ll,esis filter, typically obtained through linear p~ codinaJ (LPC) analysis of an input si~nal, conveys signal spectral information and are typically updated and l,dn~",ill~d once every time trame due to the bit-rate 30 con~l,di"l. However, updating the LPC pd,d",el~,~ in such piecewise fashion often results in discontinuity of the short-term ~y.,ll,~sis filter at frame boundaries. Linear i"l~r~,ailation o~ the LPC synthesis filter pd~dlll~ r:~ between two adjacent speech frames has been suggested previously to 21~378rj smooth spectral transitions without i"~.~asi"g the tlallalll;isi~n bit-rate. However, conventional app,od,l,G~ of such inl6,~Gldlion lead to a significant increase in encoding co""' ty. There is a need for d~J~lo~. ,9 more efficient 5 interpolation method that not only achieves the goal of sl"~ull, ,9 the filter lldnsilions, but also requires low encoding C~ AjIY.
Summ~y of the Invention 1 û A device, system, and method are provided for su~:.ld,)tially reconstructin~ a signal, the signal being p^a, lilioned into successive time intervals, each time interval si~nal partition having a repr~ser,ldli~ input reference signal with a set of vectors, and having at least a first repres~nldlh/~ electrical signal for each lep,~sel~ldli~e input ce signal of each time interval signal partition. The method, system, and device utilize at least a ç~d~boGL unit having at least a codsbooh memory, a gain adjuster where desired, a sy"tl,es;s unlt having at least a first synthesis fllter, a cu",~i.,er, and a perceptual .~ g unit having at least a first perceptual ~ y filter, for utilizing the electrical signals of the ,epr~senld~;,ra input reference signals to at least ~qenerate a related set of s~"l~,6:,iLt,d signal vectors for su~slant~ reconstructing the signal.
A sy"ll,es;~ unit utilizes the at least first ,epr~,s6nldlive electricai signal for each repl~senldlhl~ input r.Jf~r~nc~ signal for a selected time signal partition to obtain a set of url;.,l~",oldl~d parameters for the at least first sy"ll,esi~ filter. The at least first s~-,ll,esis unit, utilizing the at least first :,~"~I.esis filter, obtains the corresponding impulse response representation, and then i"~,yGlale~ the impulse responses of each selected adjacent time signal partition and of a current time signal partition i"""edidt~ly thereafter to provide a set of interpolated s~"ll,esis filters WO 92/16930 PCI'/1,~592/01299 ~ 3
INTERPOLATION AND FAST CO~E~OOK SEARCH
5 Field of the Invention The present invention relates ~enerally to the hi~h quality and low bit rate codin~ of communication signals and, more particularly, to more efficient coding of speech sisnals in the linear pf~i.,ti~, codins le~l", ,!es and in speech coders.
R~round of the Invention Code-Excited Linear ~Iv~ n (CELP) is a widely used low bit-rate speech coding It~ . Typically, a speech coder utilizing CELP achieves efficient coding of speech 15 si~nals by l , lc ,9 long-term and short term linear p,.~ ia~s to remove redundancy of a speech . ~f~"", and by utilizins a vector qJdnli.dlion technique to reduca a bit-rate required for r~p,~.3i,nli"~ p,. 'i~'ion residual signals that are also referred to the e,~cildlion signal. CELP-type speech 20 coders typically include a codebooi~ conldi, ,~ a set of excitation cod~ h~rs, a gain adjuster, a long-term synthesis filter, and a short-term ay~ si:, filter. Indices of selected excitation codeYectors, quantized gains and parameters of the ~ong-term and short-term :,~nl~)~sis fiiters are l,dns"~ d or 25 stored for reproducin~ a digital coded signal. The pa~d~ lul:~
of the short-term ~y"ll,esis filter, typically obtained through linear p~ codinaJ (LPC) analysis of an input si~nal, conveys signal spectral information and are typically updated and l,dn~",ill~d once every time trame due to the bit-rate 30 con~l,di"l. However, updating the LPC pd,d",el~,~ in such piecewise fashion often results in discontinuity of the short-term ~y.,ll,~sis filter at frame boundaries. Linear i"l~r~,ailation o~ the LPC synthesis filter pd~dlll~ r:~ between two adjacent speech frames has been suggested previously to 21~378rj smooth spectral transitions without i"~.~asi"g the tlallalll;isi~n bit-rate. However, conventional app,od,l,G~ of such inl6,~Gldlion lead to a significant increase in encoding co""' ty. There is a need for d~J~lo~. ,9 more efficient 5 interpolation method that not only achieves the goal of sl"~ull, ,9 the filter lldnsilions, but also requires low encoding C~ AjIY.
Summ~y of the Invention 1 û A device, system, and method are provided for su~:.ld,)tially reconstructin~ a signal, the signal being p^a, lilioned into successive time intervals, each time interval si~nal partition having a repr~ser,ldli~ input reference signal with a set of vectors, and having at least a first repres~nldlh/~ electrical signal for each lep,~sel~ldli~e input ce signal of each time interval signal partition. The method, system, and device utilize at least a ç~d~boGL unit having at least a codsbooh memory, a gain adjuster where desired, a sy"tl,es;s unlt having at least a first synthesis fllter, a cu",~i.,er, and a perceptual .~ g unit having at least a first perceptual ~ y filter, for utilizing the electrical signals of the ,epr~senld~;,ra input reference signals to at least ~qenerate a related set of s~"l~,6:,iLt,d signal vectors for su~slant~ reconstructing the signal.
A sy"ll,es;~ unit utilizes the at least first ,epr~,s6nldlive electricai signal for each repl~senldlhl~ input r.Jf~r~nc~ signal for a selected time signal partition to obtain a set of url;.,l~",oldl~d parameters for the at least first sy"ll,esi~ filter. The at least first s~-,ll,esis unit, utilizing the at least first :,~"~I.esis filter, obtains the corresponding impulse response representation, and then i"~,yGlale~ the impulse responses of each selected adjacent time signal partition and of a current time signal partition i"""edidt~ly thereafter to provide a set of interpolated s~"ll,esis filters WO 92/16930 PCI'/1,~592/01299 ~ 3
2~
for desired su~,a,Lilions. The intetpolated ~ lI,es;a filters provide a c~ pon"lg set of illlt7"olaldd perceptual filters for desired subpartitions such that smooth tldnsilions of the s~llllesi~ filter and the perceptual 5 ~ hlil,~ filter between each pair of adjacent partitions are obtained. The cod~book unit utilizes the set of input reference signal vectors, the related set of illlurl,~laled s~nl~lles;s filters and the related set of illlt,r,uGlàl~d perceptual filters for the current time signal partition to 10 select a corl~:."orl `illg set of optimal e~ildliùn cod~_lurs from the at least first ~,u~bo41~ memory.
Further, for each desired input reference signal vector:
(1) a particular ex.,ildlion codevector is provided from the at least first cod~bool~ memory of the codeboolc unit, the 15 codehool~ memory having a set of excitation codevectors stored therein lesponsi~ to the l~ple~s~rlldli~e input vectors; ~2) where desired, the gain adjuster, fes~,ons;~. to the particular excitation co~s~__tùr, multiplies that cod~lr~_~or by a selected e.~-,ildlion ~ain factor to substantially provide 20 cGrl~lalion with an ener~y of the lel,rds~nlalive electrical signal for each reprc,senlàlive input r.~r~nce signal vector;
for desired su~,a,Lilions. The intetpolated ~ lI,es;a filters provide a c~ pon"lg set of illlt7"olaldd perceptual filters for desired subpartitions such that smooth tldnsilions of the s~llllesi~ filter and the perceptual 5 ~ hlil,~ filter between each pair of adjacent partitions are obtained. The cod~book unit utilizes the set of input reference signal vectors, the related set of illlurl,~laled s~nl~lles;s filters and the related set of illlt,r,uGlàl~d perceptual filters for the current time signal partition to 10 select a corl~:."orl `illg set of optimal e~ildliùn cod~_lurs from the at least first ~,u~bo41~ memory.
Further, for each desired input reference signal vector:
(1) a particular ex.,ildlion codevector is provided from the at least first cod~bool~ memory of the codeboolc unit, the 15 codehool~ memory having a set of excitation codevectors stored therein lesponsi~ to the l~ple~s~rlldli~e input vectors; ~2) where desired, the gain adjuster, fes~,ons;~. to the particular excitation co~s~__tùr, multiplies that cod~lr~_~or by a selected e.~-,ildlion ~ain factor to substantially provide 20 cGrl~lalion with an ener~y of the lel,rds~nlalive electrical signal for each reprc,senlàlive input r.~r~nce signal vector;
(3) the cu,l~spon " l9 illl~",GlaLed :,~,llllesis filter"e~ or,sivu to the particular e,.cilalion cud~u_lur multiplied by the particular gain, produces the s~,lllle~iLed signal vector; (4) the 25 coll b ~er, lesponsiv~ to the synthesized signal vector and to the input ~t,funce signal vector, subtracts the s~"ll,esi~d signal vector from the input ~r~rt,nce signal vector related thereto to obtain a corresponding reconstruction error vector;
(5) an illlt~r~GIdl~d perceptual weighting unit, responsive to 30 the corlea~.oncli~g reconstruction error vector, determines a corresponding perceptually weighted squared error;
(6) a selector"t,~ol~si~e to the cGr,~spon~ ~g perceptually weighted squared error, stores an index of a codevector having the perceptually weighted squared error that it determines to WO 92/16930 PCI`/US9V01299 2103~8S 4 ~
be smaller than all other errors produced by other codevectors;
(7) the device, system and method repeat the steps (1),(2),(3),(4),(5),and (6) for every ex~ dtioi7 God~ ,tor in the ,od~boo~ memory and i.", ~e."ent these steps utilizing a fast 5 r,oclbboo~ search method, to de~-~ an optimal e~Gihlion God~"ro~,tor for the related input ~fn.~nce signal vector; and the God~l-ook unit succ6ss,;~1y inputs the set of selected optimal e~G-ihlion codevectors multiplied by the set of selected gains where desired, into the G~ pOn~' 9 set of 10 i.,t~rpokllt-d s~.-ll-es;s filters to produce the related set of ~.,tl-e;,;Led signal vectors for the given input .~f~ nce signal for sull~ldrllidlly reconstructing the input signal.
Brief Des~ lion of the Drawin~s FIG. 1 is a ~eneral block 5CIleilldliC diagram of a first .,.L- " "enl of a digital speech coder encoder unit that utilizes the present invention.
FIG. 2 is a detailed block s~l~el"aliG diagram of a first ~".L -~-~1 of a synthesis unit of FIG. 1 in acGo,~ance with 2 0 the present invention.
FIG. 3 is a detailed block sGllff-,l - diagram of a LPC
analyzer of FIG. 2 in acG~rdance. with the present invention.
FIG. 4 is a flowchart diagram showing the general sequence of steps pe(hr",ed by a digital speech coder 25 l.dns-..ilt~r that utilizes the present invention.
FIG. 4A is a flowchart diagram that illustrates a first e.,.L -enl of a fast Godebook search in accordance with the present invention.
FIG. 5 is a flowchart diagram that illustrates a first 30 manner in which an LPC-SF synthesis filter and perceptual v.~i~hlin~ filter for the m-th su~pa.lilion may be i"" 'e."en~d in accordance with the present invention.
FIG. 6 is a flowchart diagram that illustrates a second manner in whlch an LPC-SF synthesii filter rnd per~tual WO92/16930 _ PClVlrS92/01299 210378~
hli,7~ filter for the m-th su~pd,lilion may be i",~l~",ented in accon~ance with the present invention.
FIG. 7 is a flowchart diagram that illustrates a detailed fast codebook search method to ~ ,r" ~e weighted squared 5 error in accur~ance with the present invention.
iled Descr~tinn of a Preferred Ernh- ~iment FiG. 1, numeral 1ûû, illustrates a general block scliei"atic diagram of a digital speech coder l,t.nsmitl~r unit 1 û that utilizes the present invention to signal process an input signal utilizing at least a codebook unit (1û2~, having at least a first codAboo~ memory means, a gain adjuster (1û4) where desired, at least a first synthesis unit (1û6) having at least a first a~"ll,esis filter, a combiner (1û8), and a perceptual 15 ~'llillh unit (11û), to substantially reconstruct the input si~nal, typically a speech ~ r,n. The input signal is pàl liliùned into succeâsive time intervals, each time interval signal partition having a r~r~,ser,làli~e input vector having at least a first ,t,~r~ser,ldli-G electrical signal. Electrical 20 si~nals of the lep-esenldl;~ input vectors are utilized to at least generate a related set of sy.,ll,esifed signal vectors that may be utilized to substantially reconstruct the input signal.
The at least first ~o~ehook memory means provides particular ~.~cilali~n codevectors from the ~odebook memory of the 25 codehoo~ unit (102), the ~o~book memory having a set of e~c;laliun codevectors stored therein responsive to the r~prese"~dli~G input vectors. Generally, the codebook unit (102) c~"".riaes at least a cod~book memory storage for storing particular excitation codevectors, a co~ebook search 30 controller, and a codebook e~ildliol1 vector u~li",i~er for determining an optimal excitation cûdebook vector. Where desired, a gain adjuster (1 û4), typically an amplifier, multiplies the particular excitation codevectors by a selected excitation gain vector to substantially provide correlation 21~378~ .
WO 92/16930 PCT'/US92/01299 .. . .
with an ener~y of the ~I~pr~ /e input vector. The at least ~irst ,~pr~senlat;-e electrical si~nal for each fep(~se~,ldli~le input ~e~re,nce signal of each time interval si~nal partition and the particular ~ itdl;~n cûd~ tor, where desired S adjusted by mu ~ by the selected gain vector, are input into the synthesis unit (106).
FIG. 2, numeral 200, is a detailed block scl~6", ti~
dia~ram of a first 6111L li~ ,6nl of an at least first :.y"ll,esis unit (106) of FIG. 1 in acc~,dan~e with the present invention.
10 The at least first synthesis filter obtains a c~r,~s~,o~ ,9 o~ d sisnal vector for each repres~l,ldt;ie input sisnal vector. An at least first synthesis unit (106) may include a pitch analyzer (202) if desired and a pitch synthesis filter (206) if desired, to obtairl a long term predictor for further 15 adjustin~ an adjusted codebool~ vector. A first .y"ll,esis unit typically further c~""~ises at least a LPC analyzer (204) and at least a first LPC s~,ltl,esis filter (208).
FIG. 3, numeral 300, is a detailed block scl~."dlic dia~ram of a LPC analyzer (204) of FIG. 2 in ac~r~al~ce with 20 the present invention. The LPC analyzer (204) typically utilizes a LPC extractor (302) to obtain pdldlll~ l from a ~allili~ned input signal, quantizes the pa,d",~t~.~ of time si~nal partitions with an LPC quantizer (304), and interpolates the pa,d-"~t~ of two adjacent time signal pa,lili~ns with an 25 LPC i(ltt~r~OIalur (306) as set forth i~"",e.lialely following.
The at least first s~(,ll,esi, filter is typically at least a first time-varying linear predictive coding s~"l~,esis filter (LPC-SF) (208) having a transfer function substantially of a form:
3û H(z) .
1 - ~a jz-i i.1 .
where aj's, for i-1,2,...,p represent a set of es~i",al~d pr~ 2n c~ obtained by analyzinq the W~92/16930 - rcr/us92/012g9 ~ 210378~
cGr.~spo.,' )~ time si~nal partition and p le~ a~ a a predictor order. The LPC-SFs of a selected adjacent time siSinal partition and of a time partition i.llll,~ i;~t~ly thereafter are substantiaily of a form:
Ha)(z).
1 - ~a j(i)z-i i~1 where a;(i)'s, for i ~ 1, 2, 3, ..., p and j .1, 2 ~p.~,se.~l a set of pr." :~n coefficients in a selected adjacent time signal partition when j . 1 and of a curr~nt time signal partition i"""edidlely II,ert,drler when j-2"t,spe.ilii~1y, p represents a0 predictor order such that an impulse response for the transfer function H(i~z) is substantially h a)(n) ~ a(n) + ~a j(i) h (i) (n-i) where a(n) is an impulse function, and such that the impulse 15 response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear illlelr~oldli~n of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) ~ amh(l)(n) + ~mh(2)(n) .
20 where ~m ~1- am and 0 < am < 1, where a different am iS
utilized for each suL~a,lili~n, thereby providing a transfer function of the i,,le.yolaled synthesis filter substantially of a form:
Hm(z) - amH(1)(z) + ~mH(2)(Z) - A(1)(Z)A(2)(Z) where A'm(z) ~ maj(1) + amaj(2))z~
i~1 ;
and A(i)(z). 1 - ~;aj(i)z~i fOr j . 1,2, i.l wherein the perceptual weightin~ filter at the m-th subpartition of a current time interval si~nal partition suL ,Id"li~lly has a transfer function of the form:
W ( ) A(1)(Z)A(2)(z)~
where ~is typically selected to be SU~ldll '~y 0.8.
For a fast c~vJ~'vook search method in a second ~ l,Gd;",~nl, the synthesis filter (208) may be approximated by an all pole synthesis filter that is utilized to provide p~ "~tvr:, for illt~ .lOIdlill9 su~p~,lilions in the LPC-SF filter and in the perceptual ~ I,ling filter, wherein the all pole synthesis filter su~sldr,lia'!y utilizes at least: an estimating unit, responsive to selected interpolated impulse response samples, for ~:llillldlil~g a first p+1 aut~vcGr,~ldlion co~r~i ;anl~ using selected truncated i"l~",olal.,d impulse response samples; and a converting unit ,t,,~or,s;~ to the ~;,li."dlad cor,vl~lion coefficients, for ~v~vrl~rli,~g the autocorrelation c~ver~i Pnl:. to direct form prediction coefficients using a recursion algorithm.
The e~li",ated avloc~vr,eldlivn co~vrri P~ at the m-th su~pa,t :i~n can be e.~,,e,ssed as: Rm(k) . ~hm(n)hm(n+k) for k . 0,1, ..., p and the summation is over all available partition impulse responses, such that Flm(k) - llm2R(l)(k) + ,~m2R(2)(k) + c~m~m(R(12)(k) + R(21)(k)) where F.(i)(k) - ~ h(i)(n)h(i)(n+k) for k - 01, ... p and j-1 2 are autocorrelation coefficients of uninterpolated impulse 30 response of the adjacent and current partitions, and ~'O 92/16930 PCI~/l,rS92/~299 ~3~8~ -R(ii)(k) - ~ h(i)(n)h(i)(n+k) for k.0,1,...,p and i,j-1,2 where i7~;, are cross-c~". ' '-Dn coefficients between the u, ,' ~,~laled impulse t~s~,onses.
Where desired, the synthesis unit further includes a pitch s~"l~,esia unit, the pitch a~";.,esi;, unit including at least a pitch analyzer and a timo v~.ry;,\~ pitch s~"ll,es;a filter having a transfer function substantially of a form:
B (z) -1 ~-T
where T le~ S~ a an eali",dl~d pitch lag and ~ ,t~presenla sain of the pitch predictor.
The perceptual weightin~ unit, responsive to the transfer function of the interpolated s~"ll,eais filter and to output of the combiner, includes at least a first perceptual l,li"~ filter having a transfer function subaldni'-"y of a 1 5 form:
W(z) ~ H((/)~) where y is typically selected to be suL,a~d"ti~ 0.8.
Excitation code vectors are typically stored in memory, and the codttbook unit, rtjs~ sive to the perceptual weighted squared error, si~nal ~,vcesses each selected input reference vector such that every e,~,ilation codevector in the codebooh memory is si~nal rJ,ucessed for each selected input ,~r~tenc~
vector, and delu,,,, ,es the optimal excitation codevector in the codebook memory.
The ~debook unit, responsive to the impulse response of the at least first a~"ll,esis filter, utilizes a fast codebook search, wherein su~ald,llidlly the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ej, is ~e~er", )ed such tha~:
WO 92/16930 Pr~/US92/01299 .10 2~378~
Ej . Ilxll2 Ai2 where x It,pf~n~r,t~ an input tar~et vector at a selected su~pd-lilion that is suv-sldn~i~lly equal to an input ~e~el~nce si~nal vector at a selected suL,~a,liti-vn filtared by a 5 co"espol, " )9 i,.t~r~.oldled ~._ "hli"~ filter with a zero-input response of a CGrlv_,JOII " ,9 i.ltbr~JGldl~d weighted LPC-SF
subtracted from it, Aj ,~p,c,ser,la a dot product of the vector x and an i-th filtered cod~ tvr Yi,m at an m-th su~d,lilion, and Bj ~b,uresenla the squared norm of the vector Yi,m. The 10 co~ ,ol,' ,g interpolated weighted LPC-SF has a transfer function of Hm(z/~), such that:
H m (z/r) - 1 .
1 - ~ymajmz~
i-.1 where for an m-th subpartition, ~ is typically selected to be 15 0.8, and ai,m ,for i.1,2,p, such that p is a predictor order, ,~,p,~s~nl the paldlll~l~la of cv"t,:.~,or, " ,~ i,,le,,~vlaled LPC-SF, the impulse response of Hm(z/~), hwm(n)~ is su~slanli~lly equal to:
hwm(n) . ~nhm(n), and where hm(n) is an impulse response of cor,t,spondi"y LPC-SF, utilizing a fact that hm(n) is a linear inl~,~oldlion of the 25 impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n)~ at each interpolating subpartition, determined in a fast codebook search as a linear i"lbr~,Glalion of two impulse rr~sponses of related previous and current uni~,le"~.vldl~d weighted LPC-SFs:
hwm(n) ~ mhw(1)tn) + ~mhw(2)(n), WO 92/16930 _ _ PCr/US92/01299 ~ 11 21~3~85 where hwa)(n) - ~nh(i)(n) for j.1,2 are ~,-,uonenlidlly weighted u.,i"ter~,ol~l~d i~pulse It,aponses of the previous, when j,.1, and the current, when j-2, LPC synthesis filters, and where ~m 5 .1- m and 0 ~ m ~1, where a different m is utilized for each subpa~ti~i~n. The filtered cod~ tur Yi,m is determined as a convolution of the i-th eAGi~.ltiol~ cod~uc~ur cj with the correspondin~ weighted impulse response hwm(n)~ the convolution being substantially:
10 Yi,m ~ Fwmci~ where hWm(O) O O .. O
hWm(1 ) hwm(0) --hWm(2) hwm(1 ) hwm() .. O
Fwm _hWm(k-1) hwm(k-2) hwm(k-3) hwm(o) and where k ,epres~r,t~ a ~il"er,si~n of a codevector, further utili~ing the fact that hwm(n) is a linear 15 i"'~.~,oldlion of the impulse ~ ,onses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector Yi,m at each interpolating subpartition may be sLtj ,lanl;~ dett,r."i"ed as linear interpolation of two codevectors filtered by the related previous and current 20 uni-,lt,rj,oldled weighted LPC-SFs:
Yi,m- mYi(1) + ~myj(2) and where yja) - Fwa)ci for j_1,2 and where matrices Fw~1) 25 and FW(2) have substantially a same format as the matrix FWm~ but with different elements hw(l)(n) and hw(2)(n), respectively .
The squared norm Bj at each interpolating subpartition is SUI.)~ ' 'Iy a weighted sum of a squared norm of a filtered WO 92/16930 2 ~ ~ 3 ~ 8 5 12 PCI/[~S92/01299 cod~ ~3~10r yj(1) the squared norm of the filtered cod~ tur yj(2) and a dot product of those two filtered codevectors substantially beins:
Bj. m2ll yj(1)ll2 + ,3m2ll yj(2)ll2+2mi3m<yi(1).yi(2)~
5 where ,3m -1- m and 0 ~ m < 1 where a different ixm iS
utilized for each su,.~a,liliùn. The codebo~ unit determines of the dot product Aj for each int~.~ol.~ s,~ a,li~ion substantially utilizing a bac,~ -d filter .e~ponsivr~ to the matrix FWm and an input si~nal vector x such that z F~wmx 10 where t represents a l,d"apose operator and a dot product d~t~r",;.~er for forming a dot product such that:
Aj ~ z- cj >
where cj is the ith e~uitdlion cod~t~r.
A cG",b..,er (108) typically a subtractor subtracts each 15 first corrected corresponding sy,ltl,6siLed signal vector from the input ,~fu.~nce vector related thereto that related input ,~t~re,nce vector being a vector from a set of vectors for the input r~f~ri3nGe signal to obtain a c~rl~5s tohd;l~9 reconstruction error vector. The perceptual ~ lllillg unit 20 (110) wei~hts the reconstruction error vectors utilizing the at least first perceptual weighting filter wherein for each selected Si~,J ,d,lilion second corrections of partition pd,d",-aler disc.Gr,linuities are applied su~ldnti& 'y providing corrected reconstruction error vectors, and further 25 d~t~r",-, ,9 CGII~:: t perceptual weighted squared error.
The CGII~ ' ~ perceptual weighted squared error is utilized by the codeboo~ unit to determine an optimal ~x~ildli~n ~odu~l~ctu, from the odebook memory for each input r~,~rence vector. A selector l~aponsh/G to the 3 0 corresponding perceptually weighted squared error is utilized to dt,lt:r", ,e and store an index of a codevector having a perceptually welghted squared error smaller than all other errors produced by other codevectors. Where desired the gain adjuster (104) is uti,ized to multiply the optimal excildli~n ~ 13 21~3785 cod~ ,turs by particular gain factors to substantially provide u5.ste~1 where desired, optimal eA ;ldlion cod~ Lu"
c~r,t,ldl~d with an energy of the ,t,pn.3~nl..~;.u input -,"..ence si~nal such that the selected adjusted, where - 5 desired, optimal ~ACitdliOI) codevectors are signal prùcessed in the at least first s~"Ll,esis unit (106) to substantially produce ~"II,~si~ed signal vectors for reconstructing the input signal.
Typically, every ~ ildti~n cod~ .tur for each input 10 '~ ~nc~ vector is si~nal tj,ucessed to doh.", ~e an optimal eAciL~tion codu-~.ct~, from the ~,odebook memory for each input ~ererence vector.
FlGs. 4 and 4A, numeral 400 and 450, are a flowchart diagram showing the general sequence of steps performed by a di~ital speech coder t,dns",;~l~r that utiiizes the present inventiûn, and a ~ a,l diagram that illustrates a first ~",L- " "~.,l of a fast codebûoi~ search in accurJance with the present invention, l~specti~ly.
The method for substantially reconstructin~ an input signal, typically a speech ._Jufurl", provides that, the signal being pa, lilioned into successive time intervals, each time interval signal partition having a ,~rc,se~ ti,/v input re~e,~nce signal (402) with a set of vectors, and having at least a first l~pr~.~e.,ldlh/~ electrical signal for each rep.esenldliio input ,t,ter~nce signal of each time interval signal partition, the method utilizes at least a ,o~ebook unit having at least a ,odebool~ memory, a gain adjuster where desired, a synthesis unit havin~ at least a first synthesis filter, a combiner, and a perceptual .. i,~l~ling unit having at least a first perceptual 30 ~ lllillg filter, for utilizing the electrical signals of the ,t,tjre~enldlive input reference signals to at least generate a related set of sy"ll,esi~ed signal vectors for substantially reconstructing the signal.
The met~od substantially comprises the steps of:
WO 92/16930 PCI`/US92/01299 2103785. ,, (A) utilizin~ thè at least first represel,ldli~/e electrical si3nal for each ,epr~ nlali:u input ,~"~r~nce signal (402~ for a selected time si~nal partition to obtain a set of l", ,It,r~.Glal~d pdld~ lUr~ for the at least first synthesis filter (404) then 5 (B) utilizing the at least first a~r"ll,esi;, filter to obtain the c~r,~a~,ondi,)~ impulse response ~ep,~selildlion and illl~r~Jolalillg the impulse ,es~conses of each selected adjacent time signal partition and of a current time signal partition i"""ecli~t~ly Ill~,ea~ler to provide a set of inler~,olàled 10 ayllllle~ia filters for desired subpartitions; and utilizing the i"lt,r~oldled a~ l,es;s filters to provide a c~ a~,onding set of ir,tur~,olated perceptual ~.6i~1)1in~ filters for desired s~bpa, liliuns (406). I"lt" ~,olal;~n provides for smooth transitions of the s~"ll,esia filter and the perceptual 15 ..~.i~llli,~g filter between each pair of adjacent partitions are obtained.
Next (C) the set of input ~f~ ce signal vectors the related set of i" ~,ûldled a~"ll,esis filters and the related set of interpolated perceptual ,.~:~ ',li"g filters for the 2 0 current time si~nal partition are utilized to select the c~r,~s~,ori ,9 set of optimal exci~dlion codevectors from the at least first codebooh memory (408) further i"")le",en~ing the following steps for each deâired input ,ufurenGe signal vector (401) :(1) providing a particular e~cildli~n cûd~ lur 25 from the at least first co~ebook ~emory the c~ûdeboo~ memory havin~ a set of eAuild~iûn codevectors stored therein elSpOrl3;J~3 to the reFi,eser,ldli~e input vectors (4û3);
(2) where desired multiplying the particular e~cildlion codevector by a selected excitation gain factor tû
30 substantially provide cG-,~ldlion with an energy of the representative electrical signal for each repr~senldli~e input ,t"erer,ce sisnal vector (405); (3) inputting the particular excitation codevector multiplied by the particular gain into the co"~spon ,g i"~u ~,oldled synth~sis ~ilter ~o p-oduce the WO 92/16930 PCI~/~ rS9~/01299 ~ 15 210~78~
siLdd signal vector (407); (4) subtracting the s~ d si~nal vector from the input f~erence signal vector related thereto to obtain a cor.e_porldi"g reconstruction error vector (409); (5) inputting the 5 reconstruction error vector into the corl~o.por,~
r~Gldted psrceptual ~ unit to ~--l .Ill )e a CGIl~S~ ond;~ perceptually weighted squared error (411);
(6) storing index of codevector havin~ the perceptually weighted squared ~rror smaller than all other errors produced 10 by other cod~ ctul~ (413); (7) repeating the steps (1),(2),(3),(4),(5),and (6) for every ~A~iildli~n codevector in the codebook memory (415) and ;Ill, 'e.llerllil)g these steps utilizing a fast ~d~l,ooh search method, to ddlellll;lle an optimal eAci~ation codevector for the related input reference si~nal 15 vector (410,417); and (D) succes~ ly inputting the set of selected optimal e~cildli~n cod~u~tur~ multiplied by the set of selected gains where desired, into the c~ ,Gr "~ set of illl6r~ 01dl~d :,~,llll~s;s filters (419) to produce the related set of s~llll,esi~ed si~nal vectors (412) for the given input 20 relre~dnce signal for su~lanlially reconstructing the input signal (414).
As set forth above, the method typically utilizes the at least first synthesis filter, SLI,:.Idl.:-'ly at least a first time-varying linear pr~ o coding synthesis filter (LPC-25 SF) where ris typically selected to be suL ,l~l~t;dlly 0.8,gen~ approAilll~llcld by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual ~ g filter.
FIG. 5, nurneral 500, is a flowchart diagram that 30 illustrates a first manner in which an LPC-SF sy,ll~lesis filter and perceptual weighting filter for the m-th subpartition may be illlr !e ~enldd in accordance with the present invention. LPC
~,o~rrici~rll:, of a previous time signal partition {aj(1 )} and of a current time si~nal partition i"""edialdly thereafter {aj(2)}
2103~8~
, are each utilized to ~enerate impulse l~sponses (502, 504) from an LPC-SF, being h(1)(n) . a(n) + ~;a(l)h(1)(n-i) and i.1 h(2)(n) . a(n) + ~;a(2)h(2)(n-i), .~,s~,ect;~,ly where a(n) is an i -1 impulse function and aj(i), for the set i-1,2,...,p and j~1,2, 5 ,t,prusc.~ts a set of quantized pr. li~ cse~i e ,l~ in a previous time partition for j.1 and the current time partition for j.2. h(i)(n) ,~prese,l~a the impulse response of an LPC-SF.
The impulse r~,ponses for the previous time partition input and the current time partition input are i"la",rjldlad to obtain 10 the interpolated impulse response (506), substantiaily, hm(n) - mh(1 )(n) + ~mh(2)(n)~ where ~m ~ rn and o < am c 1. Autocorrelations of hm(n) are d~lt~.l"- ,ed (508) that are then converted to LPC ~o~i e.,la (510), su~ ,)l;z:~y generating, for 15 selected su~&li--~hs, an il,l~l~.Gl._~d LPC-SF having Hm(z)- for j~1,2 and an interpolated 1 - ~a j(i)z-i i.1 perceptual h._htillg filter having Wm(z)- H(z)) wherein y is su~:,ldr,i-'~y 0.8.
FIG. 6 numeral 600 is a flowchart diagram that 20 illustrates a second manner in which an LPC-SF synthesis filter and perceptual ~i~hlillg filter for the m-th subpdrti~ion may be i"" 'e."~r,lad in accor~idnce with the present invention.
LPC coefficients of a previous time signal partition 25 ~a;(1 )) and of a current time signal partition illllll~did~ly II,er~a~l~( {aj(2)} are each utilized to generate, for each desired su~pa, lili~n an illl~r~GIdl~d LPC-SF (602) having 2/ 1 693~ 17 PCr/U592/01 299 Hm(z) - ~mH(1)(z) + ~mH(2)(z), sub~k.n 'l~ bein~ a cu.,~_pon ~ z-transform of the illl~llpOla11,d s~.,1116sis filter (506), and c~ ,ts bein~ as set forth above, and also an ol 1ed, ~ 9 filter (604), havin~ Wm(Z)- Hm(~) 5 c~e~i- 3.~1s being as set forth above. A system i"~ ~."~nLi"~
the method of this invention also may be utilized in acco,Jance with the method des.i,i~ed above.
FIG. 7, ~umeral 700, is a flowchart diagram that illustrates a detailsd fast cod~ol~ search method to 10 dehr., ,e wei~hted squared error in acco(Jance with the present invention. The fast cod~l)oo~ search method substantially further includes utilizin~ a si"" li~ied method to delt~r,-,:.,e the perceptually weighted squared error (724) between an input signal vector (401) and a related ay"11,eai~ed 15 codevector utilizing an i-th e~;t~`;on codu-e~ t~r (708) denoting this error by Ej, such that:
E ~ 2 Ai2 where x ,ep.~se.,ta an input target vector (702) at a selected 2 0 subpartition that is substantially equal to an input re~ nce signal vector at a selected subpartition filtered by a c~r,l,apor..li,~ r~Glaled weighting filter with a zero-input response of a C~llt,apO~ g interpolated weighted LPC-SF
subtracted from it, Aj le~r~se-~1a a dot product of the vector x 25 and an i-th filtered cod~ lur Yi,m at an m-th subpartition (7û6), and Bj l~pltlS~IIla the squared norm of the vector Yi,m (722). A co,-t,a~on~ g ill~ JGI~1~d weighted LPC-SF has a transfer function of Hm(z/y), such that:
Hm(z/~). 1 1 - ~ymajmz~
i ~1 -210378~ .
WO 92/16930 PCI`/US92/01299 where for an m-th suipd,lition, ~is typically selected to be 0.8, and ai m for i-1 2 ...p such that p is a predictor order fe~r~senl the parameters of c~r,~_~or~ "1oldlc,d LPC-SF
the impulse response of H(z/~) hw(n) is sui ala"~idil~
equal to:
hw(n) _ ynhm(n), and where hm(n) is an impulse response of Corl~a~Jorl~ l9 LPC-SF
utilizing a fact that hm(n) is a linear i"~,yGldli~n of the impulse ,e,~i,onses of related previous and current u~, ,ltlr~,~ldled LPC-SFs hwm(n)1 at each i"~r~.olaling subpartition d hr", ,ed in a fast co~ebos~ search as a iinear i"lt,r~oldlion of two impulse , ~sponses of related previous and current ur ,t~".oldled weishted LPC-SFs:
hwm(n) - amhw(1 )(n) ~ i3mhw(2)(n) where hw(i)(n) . ynh(i)(n) for 1 12 are exponentially w~ighted un lltnuGldled impuls~ ~5~uoi ses of the previous when j-1 and the current when j-2 uninterpolated signal partitions and where ~m -1- m and 0 < ~m < 1, where a different m is utilized for each sui pa,lilion.
The fiitered codevector Yi m is delt"",ined as a G~r,.t. lti~n (710) once per signal partition of the i-th e,~Gitdli~n codevector cj with the cG"t,a~.ondii~g weighted impulse response hwm(n)~ the convolution being substantially:
30 Yi m ~ Fwmci~ where Wo 92/16930 2 1 ~ 3 7 8 5 PCI-/~'S92/01299 hWm(O) O O .......... O
hWm(1) hwm(0) 0 .......... 0 hWm(2) hwm(1) hwm() -- O
Fwm - . . . .......... .
. . .
_hWm(k-1) hWm(k-2) hwm(k-3) hwm(0)_ and where k .~.resents a ' "~r,~ivn of a cod~ ,vlur, further utilizing the fact that hwm(n) is a linear i,.l~rpGlaliûn of the impulse ~:",ûnses of related previous and current uninterpolated weighted LPC-SFs, the filtered codv~vc~vr Yi,m at each i~ oldli.,g subpartition may be svv~:.lanli~lly del~-."ined as linear interpolation of two codevectors filtered by the related previous and current v-,:.-le-~,Gl~l~d weighted LPC-SFs:
Yi,m- mYi(1) + ~myj(2~
and where yia) - Fw(i)ci for j-1,2 and where matrices Fw(1) and FW(2) have suLsld.,ti~ ^ a same format as the matrix FWm~ but with difterent elements hw(1)(n) and hw(2)(n), .e~pe-vti,~vly. The squared norm Bj at each inl~".oldli,)g subpartitiûn is substantially a weighted sum (722) ûf a squared norm (716) of a tiltered code~vctvr yj(1)(712), the squared nûrm (72û) of the filtered codevector yj(2)(714), and a dût prûduct (718) of thûse twû filtered cûdevectors, substantially being:
Bj. am2ll yj(1)ll2 + ~m2llyj(2)ll2 +2m~m~yj(1).yj(2)~
2~v where ~m -1- m and 0 < m ~1, where a different m is utilized for each subpartition. Determination of the dot product Aj for each interpolating subpartition substantially cû"",rises two steps:
A) back~ filtering (704) such that z = Ftwmx; and 2103~8~
where t ~ s~r,t~ a lldl~apose operator: and B) formin~ a dot product (706) such that:
Aj - ~ z- cj ~ , where cj is the ith eA~,itdt;~n codu/__tur.
Then Aj, Bj, and x are utilized to ~ -Ill Ie error Ej, such that:substantially:
E j _ llxll2 - Bij (724) .
Backward filtering, dot product d '.r,l. )dlion for Aj, dot producUon d~l~rl,l;nalion for Bj, del~,rll, ,iliùn of two squared 10 norms, obtaining a weighted summation, and delbr,,, ~;l,9 wei~hted squared error are p6,lul,l,ed for every desired interpolatins subpartition.
This novel device, method, and system, typically i,~" !e .,~nltld in a di~ital speech coder, provides for an 15 intur~ol~ d s~llllesia filter for smoothing discontinuities in a~ eai~d reconstructed signals caused by dis~rl~;.,uities at partition boundaries of sampled si3nals. This illlt,l~,oldled s~.lllles;~ filter has two particularly important propei lies: a resultin~ s~ is filter H l(Z) is gu~lld,lleed to be stable as 20 lon~ as the filter H(1)(z) and H(2)(z) are stable; and the resultin~ s~lllll6sis filter is a pole-zero filter that is different from the LPC modelins method based on an all-pole filter. Two rs.,lL- ' Iler~l~, set forth above, provide for reconstruction of an LPC-SF and a perceptual ~.._i~l,li,~g filt~r 25 from the il~tbr~JGldl~ impulse response. The first 6l,1bo~' llent, utilizing the pole-zero synthesis filter obtained from interpolating the impulse respon~es of two all-pole synthesis filters for adjacent time partitions generates an interpolated synthesis filter, and necessilates 3 0 updating/interpolating of the perceptual weightin~ filter (604). The interpolated ~ hlill~ filter t604) is not necessalily stable, requirin~ a stability check for each set of illlbr~,olaled cobr~k,;~rll~. Where instability is detected for a 2I~37~5 particular subpartition, ul,inlt,r~,olated co~rri ~.lt~ are used for that subpd, lilion .
- To avoid the instability check ~Csoc lpd with utilizing the pole-zero s~.,ll,esi, filter, a second e."bo~i",ei~l utilizes 5 an all-pole sy.,lll~sis filter to ap~ru~i",ald the pole-zero filter of the first ~",b~di",e,nl. In the second e",L~ "enl, the first p + 1 a~lucor,-' ~n coefficients of the i"l~r~.ol~led impulse response for a suLpd,t;~iùn are ~ , ~, then converted to direct form prediction coerfici~r,ls, typically utilizin~ the 1 û Levinson recursion al~orithm. The resulting prediction coe~ric;ehl~ ar~ utilized in a LPC-SF and a perceptual I.Ii.,g filter for the su~pd.lilion. Thus, the required number of computations required to generate the first p+1 autocorrelation coerric;~r,la from the impulse responses per 15 partition is sul, .lani -'~y of the order of 3(p+1)L + 4(p~-1)Njtp, where L is a length of a truncated/~sli--,al~d impulse response and Njtp is substantially a number of suL,parlili~ns where ir,~r~Glation is p~-ror",dd. An illlp~lldl~l aJvd-,l~e of the second ~., L "enl 2û is that to delt7r-, le the autocorrelation coerr. rll~ of the lal~d impulse response, there is no necessil~ to linearly interpolate an entire truncated impulse response sequence.
Computer simulations were utilized to compare the 25 pe(Fu""ance of the method of this invention with two other LPC interpolation methods using direct form ~r. ~: n c~.,r o ,1~ and PARCOR co~r~i hl~, r~s?e~;t;~ly, as i"l~"u~lalion pard"~ ra. A speech codr~r utilizin3 this invention was configured at bit-rates of 4800 and 8000 bit per 3û second (bps) r~s~,eclii~ly. At 8000 bps, almost identical pel~ur",ance, both subjectively and objectively, was obtained when using the direct form prediction coefficients and when usin~ impulse response for inlt"~J~laliûn. However, at 4800 bps, the coder utilizing this invention outperforms the other WO 92/16930 PCI`/US92/01299 210378~ 22 , two il~tv~GlaliOi~ methods. Therefore, the method of this invention not only offers a s;~ ic,alll computational ad~. ~ld~6 over other typical i~ ,Gl~ methods, but also improves speech quality.
Further, when the impulse response of the LPC-SF is utilized, a codevector filtered by the i"~ ldt~d s~"ll,esis filter is simply equal to the linear intv. ,.,oldlion of the two cod~lvcturs filtered by the previous and current ~nillte,r~Joldt~d s~ llesis filters allowing a fast codeboo~.
search. The second ~ l of LPC i" ~Gl~t;~n methods thus provides a fast ~)~ebook search nnethod, as is illustrated below. Where p, K, N, and Ns are used to represent the LPC
predictor order, vector length, e~ -n codeboo4 size, and number of subpartitions per partition, ~a~e~ ly, the following table gives a c~""parison of co-Jebook search cv"~ of usin~ the fast cod~book search method and a conventional al~orill,l".
TASK COMPI FXITY (OPFRATION.~/PARTITION) Conver~jon~l F~Ct Codebook S~ch Filtering codG,/~--to,a pkNNs pKN
Computin~
ener~ies KNNs 2KN + 3N(Ns-1) Computing dot products KNNs KNNs + ( 2 )(Ns-1 ) Total (p+2)KNNs (p+2+Ns)KN +3N(Ns-1) + 2 (NS-~) WO 92/16930 23 PCI`/1'592/01299 21~785 For example, where p, K, N, and Ns equal 10, 40 1024 and 4",_p~ ly (with a partition size of 160 samples and a sampling frequency of 8 kHz), a total of major computations for a cc"J_.,Iional co~ebook search is of the order of 98.3 MIPS
5 (Million Instructions Per Second), but only on the order of 33.3 MIPS for a fast cod~ oh search, yielding sul,~Id"lially a 66 percent co", ' ~y reduction. When cc",b:.,ed with other efficient coding schemes, the method and hardware i", '~ "rritdli~n of the present invention provide for 10 substantial reduction in computational cost for CELP-type coders, provide improved speech coder performance, and maintain a l~asonably low encoding co""' ~y.
Thus, the second e",L- "e,r,l is a preferred e"l~o~i",t",l since less computation is required, odeboo~ sear~;l, ,9 c~", ' ~y is 15 ",;";",iLed, and partition boundary sampling discontinuities are ,",G~ltl-ed, thereby providin~ improved :.~"II,e~i~ed si~nal vectors for reconstructing input signals.
I claim:
(5) an illlt~r~GIdl~d perceptual weighting unit, responsive to 30 the corlea~.oncli~g reconstruction error vector, determines a corresponding perceptually weighted squared error;
(6) a selector"t,~ol~si~e to the cGr,~spon~ ~g perceptually weighted squared error, stores an index of a codevector having the perceptually weighted squared error that it determines to WO 92/16930 PCI`/US9V01299 2103~8S 4 ~
be smaller than all other errors produced by other codevectors;
(7) the device, system and method repeat the steps (1),(2),(3),(4),(5),and (6) for every ex~ dtioi7 God~ ,tor in the ,od~boo~ memory and i.", ~e."ent these steps utilizing a fast 5 r,oclbboo~ search method, to de~-~ an optimal e~Gihlion God~"ro~,tor for the related input ~fn.~nce signal vector; and the God~l-ook unit succ6ss,;~1y inputs the set of selected optimal e~G-ihlion codevectors multiplied by the set of selected gains where desired, into the G~ pOn~' 9 set of 10 i.,t~rpokllt-d s~.-ll-es;s filters to produce the related set of ~.,tl-e;,;Led signal vectors for the given input .~f~ nce signal for sull~ldrllidlly reconstructing the input signal.
Brief Des~ lion of the Drawin~s FIG. 1 is a ~eneral block 5CIleilldliC diagram of a first .,.L- " "enl of a digital speech coder encoder unit that utilizes the present invention.
FIG. 2 is a detailed block s~l~el"aliG diagram of a first ~".L -~-~1 of a synthesis unit of FIG. 1 in acGo,~ance with 2 0 the present invention.
FIG. 3 is a detailed block sGllff-,l - diagram of a LPC
analyzer of FIG. 2 in acG~rdance. with the present invention.
FIG. 4 is a flowchart diagram showing the general sequence of steps pe(hr",ed by a digital speech coder 25 l.dns-..ilt~r that utilizes the present invention.
FIG. 4A is a flowchart diagram that illustrates a first e.,.L -enl of a fast Godebook search in accordance with the present invention.
FIG. 5 is a flowchart diagram that illustrates a first 30 manner in which an LPC-SF synthesis filter and perceptual v.~i~hlin~ filter for the m-th su~pa.lilion may be i"" 'e."en~d in accordance with the present invention.
FIG. 6 is a flowchart diagram that illustrates a second manner in whlch an LPC-SF synthesii filter rnd per~tual WO92/16930 _ PClVlrS92/01299 210378~
hli,7~ filter for the m-th su~pd,lilion may be i",~l~",ented in accon~ance with the present invention.
FIG. 7 is a flowchart diagram that illustrates a detailed fast codebook search method to ~ ,r" ~e weighted squared 5 error in accur~ance with the present invention.
iled Descr~tinn of a Preferred Ernh- ~iment FiG. 1, numeral 1ûû, illustrates a general block scliei"atic diagram of a digital speech coder l,t.nsmitl~r unit 1 û that utilizes the present invention to signal process an input signal utilizing at least a codebook unit (1û2~, having at least a first codAboo~ memory means, a gain adjuster (1û4) where desired, at least a first synthesis unit (1û6) having at least a first a~"ll,esis filter, a combiner (1û8), and a perceptual 15 ~'llillh unit (11û), to substantially reconstruct the input si~nal, typically a speech ~ r,n. The input signal is pàl liliùned into succeâsive time intervals, each time interval signal partition having a r~r~,ser,làli~e input vector having at least a first ,t,~r~ser,ldli-G electrical signal. Electrical 20 si~nals of the lep-esenldl;~ input vectors are utilized to at least generate a related set of sy.,ll,esifed signal vectors that may be utilized to substantially reconstruct the input signal.
The at least first ~o~ehook memory means provides particular ~.~cilali~n codevectors from the ~odebook memory of the 25 codehoo~ unit (102), the ~o~book memory having a set of e~c;laliun codevectors stored therein responsive to the r~prese"~dli~G input vectors. Generally, the codebook unit (102) c~"".riaes at least a cod~book memory storage for storing particular excitation codevectors, a co~ebook search 30 controller, and a codebook e~ildliol1 vector u~li",i~er for determining an optimal excitation cûdebook vector. Where desired, a gain adjuster (1 û4), typically an amplifier, multiplies the particular excitation codevectors by a selected excitation gain vector to substantially provide correlation 21~378~ .
WO 92/16930 PCT'/US92/01299 .. . .
with an ener~y of the ~I~pr~ /e input vector. The at least ~irst ,~pr~senlat;-e electrical si~nal for each fep(~se~,ldli~le input ~e~re,nce signal of each time interval si~nal partition and the particular ~ itdl;~n cûd~ tor, where desired S adjusted by mu ~ by the selected gain vector, are input into the synthesis unit (106).
FIG. 2, numeral 200, is a detailed block scl~6", ti~
dia~ram of a first 6111L li~ ,6nl of an at least first :.y"ll,esis unit (106) of FIG. 1 in acc~,dan~e with the present invention.
10 The at least first synthesis filter obtains a c~r,~s~,o~ ,9 o~ d sisnal vector for each repres~l,ldt;ie input sisnal vector. An at least first synthesis unit (106) may include a pitch analyzer (202) if desired and a pitch synthesis filter (206) if desired, to obtairl a long term predictor for further 15 adjustin~ an adjusted codebool~ vector. A first .y"ll,esis unit typically further c~""~ises at least a LPC analyzer (204) and at least a first LPC s~,ltl,esis filter (208).
FIG. 3, numeral 300, is a detailed block scl~."dlic dia~ram of a LPC analyzer (204) of FIG. 2 in ac~r~al~ce with 20 the present invention. The LPC analyzer (204) typically utilizes a LPC extractor (302) to obtain pdldlll~ l from a ~allili~ned input signal, quantizes the pa,d",~t~.~ of time si~nal partitions with an LPC quantizer (304), and interpolates the pa,d-"~t~ of two adjacent time signal pa,lili~ns with an 25 LPC i(ltt~r~OIalur (306) as set forth i~"",e.lialely following.
The at least first s~(,ll,esi, filter is typically at least a first time-varying linear predictive coding s~"l~,esis filter (LPC-SF) (208) having a transfer function substantially of a form:
3û H(z) .
1 - ~a jz-i i.1 .
where aj's, for i-1,2,...,p represent a set of es~i",al~d pr~ 2n c~ obtained by analyzinq the W~92/16930 - rcr/us92/012g9 ~ 210378~
cGr.~spo.,' )~ time si~nal partition and p le~ a~ a a predictor order. The LPC-SFs of a selected adjacent time siSinal partition and of a time partition i.llll,~ i;~t~ly thereafter are substantiaily of a form:
Ha)(z).
1 - ~a j(i)z-i i~1 where a;(i)'s, for i ~ 1, 2, 3, ..., p and j .1, 2 ~p.~,se.~l a set of pr." :~n coefficients in a selected adjacent time signal partition when j . 1 and of a curr~nt time signal partition i"""edidlely II,ert,drler when j-2"t,spe.ilii~1y, p represents a0 predictor order such that an impulse response for the transfer function H(i~z) is substantially h a)(n) ~ a(n) + ~a j(i) h (i) (n-i) where a(n) is an impulse function, and such that the impulse 15 response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear illlelr~oldli~n of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) ~ amh(l)(n) + ~mh(2)(n) .
20 where ~m ~1- am and 0 < am < 1, where a different am iS
utilized for each suL~a,lili~n, thereby providing a transfer function of the i,,le.yolaled synthesis filter substantially of a form:
Hm(z) - amH(1)(z) + ~mH(2)(Z) - A(1)(Z)A(2)(Z) where A'm(z) ~ maj(1) + amaj(2))z~
i~1 ;
and A(i)(z). 1 - ~;aj(i)z~i fOr j . 1,2, i.l wherein the perceptual weightin~ filter at the m-th subpartition of a current time interval si~nal partition suL ,Id"li~lly has a transfer function of the form:
W ( ) A(1)(Z)A(2)(z)~
where ~is typically selected to be SU~ldll '~y 0.8.
For a fast c~vJ~'vook search method in a second ~ l,Gd;",~nl, the synthesis filter (208) may be approximated by an all pole synthesis filter that is utilized to provide p~ "~tvr:, for illt~ .lOIdlill9 su~p~,lilions in the LPC-SF filter and in the perceptual ~ I,ling filter, wherein the all pole synthesis filter su~sldr,lia'!y utilizes at least: an estimating unit, responsive to selected interpolated impulse response samples, for ~:llillldlil~g a first p+1 aut~vcGr,~ldlion co~r~i ;anl~ using selected truncated i"l~",olal.,d impulse response samples; and a converting unit ,t,,~or,s;~ to the ~;,li."dlad cor,vl~lion coefficients, for ~v~vrl~rli,~g the autocorrelation c~ver~i Pnl:. to direct form prediction coefficients using a recursion algorithm.
The e~li",ated avloc~vr,eldlivn co~vrri P~ at the m-th su~pa,t :i~n can be e.~,,e,ssed as: Rm(k) . ~hm(n)hm(n+k) for k . 0,1, ..., p and the summation is over all available partition impulse responses, such that Flm(k) - llm2R(l)(k) + ,~m2R(2)(k) + c~m~m(R(12)(k) + R(21)(k)) where F.(i)(k) - ~ h(i)(n)h(i)(n+k) for k - 01, ... p and j-1 2 are autocorrelation coefficients of uninterpolated impulse 30 response of the adjacent and current partitions, and ~'O 92/16930 PCI~/l,rS92/~299 ~3~8~ -R(ii)(k) - ~ h(i)(n)h(i)(n+k) for k.0,1,...,p and i,j-1,2 where i7~;, are cross-c~". ' '-Dn coefficients between the u, ,' ~,~laled impulse t~s~,onses.
Where desired, the synthesis unit further includes a pitch s~"l~,esia unit, the pitch a~";.,esi;, unit including at least a pitch analyzer and a timo v~.ry;,\~ pitch s~"ll,es;a filter having a transfer function substantially of a form:
B (z) -1 ~-T
where T le~ S~ a an eali",dl~d pitch lag and ~ ,t~presenla sain of the pitch predictor.
The perceptual weightin~ unit, responsive to the transfer function of the interpolated s~"ll,eais filter and to output of the combiner, includes at least a first perceptual l,li"~ filter having a transfer function subaldni'-"y of a 1 5 form:
W(z) ~ H((/)~) where y is typically selected to be suL,a~d"ti~ 0.8.
Excitation code vectors are typically stored in memory, and the codttbook unit, rtjs~ sive to the perceptual weighted squared error, si~nal ~,vcesses each selected input reference vector such that every e,~,ilation codevector in the codebooh memory is si~nal rJ,ucessed for each selected input ,~r~tenc~
vector, and delu,,,, ,es the optimal excitation codevector in the codebook memory.
The ~debook unit, responsive to the impulse response of the at least first a~"ll,esis filter, utilizes a fast codebook search, wherein su~ald,llidlly the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ej, is ~e~er", )ed such tha~:
WO 92/16930 Pr~/US92/01299 .10 2~378~
Ej . Ilxll2 Ai2 where x It,pf~n~r,t~ an input tar~et vector at a selected su~pd-lilion that is suv-sldn~i~lly equal to an input ~e~el~nce si~nal vector at a selected suL,~a,liti-vn filtared by a 5 co"espol, " )9 i,.t~r~.oldled ~._ "hli"~ filter with a zero-input response of a CGrlv_,JOII " ,9 i.ltbr~JGldl~d weighted LPC-SF
subtracted from it, Aj ,~p,c,ser,la a dot product of the vector x and an i-th filtered cod~ tvr Yi,m at an m-th su~d,lilion, and Bj ~b,uresenla the squared norm of the vector Yi,m. The 10 co~ ,ol,' ,g interpolated weighted LPC-SF has a transfer function of Hm(z/~), such that:
H m (z/r) - 1 .
1 - ~ymajmz~
i-.1 where for an m-th subpartition, ~ is typically selected to be 15 0.8, and ai,m ,for i.1,2,p, such that p is a predictor order, ,~,p,~s~nl the paldlll~l~la of cv"t,:.~,or, " ,~ i,,le,,~vlaled LPC-SF, the impulse response of Hm(z/~), hwm(n)~ is su~slanli~lly equal to:
hwm(n) . ~nhm(n), and where hm(n) is an impulse response of cor,t,spondi"y LPC-SF, utilizing a fact that hm(n) is a linear inl~,~oldlion of the 25 impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n)~ at each interpolating subpartition, determined in a fast codebook search as a linear i"lbr~,Glalion of two impulse rr~sponses of related previous and current uni~,le"~.vldl~d weighted LPC-SFs:
hwm(n) ~ mhw(1)tn) + ~mhw(2)(n), WO 92/16930 _ _ PCr/US92/01299 ~ 11 21~3~85 where hwa)(n) - ~nh(i)(n) for j.1,2 are ~,-,uonenlidlly weighted u.,i"ter~,ol~l~d i~pulse It,aponses of the previous, when j,.1, and the current, when j-2, LPC synthesis filters, and where ~m 5 .1- m and 0 ~ m ~1, where a different m is utilized for each subpa~ti~i~n. The filtered cod~ tur Yi,m is determined as a convolution of the i-th eAGi~.ltiol~ cod~uc~ur cj with the correspondin~ weighted impulse response hwm(n)~ the convolution being substantially:
10 Yi,m ~ Fwmci~ where hWm(O) O O .. O
hWm(1 ) hwm(0) --hWm(2) hwm(1 ) hwm() .. O
Fwm _hWm(k-1) hwm(k-2) hwm(k-3) hwm(o) and where k ,epres~r,t~ a ~il"er,si~n of a codevector, further utili~ing the fact that hwm(n) is a linear 15 i"'~.~,oldlion of the impulse ~ ,onses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector Yi,m at each interpolating subpartition may be sLtj ,lanl;~ dett,r."i"ed as linear interpolation of two codevectors filtered by the related previous and current 20 uni-,lt,rj,oldled weighted LPC-SFs:
Yi,m- mYi(1) + ~myj(2) and where yja) - Fwa)ci for j_1,2 and where matrices Fw~1) 25 and FW(2) have substantially a same format as the matrix FWm~ but with different elements hw(l)(n) and hw(2)(n), respectively .
The squared norm Bj at each interpolating subpartition is SUI.)~ ' 'Iy a weighted sum of a squared norm of a filtered WO 92/16930 2 ~ ~ 3 ~ 8 5 12 PCI/[~S92/01299 cod~ ~3~10r yj(1) the squared norm of the filtered cod~ tur yj(2) and a dot product of those two filtered codevectors substantially beins:
Bj. m2ll yj(1)ll2 + ,3m2ll yj(2)ll2+2mi3m<yi(1).yi(2)~
5 where ,3m -1- m and 0 ~ m < 1 where a different ixm iS
utilized for each su,.~a,liliùn. The codebo~ unit determines of the dot product Aj for each int~.~ol.~ s,~ a,li~ion substantially utilizing a bac,~ -d filter .e~ponsivr~ to the matrix FWm and an input si~nal vector x such that z F~wmx 10 where t represents a l,d"apose operator and a dot product d~t~r",;.~er for forming a dot product such that:
Aj ~ z- cj >
where cj is the ith e~uitdlion cod~t~r.
A cG",b..,er (108) typically a subtractor subtracts each 15 first corrected corresponding sy,ltl,6siLed signal vector from the input ,~fu.~nce vector related thereto that related input ,~t~re,nce vector being a vector from a set of vectors for the input r~f~ri3nGe signal to obtain a c~rl~5s tohd;l~9 reconstruction error vector. The perceptual ~ lllillg unit 20 (110) wei~hts the reconstruction error vectors utilizing the at least first perceptual weighting filter wherein for each selected Si~,J ,d,lilion second corrections of partition pd,d",-aler disc.Gr,linuities are applied su~ldnti& 'y providing corrected reconstruction error vectors, and further 25 d~t~r",-, ,9 CGII~:: t perceptual weighted squared error.
The CGII~ ' ~ perceptual weighted squared error is utilized by the codeboo~ unit to determine an optimal ~x~ildli~n ~odu~l~ctu, from the odebook memory for each input r~,~rence vector. A selector l~aponsh/G to the 3 0 corresponding perceptually weighted squared error is utilized to dt,lt:r", ,e and store an index of a codevector having a perceptually welghted squared error smaller than all other errors produced by other codevectors. Where desired the gain adjuster (104) is uti,ized to multiply the optimal excildli~n ~ 13 21~3785 cod~ ,turs by particular gain factors to substantially provide u5.ste~1 where desired, optimal eA ;ldlion cod~ Lu"
c~r,t,ldl~d with an energy of the ,t,pn.3~nl..~;.u input -,"..ence si~nal such that the selected adjusted, where - 5 desired, optimal ~ACitdliOI) codevectors are signal prùcessed in the at least first s~"Ll,esis unit (106) to substantially produce ~"II,~si~ed signal vectors for reconstructing the input signal.
Typically, every ~ ildti~n cod~ .tur for each input 10 '~ ~nc~ vector is si~nal tj,ucessed to doh.", ~e an optimal eAciL~tion codu-~.ct~, from the ~,odebook memory for each input ~ererence vector.
FlGs. 4 and 4A, numeral 400 and 450, are a flowchart diagram showing the general sequence of steps performed by a di~ital speech coder t,dns",;~l~r that utiiizes the present inventiûn, and a ~ a,l diagram that illustrates a first ~",L- " "~.,l of a fast codebûoi~ search in accurJance with the present invention, l~specti~ly.
The method for substantially reconstructin~ an input signal, typically a speech ._Jufurl", provides that, the signal being pa, lilioned into successive time intervals, each time interval signal partition having a ,~rc,se~ ti,/v input re~e,~nce signal (402) with a set of vectors, and having at least a first l~pr~.~e.,ldlh/~ electrical signal for each rep.esenldliio input ,t,ter~nce signal of each time interval signal partition, the method utilizes at least a ,o~ebook unit having at least a ,odebool~ memory, a gain adjuster where desired, a synthesis unit havin~ at least a first synthesis filter, a combiner, and a perceptual .. i,~l~ling unit having at least a first perceptual 30 ~ lllillg filter, for utilizing the electrical signals of the ,t,tjre~enldlive input reference signals to at least generate a related set of sy"ll,esi~ed signal vectors for substantially reconstructing the signal.
The met~od substantially comprises the steps of:
WO 92/16930 PCI`/US92/01299 2103785. ,, (A) utilizin~ thè at least first represel,ldli~/e electrical si3nal for each ,epr~ nlali:u input ,~"~r~nce signal (402~ for a selected time si~nal partition to obtain a set of l", ,It,r~.Glal~d pdld~ lUr~ for the at least first synthesis filter (404) then 5 (B) utilizing the at least first a~r"ll,esi;, filter to obtain the c~r,~a~,ondi,)~ impulse response ~ep,~selildlion and illl~r~Jolalillg the impulse ,es~conses of each selected adjacent time signal partition and of a current time signal partition i"""ecli~t~ly Ill~,ea~ler to provide a set of inler~,olàled 10 ayllllle~ia filters for desired subpartitions; and utilizing the i"lt,r~oldled a~ l,es;s filters to provide a c~ a~,onding set of ir,tur~,olated perceptual ~.6i~1)1in~ filters for desired s~bpa, liliuns (406). I"lt" ~,olal;~n provides for smooth transitions of the s~"ll,esia filter and the perceptual 15 ..~.i~llli,~g filter between each pair of adjacent partitions are obtained.
Next (C) the set of input ~f~ ce signal vectors the related set of i" ~,ûldled a~"ll,esis filters and the related set of interpolated perceptual ,.~:~ ',li"g filters for the 2 0 current time si~nal partition are utilized to select the c~r,~s~,ori ,9 set of optimal exci~dlion codevectors from the at least first codebooh memory (408) further i"")le",en~ing the following steps for each deâired input ,ufurenGe signal vector (401) :(1) providing a particular e~cildli~n cûd~ lur 25 from the at least first co~ebook ~emory the c~ûdeboo~ memory havin~ a set of eAuild~iûn codevectors stored therein elSpOrl3;J~3 to the reFi,eser,ldli~e input vectors (4û3);
(2) where desired multiplying the particular e~cildlion codevector by a selected excitation gain factor tû
30 substantially provide cG-,~ldlion with an energy of the representative electrical signal for each repr~senldli~e input ,t"erer,ce sisnal vector (405); (3) inputting the particular excitation codevector multiplied by the particular gain into the co"~spon ,g i"~u ~,oldled synth~sis ~ilter ~o p-oduce the WO 92/16930 PCI~/~ rS9~/01299 ~ 15 210~78~
siLdd signal vector (407); (4) subtracting the s~ d si~nal vector from the input f~erence signal vector related thereto to obtain a cor.e_porldi"g reconstruction error vector (409); (5) inputting the 5 reconstruction error vector into the corl~o.por,~
r~Gldted psrceptual ~ unit to ~--l .Ill )e a CGIl~S~ ond;~ perceptually weighted squared error (411);
(6) storing index of codevector havin~ the perceptually weighted squared ~rror smaller than all other errors produced 10 by other cod~ ctul~ (413); (7) repeating the steps (1),(2),(3),(4),(5),and (6) for every ~A~iildli~n codevector in the codebook memory (415) and ;Ill, 'e.llerllil)g these steps utilizing a fast ~d~l,ooh search method, to ddlellll;lle an optimal eAci~ation codevector for the related input reference si~nal 15 vector (410,417); and (D) succes~ ly inputting the set of selected optimal e~cildli~n cod~u~tur~ multiplied by the set of selected gains where desired, into the c~ ,Gr "~ set of illl6r~ 01dl~d :,~,llll~s;s filters (419) to produce the related set of s~llll,esi~ed si~nal vectors (412) for the given input 20 relre~dnce signal for su~lanlially reconstructing the input signal (414).
As set forth above, the method typically utilizes the at least first synthesis filter, SLI,:.Idl.:-'ly at least a first time-varying linear pr~ o coding synthesis filter (LPC-25 SF) where ris typically selected to be suL ,l~l~t;dlly 0.8,gen~ approAilll~llcld by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual ~ g filter.
FIG. 5, nurneral 500, is a flowchart diagram that 30 illustrates a first manner in which an LPC-SF sy,ll~lesis filter and perceptual weighting filter for the m-th subpartition may be illlr !e ~enldd in accordance with the present invention. LPC
~,o~rrici~rll:, of a previous time signal partition {aj(1 )} and of a current time si~nal partition i"""edialdly thereafter {aj(2)}
2103~8~
, are each utilized to ~enerate impulse l~sponses (502, 504) from an LPC-SF, being h(1)(n) . a(n) + ~;a(l)h(1)(n-i) and i.1 h(2)(n) . a(n) + ~;a(2)h(2)(n-i), .~,s~,ect;~,ly where a(n) is an i -1 impulse function and aj(i), for the set i-1,2,...,p and j~1,2, 5 ,t,prusc.~ts a set of quantized pr. li~ cse~i e ,l~ in a previous time partition for j.1 and the current time partition for j.2. h(i)(n) ,~prese,l~a the impulse response of an LPC-SF.
The impulse r~,ponses for the previous time partition input and the current time partition input are i"la",rjldlad to obtain 10 the interpolated impulse response (506), substantiaily, hm(n) - mh(1 )(n) + ~mh(2)(n)~ where ~m ~ rn and o < am c 1. Autocorrelations of hm(n) are d~lt~.l"- ,ed (508) that are then converted to LPC ~o~i e.,la (510), su~ ,)l;z:~y generating, for 15 selected su~&li--~hs, an il,l~l~.Gl._~d LPC-SF having Hm(z)- for j~1,2 and an interpolated 1 - ~a j(i)z-i i.1 perceptual h._htillg filter having Wm(z)- H(z)) wherein y is su~:,ldr,i-'~y 0.8.
FIG. 6 numeral 600 is a flowchart diagram that 20 illustrates a second manner in which an LPC-SF synthesis filter and perceptual ~i~hlillg filter for the m-th subpdrti~ion may be i"" 'e."~r,lad in accor~idnce with the present invention.
LPC coefficients of a previous time signal partition 25 ~a;(1 )) and of a current time signal partition illllll~did~ly II,er~a~l~( {aj(2)} are each utilized to generate, for each desired su~pa, lili~n an illl~r~GIdl~d LPC-SF (602) having 2/ 1 693~ 17 PCr/U592/01 299 Hm(z) - ~mH(1)(z) + ~mH(2)(z), sub~k.n 'l~ bein~ a cu.,~_pon ~ z-transform of the illl~llpOla11,d s~.,1116sis filter (506), and c~ ,ts bein~ as set forth above, and also an ol 1ed, ~ 9 filter (604), havin~ Wm(Z)- Hm(~) 5 c~e~i- 3.~1s being as set forth above. A system i"~ ~."~nLi"~
the method of this invention also may be utilized in acco,Jance with the method des.i,i~ed above.
FIG. 7, ~umeral 700, is a flowchart diagram that illustrates a detailsd fast cod~ol~ search method to 10 dehr., ,e wei~hted squared error in acco(Jance with the present invention. The fast cod~l)oo~ search method substantially further includes utilizin~ a si"" li~ied method to delt~r,-,:.,e the perceptually weighted squared error (724) between an input signal vector (401) and a related ay"11,eai~ed 15 codevector utilizing an i-th e~;t~`;on codu-e~ t~r (708) denoting this error by Ej, such that:
E ~ 2 Ai2 where x ,ep.~se.,ta an input target vector (702) at a selected 2 0 subpartition that is substantially equal to an input re~ nce signal vector at a selected subpartition filtered by a c~r,l,apor..li,~ r~Glaled weighting filter with a zero-input response of a C~llt,apO~ g interpolated weighted LPC-SF
subtracted from it, Aj le~r~se-~1a a dot product of the vector x 25 and an i-th filtered cod~ lur Yi,m at an m-th subpartition (7û6), and Bj l~pltlS~IIla the squared norm of the vector Yi,m (722). A co,-t,a~on~ g ill~ JGI~1~d weighted LPC-SF has a transfer function of Hm(z/y), such that:
Hm(z/~). 1 1 - ~ymajmz~
i ~1 -210378~ .
WO 92/16930 PCI`/US92/01299 where for an m-th suipd,lition, ~is typically selected to be 0.8, and ai m for i-1 2 ...p such that p is a predictor order fe~r~senl the parameters of c~r,~_~or~ "1oldlc,d LPC-SF
the impulse response of H(z/~) hw(n) is sui ala"~idil~
equal to:
hw(n) _ ynhm(n), and where hm(n) is an impulse response of Corl~a~Jorl~ l9 LPC-SF
utilizing a fact that hm(n) is a linear i"~,yGldli~n of the impulse ,e,~i,onses of related previous and current u~, ,ltlr~,~ldled LPC-SFs hwm(n)1 at each i"~r~.olaling subpartition d hr", ,ed in a fast co~ebos~ search as a iinear i"lt,r~oldlion of two impulse , ~sponses of related previous and current ur ,t~".oldled weishted LPC-SFs:
hwm(n) - amhw(1 )(n) ~ i3mhw(2)(n) where hw(i)(n) . ynh(i)(n) for 1 12 are exponentially w~ighted un lltnuGldled impuls~ ~5~uoi ses of the previous when j-1 and the current when j-2 uninterpolated signal partitions and where ~m -1- m and 0 < ~m < 1, where a different m is utilized for each sui pa,lilion.
The fiitered codevector Yi m is delt"",ined as a G~r,.t. lti~n (710) once per signal partition of the i-th e,~Gitdli~n codevector cj with the cG"t,a~.ondii~g weighted impulse response hwm(n)~ the convolution being substantially:
30 Yi m ~ Fwmci~ where Wo 92/16930 2 1 ~ 3 7 8 5 PCI-/~'S92/01299 hWm(O) O O .......... O
hWm(1) hwm(0) 0 .......... 0 hWm(2) hwm(1) hwm() -- O
Fwm - . . . .......... .
. . .
_hWm(k-1) hWm(k-2) hwm(k-3) hwm(0)_ and where k .~.resents a ' "~r,~ivn of a cod~ ,vlur, further utilizing the fact that hwm(n) is a linear i,.l~rpGlaliûn of the impulse ~:",ûnses of related previous and current uninterpolated weighted LPC-SFs, the filtered codv~vc~vr Yi,m at each i~ oldli.,g subpartition may be svv~:.lanli~lly del~-."ined as linear interpolation of two codevectors filtered by the related previous and current v-,:.-le-~,Gl~l~d weighted LPC-SFs:
Yi,m- mYi(1) + ~myj(2~
and where yia) - Fw(i)ci for j-1,2 and where matrices Fw(1) and FW(2) have suLsld.,ti~ ^ a same format as the matrix FWm~ but with difterent elements hw(1)(n) and hw(2)(n), .e~pe-vti,~vly. The squared norm Bj at each inl~".oldli,)g subpartitiûn is substantially a weighted sum (722) ûf a squared norm (716) of a tiltered code~vctvr yj(1)(712), the squared nûrm (72û) of the filtered codevector yj(2)(714), and a dût prûduct (718) of thûse twû filtered cûdevectors, substantially being:
Bj. am2ll yj(1)ll2 + ~m2llyj(2)ll2 +2m~m~yj(1).yj(2)~
2~v where ~m -1- m and 0 < m ~1, where a different m is utilized for each subpartition. Determination of the dot product Aj for each interpolating subpartition substantially cû"",rises two steps:
A) back~ filtering (704) such that z = Ftwmx; and 2103~8~
where t ~ s~r,t~ a lldl~apose operator: and B) formin~ a dot product (706) such that:
Aj - ~ z- cj ~ , where cj is the ith eA~,itdt;~n codu/__tur.
Then Aj, Bj, and x are utilized to ~ -Ill Ie error Ej, such that:substantially:
E j _ llxll2 - Bij (724) .
Backward filtering, dot product d '.r,l. )dlion for Aj, dot producUon d~l~rl,l;nalion for Bj, del~,rll, ,iliùn of two squared 10 norms, obtaining a weighted summation, and delbr,,, ~;l,9 wei~hted squared error are p6,lul,l,ed for every desired interpolatins subpartition.
This novel device, method, and system, typically i,~" !e .,~nltld in a di~ital speech coder, provides for an 15 intur~ol~ d s~llllesia filter for smoothing discontinuities in a~ eai~d reconstructed signals caused by dis~rl~;.,uities at partition boundaries of sampled si3nals. This illlt,l~,oldled s~.lllles;~ filter has two particularly important propei lies: a resultin~ s~ is filter H l(Z) is gu~lld,lleed to be stable as 20 lon~ as the filter H(1)(z) and H(2)(z) are stable; and the resultin~ s~lllll6sis filter is a pole-zero filter that is different from the LPC modelins method based on an all-pole filter. Two rs.,lL- ' Iler~l~, set forth above, provide for reconstruction of an LPC-SF and a perceptual ~.._i~l,li,~g filt~r 25 from the il~tbr~JGldl~ impulse response. The first 6l,1bo~' llent, utilizing the pole-zero synthesis filter obtained from interpolating the impulse respon~es of two all-pole synthesis filters for adjacent time partitions generates an interpolated synthesis filter, and necessilates 3 0 updating/interpolating of the perceptual weightin~ filter (604). The interpolated ~ hlill~ filter t604) is not necessalily stable, requirin~ a stability check for each set of illlbr~,olaled cobr~k,;~rll~. Where instability is detected for a 2I~37~5 particular subpartition, ul,inlt,r~,olated co~rri ~.lt~ are used for that subpd, lilion .
- To avoid the instability check ~Csoc lpd with utilizing the pole-zero s~.,ll,esi, filter, a second e."bo~i",ei~l utilizes 5 an all-pole sy.,lll~sis filter to ap~ru~i",ald the pole-zero filter of the first ~",b~di",e,nl. In the second e",L~ "enl, the first p + 1 a~lucor,-' ~n coefficients of the i"l~r~.ol~led impulse response for a suLpd,t;~iùn are ~ , ~, then converted to direct form prediction coerfici~r,ls, typically utilizin~ the 1 û Levinson recursion al~orithm. The resulting prediction coe~ric;ehl~ ar~ utilized in a LPC-SF and a perceptual I.Ii.,g filter for the su~pd.lilion. Thus, the required number of computations required to generate the first p+1 autocorrelation coerric;~r,la from the impulse responses per 15 partition is sul, .lani -'~y of the order of 3(p+1)L + 4(p~-1)Njtp, where L is a length of a truncated/~sli--,al~d impulse response and Njtp is substantially a number of suL,parlili~ns where ir,~r~Glation is p~-ror",dd. An illlp~lldl~l aJvd-,l~e of the second ~., L "enl 2û is that to delt7r-, le the autocorrelation coerr. rll~ of the lal~d impulse response, there is no necessil~ to linearly interpolate an entire truncated impulse response sequence.
Computer simulations were utilized to compare the 25 pe(Fu""ance of the method of this invention with two other LPC interpolation methods using direct form ~r. ~: n c~.,r o ,1~ and PARCOR co~r~i hl~, r~s?e~;t;~ly, as i"l~"u~lalion pard"~ ra. A speech codr~r utilizin3 this invention was configured at bit-rates of 4800 and 8000 bit per 3û second (bps) r~s~,eclii~ly. At 8000 bps, almost identical pel~ur",ance, both subjectively and objectively, was obtained when using the direct form prediction coefficients and when usin~ impulse response for inlt"~J~laliûn. However, at 4800 bps, the coder utilizing this invention outperforms the other WO 92/16930 PCI`/US92/01299 210378~ 22 , two il~tv~GlaliOi~ methods. Therefore, the method of this invention not only offers a s;~ ic,alll computational ad~. ~ld~6 over other typical i~ ,Gl~ methods, but also improves speech quality.
Further, when the impulse response of the LPC-SF is utilized, a codevector filtered by the i"~ ldt~d s~"ll,esis filter is simply equal to the linear intv. ,.,oldlion of the two cod~lvcturs filtered by the previous and current ~nillte,r~Joldt~d s~ llesis filters allowing a fast codeboo~.
search. The second ~ l of LPC i" ~Gl~t;~n methods thus provides a fast ~)~ebook search nnethod, as is illustrated below. Where p, K, N, and Ns are used to represent the LPC
predictor order, vector length, e~ -n codeboo4 size, and number of subpartitions per partition, ~a~e~ ly, the following table gives a c~""parison of co-Jebook search cv"~ of usin~ the fast cod~book search method and a conventional al~orill,l".
TASK COMPI FXITY (OPFRATION.~/PARTITION) Conver~jon~l F~Ct Codebook S~ch Filtering codG,/~--to,a pkNNs pKN
Computin~
ener~ies KNNs 2KN + 3N(Ns-1) Computing dot products KNNs KNNs + ( 2 )(Ns-1 ) Total (p+2)KNNs (p+2+Ns)KN +3N(Ns-1) + 2 (NS-~) WO 92/16930 23 PCI`/1'592/01299 21~785 For example, where p, K, N, and Ns equal 10, 40 1024 and 4",_p~ ly (with a partition size of 160 samples and a sampling frequency of 8 kHz), a total of major computations for a cc"J_.,Iional co~ebook search is of the order of 98.3 MIPS
5 (Million Instructions Per Second), but only on the order of 33.3 MIPS for a fast cod~ oh search, yielding sul,~Id"lially a 66 percent co", ' ~y reduction. When cc",b:.,ed with other efficient coding schemes, the method and hardware i", '~ "rritdli~n of the present invention provide for 10 substantial reduction in computational cost for CELP-type coders, provide improved speech coder performance, and maintain a l~asonably low encoding co""' ~y.
Thus, the second e",L- "e,r,l is a preferred e"l~o~i",t",l since less computation is required, odeboo~ sear~;l, ,9 c~", ' ~y is 15 ",;";",iLed, and partition boundary sampling discontinuities are ,",G~ltl-ed, thereby providin~ improved :.~"II,e~i~ed si~nal vectors for reconstructing input signals.
I claim:
Claims (8)
1. A method for substantially reconstructing a signal, the signal being partitioned into successive time intervals, each time interval signal partition having a representative input reference signal with a set of vectors, and having at least a first representative electrical signal for each representative input reference signal of each time interval signal partition, the method utilizing at least a codebook unit having at least a codebook memory, a gain adjuster where desired, a synthesis unit having at least a first synthesis filter, a combiner, and a perceptual weighting unit having at least a first perceptual weighting filter, for utilizing the electrical signals of the representative input reference signals to at least generate a related set of synthesized signal vectors for substantially reconstructing the signal, the method comprising the steps of:
(A) utilizing the at least first representative electrical signal for each representative input reference signal for a selected time signal partition to obtain a set of uninterpolated parameters for the at least first synthesis filter;
(B) utilizing the at least first synthesis filter to obtain the corresponding impulse response representation, and interpolating the impulse responses of each selected adjacent time signal partition and of a current time signal partition immediately thereafter to provide a set of interpolated synthesis filters for desired subpartitions; and utilizing the interpolated synthesis filters to provide a corresponding set of interpolated perceptual weighting filters for desired subpartitions; such that smooth transitions of the synthesis filter and the perceptual weighting filter between each pair of adjacent partitions are obtained;
(C) utilizing the set of input reference signal vectors, the related set of interpolated synthesis filters and the related set of interpolated perceptual weighting filters for the current time signal partition to select the corresponding set of optimal excitation codevectors from the at least first codebook memory, further implementing the following steps for each desired input reference signal vector:
(1) providing a particular excitation codevector from the at least first codebook memory, the codebook memory having a set of excitation codevectors stored therein responsive to the representative input vectors;
(2) where desired, multiplying the particular excitation codevector by a selected excitation gain factor to substantially provide correlation with an energy of the representative electrical signal for each representative input reference signal vector;
(3) inputting the particular excitation codevector multiplied by the particular gain into the corresponding interpolated synthesis filter to produce the synthesized signal vector;
(4) subtracting the synthesized signal vector from the input reference signal vector related thereto to obtain a corresponding reconstruction error vector;
(5) inputting the reconstruction error vector into the corresponding interpolated perceptual weighting unit to determine a corresponding perceptually weighted squared error;
(6) storing index of codevector having the perceptually weighted squared error smaller than all other errors produced by other codevectors;
(7) repeating the steps (1),(2),(3),(4),(5),and (6) for every excitation codevector in the codebook memory and implementing these steps utilizing a fast codebook search method, to determine an optimal excitation codevector for the related input reference signal vector; and (D) successively inputting the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, into the corresponding set of interpolated synthesis filters to produce the related set of synthesized signal vectors for the given input reference signal for substantially reconstructing the input signal.
(A) utilizing the at least first representative electrical signal for each representative input reference signal for a selected time signal partition to obtain a set of uninterpolated parameters for the at least first synthesis filter;
(B) utilizing the at least first synthesis filter to obtain the corresponding impulse response representation, and interpolating the impulse responses of each selected adjacent time signal partition and of a current time signal partition immediately thereafter to provide a set of interpolated synthesis filters for desired subpartitions; and utilizing the interpolated synthesis filters to provide a corresponding set of interpolated perceptual weighting filters for desired subpartitions; such that smooth transitions of the synthesis filter and the perceptual weighting filter between each pair of adjacent partitions are obtained;
(C) utilizing the set of input reference signal vectors, the related set of interpolated synthesis filters and the related set of interpolated perceptual weighting filters for the current time signal partition to select the corresponding set of optimal excitation codevectors from the at least first codebook memory, further implementing the following steps for each desired input reference signal vector:
(1) providing a particular excitation codevector from the at least first codebook memory, the codebook memory having a set of excitation codevectors stored therein responsive to the representative input vectors;
(2) where desired, multiplying the particular excitation codevector by a selected excitation gain factor to substantially provide correlation with an energy of the representative electrical signal for each representative input reference signal vector;
(3) inputting the particular excitation codevector multiplied by the particular gain into the corresponding interpolated synthesis filter to produce the synthesized signal vector;
(4) subtracting the synthesized signal vector from the input reference signal vector related thereto to obtain a corresponding reconstruction error vector;
(5) inputting the reconstruction error vector into the corresponding interpolated perceptual weighting unit to determine a corresponding perceptually weighted squared error;
(6) storing index of codevector having the perceptually weighted squared error smaller than all other errors produced by other codevectors;
(7) repeating the steps (1),(2),(3),(4),(5),and (6) for every excitation codevector in the codebook memory and implementing these steps utilizing a fast codebook search method, to determine an optimal excitation codevector for the related input reference signal vector; and (D) successively inputting the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, into the corresponding set of interpolated synthesis filters to produce the related set of synthesized signal vectors for the given input reference signal for substantially reconstructing the input signal.
2. The method of claim 1, wherein at least one of:
(a) the signal is a speech waveform; and (b) the at least first synthesis filter substantially is at least a first time-varying linear predictive coding synthesis filter (LPC-SF) having a transfer function substantially of a form:
, where ai's for i=1,2,...,p represent a set of estimated prediction coefficients obtained by analyzing the corresponding time signal partition and p represents a predictor order.
(a) the signal is a speech waveform; and (b) the at least first synthesis filter substantially is at least a first time-varying linear predictive coding synthesis filter (LPC-SF) having a transfer function substantially of a form:
, where ai's for i=1,2,...,p represent a set of estimated prediction coefficients obtained by analyzing the corresponding time signal partition and p represents a predictor order.
3. The method of claim 1, wherein at least one of:
(a) the LPC-SFs of a selected adjacent time signal partition and of a time partition immediately thereafter are substantially of a form:
, where ai(j)'s, for i = 1, 2, 3, ..., p and j = 1,2 represent a set of prediction coefficients in a selected adjacent time signal partition when j = 1 and of a current time signal partition immediately thereafter when j=2, respectively, p represents a predictor order such that an impulse response for the transfer function H(j)(z) is substantially p h(j)(n) = ?(n) + .SIGMA.ai(j)h(j)(n-i) , i=1 where ?(n) is an impulse function, and such that the impulse response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear interpolation of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) = .alpha.mh(1)(n) + .beta.mh(2)(n) , where .beta.m = 1 - .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m isutilized for each subpartition, thereby providing a transfer function of the interpolated synthesis filter substantially of a form:
Hm(z) = .alpha.mH(1)(z) + .beta.mH(2)(z) = , where A'm(z) = 1 p and A(j)(z) = 1 - .SIGMA.ai(j)z-i for j = 1,2, i=1 wherein the perceptual weighting filter at the m-th subpartition of a current time interval signal partition substantially has a transfer function of the form:
Wm(z) = , where .gamma. is typically selected to be substantially 0.8;
(b) the synthesis filter is approximated by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual weigthing filter, wherein the all pole synthesis filter parameters are obtained substantially utilizing the steps of:
estimating a first p+1 autocorrelation coefficients using selected truncated interpolated impulse response samples; and converting the autocorrelation coefficients to direct form prediction coefficients using a recursion algorithm; and (c) the estimated autocorrelation coefficients at the m-th subpartition can be expressed as: ?m(k) = ?hm(n)hm(n+k) for k = 0,1, ..., p and the summation is over all available partition impulse responses, such that ?m(k) = .alpha.m?(1)(k) + .beta.m?(2)(k) + .alpha.m.beta.m(?(12)(k) + ?(21)(k)) where ?(j)(k) = ?h(j)(n)h(j)(n+k) for k = 0,1, ..., p and j=1,2, are autocorrelation coefficients of uninterpolated impulse response of the adjacent and current partitions, and ?(ij)(k) = ?h(i)(n)h(j)(n+k) for k=0,1,...,p and i,j=1,2 where i?j, are cross-correlation coefficients between the uninterpolated impulse responses.
(a) the LPC-SFs of a selected adjacent time signal partition and of a time partition immediately thereafter are substantially of a form:
, where ai(j)'s, for i = 1, 2, 3, ..., p and j = 1,2 represent a set of prediction coefficients in a selected adjacent time signal partition when j = 1 and of a current time signal partition immediately thereafter when j=2, respectively, p represents a predictor order such that an impulse response for the transfer function H(j)(z) is substantially p h(j)(n) = ?(n) + .SIGMA.ai(j)h(j)(n-i) , i=1 where ?(n) is an impulse function, and such that the impulse response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear interpolation of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) = .alpha.mh(1)(n) + .beta.mh(2)(n) , where .beta.m = 1 - .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m isutilized for each subpartition, thereby providing a transfer function of the interpolated synthesis filter substantially of a form:
Hm(z) = .alpha.mH(1)(z) + .beta.mH(2)(z) = , where A'm(z) = 1 p and A(j)(z) = 1 - .SIGMA.ai(j)z-i for j = 1,2, i=1 wherein the perceptual weighting filter at the m-th subpartition of a current time interval signal partition substantially has a transfer function of the form:
Wm(z) = , where .gamma. is typically selected to be substantially 0.8;
(b) the synthesis filter is approximated by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual weigthing filter, wherein the all pole synthesis filter parameters are obtained substantially utilizing the steps of:
estimating a first p+1 autocorrelation coefficients using selected truncated interpolated impulse response samples; and converting the autocorrelation coefficients to direct form prediction coefficients using a recursion algorithm; and (c) the estimated autocorrelation coefficients at the m-th subpartition can be expressed as: ?m(k) = ?hm(n)hm(n+k) for k = 0,1, ..., p and the summation is over all available partition impulse responses, such that ?m(k) = .alpha.m?(1)(k) + .beta.m?(2)(k) + .alpha.m.beta.m(?(12)(k) + ?(21)(k)) where ?(j)(k) = ?h(j)(n)h(j)(n+k) for k = 0,1, ..., p and j=1,2, are autocorrelation coefficients of uninterpolated impulse response of the adjacent and current partitions, and ?(ij)(k) = ?h(i)(n)h(j)(n+k) for k=0,1,...,p and i,j=1,2 where i?j, are cross-correlation coefficients between the uninterpolated impulse responses.
4. The method of claim 1, wherein at least one of:
(a) the synthesis unit further includes a pitch synthesis unit the pitch synthesis unit including at least a pitch analyzer and a time-varying pitch synthesis filter having a transfer function substantially of a form:
-----B(Z) = 1-.beta.z-T , where T represents an estimated pitch lag and .beta. represents gain of the pitch predictor;
(b) the excitation code vectors are stored in memory;
(c) the perceptual weighting unit includes at least a first perceptual weighting filter having a transfer function substantially of a form:
H(z/.gamma.) -----W(z) = H(z) , where .gamma. is typically selected to be substantially 0.8;
(d) determining an optimal excitation codevector from the codebook memory for each input reference vector includes signal processing every excitation codevector in the codebook memory for each input reference vector, then determining the optimal excitation codevector of those codevectors processed;
and (e) the fast codebook search method substantially further includes utilizing a simplified method to obtain the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ei, such that:
Ai2 ---Ei = ¦¦x¦¦2 - Bi where x represents an input target vector at a selected subpartition that is substantially equal to an input reference signal vector at a selected subpartition filtered by a corresponding interpolated weighting filter with a zero-input response of a corresponding interpolated weighted LPC-SF
subtracted from it, Ai represents a dot product of the vector x and an i-th filtered codevector yi,m at an m-th subpartition, and Bi represents the squared norm of the vector .gamma.i,m, and wherein 4 (e) further includes at least one of:
(1) the corresponding interpolated weighted LPC-SF has a transfer function of Hm(z/.gamma.), such that:
, where for an m-th subpartition, .gamma. is typically selected to be 0.8, and ai,m ,for i=1,2,...p, such that p is a predictor order, represent the parameters of corresponding interpolated LPC-SF, the impulse response of Hm(z/.gamma.), hwm(n), is substantially equal to:
hwm(n) = .gamma.nhm(n), and where hm(n) is an impulse response of corresponding LPC-SF, utilizing a fact that hm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n), at each interpolating subpartition, determined in a fast codebook search as a linear interpolation of two impulse responses of related previous and current uninterpolated weighted LPC-SFs:
hwm(n) = .alpha.mhw(1)(n) + .beta.mhw(2)(n), where hw(j)(n) = .gamma.nh(j)(n) for j=1,2 are exponentially weighted uninterpolated impulse responses of the previous, when j=1, and the current, when j=2, LPC synthesis filters, and where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition;
(2) the filtered codevector yi,m is determined as a convolution of the i-th excitation codvector ci with the corresponding weighted impulse response hwm(n), the convolution being substantially:
yi,m = Fwmci, where Fwm =
and where k represent a dimension of a codevector, further utilizing the fact that hwm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector yi,m at each interpolating subpartition may be substantially determined as linear interpolation of two codevectors filtered by the related previous and current uninterpolated weighted LPC-SFs:
yi,m = .alpha.myi(1) + .beta.myi(2), and where yj(j) = Fw(j)ci for j=1,2 and where matrices Fw(1) and Fw(2) have substantially a same format as the matrix Fwm, but with different elements hw(1)(n) and hw(2)(n), respectively;
(3) the squared norm Bi at each interpolating subpartition is substantially a weighted sum of a squared norm of a filtered codevector yi(1), the squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, substantially being:
Bi = .alpha.m¦¦ yi(1)¦¦ + .beta.m¦¦ yi(2)¦¦+2.alpha.m.beta.m<yi(1).yi(2)>, where .beta.m = 1 - .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition; and (4) determination of the dot product Ai for each interpolating subpartition substantially comprises two steps:
A) backward filtering such that z = Ftwmx; and where t represents a transpose operator; and B) forming a dot product such that:
Ai = < z. ci > , where ci is the ith excitation codevector.
(a) the synthesis unit further includes a pitch synthesis unit the pitch synthesis unit including at least a pitch analyzer and a time-varying pitch synthesis filter having a transfer function substantially of a form:
-----B(Z) = 1-.beta.z-T , where T represents an estimated pitch lag and .beta. represents gain of the pitch predictor;
(b) the excitation code vectors are stored in memory;
(c) the perceptual weighting unit includes at least a first perceptual weighting filter having a transfer function substantially of a form:
H(z/.gamma.) -----W(z) = H(z) , where .gamma. is typically selected to be substantially 0.8;
(d) determining an optimal excitation codevector from the codebook memory for each input reference vector includes signal processing every excitation codevector in the codebook memory for each input reference vector, then determining the optimal excitation codevector of those codevectors processed;
and (e) the fast codebook search method substantially further includes utilizing a simplified method to obtain the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ei, such that:
Ai2 ---Ei = ¦¦x¦¦2 - Bi where x represents an input target vector at a selected subpartition that is substantially equal to an input reference signal vector at a selected subpartition filtered by a corresponding interpolated weighting filter with a zero-input response of a corresponding interpolated weighted LPC-SF
subtracted from it, Ai represents a dot product of the vector x and an i-th filtered codevector yi,m at an m-th subpartition, and Bi represents the squared norm of the vector .gamma.i,m, and wherein 4 (e) further includes at least one of:
(1) the corresponding interpolated weighted LPC-SF has a transfer function of Hm(z/.gamma.), such that:
, where for an m-th subpartition, .gamma. is typically selected to be 0.8, and ai,m ,for i=1,2,...p, such that p is a predictor order, represent the parameters of corresponding interpolated LPC-SF, the impulse response of Hm(z/.gamma.), hwm(n), is substantially equal to:
hwm(n) = .gamma.nhm(n), and where hm(n) is an impulse response of corresponding LPC-SF, utilizing a fact that hm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n), at each interpolating subpartition, determined in a fast codebook search as a linear interpolation of two impulse responses of related previous and current uninterpolated weighted LPC-SFs:
hwm(n) = .alpha.mhw(1)(n) + .beta.mhw(2)(n), where hw(j)(n) = .gamma.nh(j)(n) for j=1,2 are exponentially weighted uninterpolated impulse responses of the previous, when j=1, and the current, when j=2, LPC synthesis filters, and where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition;
(2) the filtered codevector yi,m is determined as a convolution of the i-th excitation codvector ci with the corresponding weighted impulse response hwm(n), the convolution being substantially:
yi,m = Fwmci, where Fwm =
and where k represent a dimension of a codevector, further utilizing the fact that hwm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector yi,m at each interpolating subpartition may be substantially determined as linear interpolation of two codevectors filtered by the related previous and current uninterpolated weighted LPC-SFs:
yi,m = .alpha.myi(1) + .beta.myi(2), and where yj(j) = Fw(j)ci for j=1,2 and where matrices Fw(1) and Fw(2) have substantially a same format as the matrix Fwm, but with different elements hw(1)(n) and hw(2)(n), respectively;
(3) the squared norm Bi at each interpolating subpartition is substantially a weighted sum of a squared norm of a filtered codevector yi(1), the squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, substantially being:
Bi = .alpha.m¦¦ yi(1)¦¦ + .beta.m¦¦ yi(2)¦¦+2.alpha.m.beta.m<yi(1).yi(2)>, where .beta.m = 1 - .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition; and (4) determination of the dot product Ai for each interpolating subpartition substantially comprises two steps:
A) backward filtering such that z = Ftwmx; and where t represents a transpose operator; and B) forming a dot product such that:
Ai = < z. ci > , where ci is the ith excitation codevector.
5. A device for substantially reconstructing a signal, the signal being partitioned into successive time intervals each time interval signal partition having a representative input reference signal with a set of vectors, and having at least a first representative electrical signal for each representative input reference signal of each time interval signal partition for utilizing the electrical signals of the representative input reference signals to at least generate a related set of synthesized signal vectors for substantially reconstructing the signal, the device comprising at least:
(A) a first synthesis unit responsive to the at least first representative electrical signal for each representative input reference signal, for utilizing the at least first representative electrical signal for each representative input reference signal for a selected time signal partition to obtain a set of uninterpolated parameters for the at least first synthesis filter and the impulse response of this synthesis filter, and for interpolating the impulse responses of each selected adjacent time signal partition and of a current time signal partition immediately thereafter to provide a set of interpolated synthesis filters for desired subpartitions; and utilizing the interpolated synthesis filters to provide a corresponding set of interpolated perceptual weighting filters to at least a first perceptual weighting unit for desired subpartitions such that the at least first perceptual weighting unit provides at least a first perceptually weighted squared error and such that smooth transitions of the synthesis filter and the perceptual weighting filter between each pair of adjacent partitions are obtained;
(B) a codebook unit, responsive to the set of input reference signal vectors the related set of interpolated synthesis filters and the related set of interpolated perceptual weighting filters for the current time signal partition, for selecting the corresponding set of optimal excitation codevectors from the at least first codebook memory for each desired input reference signal vector, further comprising at least:
(1) a codebook memory, for providing a particular excitation codevector from the at least first codebook memory, the codebook memory having a set of excitation codevectors stored therein responsive to the representative input vectors;
(2) a gain adjuster, responsive to the particular excitation codevector, for, where desired, multiplying the particular excitation codevector by a selected excitation gain factor to substantially provide correlation with an energy of the representative electrical signal for each representative input reference signal vector;
(3) an interpolated synthesis filter having a transfer function, responsive to the particular excitation codevector multiplied by the particular gain for producing a synthesized signal vector;
(4) a combiner, responsive to the synthesized signal vector and to the input reference signal vector related thereto, for subtracting the synthesized signal vector from the input reference signal vector related thereto to obtain a corresponding reconstruction error vector;
(5) an interpolated perceptual weighting unit, responsive to the corresponding reconstruction error vector and to the interpolated synthesis filter transfer function, for determining a corresponding perceptually weighted squared error;
(6) a selector, responsive to the corresponding perceptually weighted squared error for determining and storing an index of a codevector having the perceptually weighted squared error smaller than all other errors produced by other codevectors;
(7) repetition means, responsive to the number of excitation codevectors in the codebook memory, for repeating the steps (1),(2),(3),(4),(5),and (6) for every excitation codevector in the codebook memory and for implementing these steps utilizing a fast codebook search method, to determine an optimal excitation codevector for the related input reference signal vector; and (C) codebook unit control means, responsive to the the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, for successively inputting the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, into the corresponding set of interpolated synthesis filters to produce the related set of synthesized signal vectors for the given input reference signal for substantially reconstructing the input signal.
(A) a first synthesis unit responsive to the at least first representative electrical signal for each representative input reference signal, for utilizing the at least first representative electrical signal for each representative input reference signal for a selected time signal partition to obtain a set of uninterpolated parameters for the at least first synthesis filter and the impulse response of this synthesis filter, and for interpolating the impulse responses of each selected adjacent time signal partition and of a current time signal partition immediately thereafter to provide a set of interpolated synthesis filters for desired subpartitions; and utilizing the interpolated synthesis filters to provide a corresponding set of interpolated perceptual weighting filters to at least a first perceptual weighting unit for desired subpartitions such that the at least first perceptual weighting unit provides at least a first perceptually weighted squared error and such that smooth transitions of the synthesis filter and the perceptual weighting filter between each pair of adjacent partitions are obtained;
(B) a codebook unit, responsive to the set of input reference signal vectors the related set of interpolated synthesis filters and the related set of interpolated perceptual weighting filters for the current time signal partition, for selecting the corresponding set of optimal excitation codevectors from the at least first codebook memory for each desired input reference signal vector, further comprising at least:
(1) a codebook memory, for providing a particular excitation codevector from the at least first codebook memory, the codebook memory having a set of excitation codevectors stored therein responsive to the representative input vectors;
(2) a gain adjuster, responsive to the particular excitation codevector, for, where desired, multiplying the particular excitation codevector by a selected excitation gain factor to substantially provide correlation with an energy of the representative electrical signal for each representative input reference signal vector;
(3) an interpolated synthesis filter having a transfer function, responsive to the particular excitation codevector multiplied by the particular gain for producing a synthesized signal vector;
(4) a combiner, responsive to the synthesized signal vector and to the input reference signal vector related thereto, for subtracting the synthesized signal vector from the input reference signal vector related thereto to obtain a corresponding reconstruction error vector;
(5) an interpolated perceptual weighting unit, responsive to the corresponding reconstruction error vector and to the interpolated synthesis filter transfer function, for determining a corresponding perceptually weighted squared error;
(6) a selector, responsive to the corresponding perceptually weighted squared error for determining and storing an index of a codevector having the perceptually weighted squared error smaller than all other errors produced by other codevectors;
(7) repetition means, responsive to the number of excitation codevectors in the codebook memory, for repeating the steps (1),(2),(3),(4),(5),and (6) for every excitation codevector in the codebook memory and for implementing these steps utilizing a fast codebook search method, to determine an optimal excitation codevector for the related input reference signal vector; and (C) codebook unit control means, responsive to the the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, for successively inputting the set of selected optimal excitation codevectors multiplied by the set of selected gains where desired, into the corresponding set of interpolated synthesis filters to produce the related set of synthesized signal vectors for the given input reference signal for substantially reconstructing the input signal.
6. The device of claim 5, wherein at least one of:
(a) the signal is a speech waveform; and (b) the at least first synthesis filter substantially is at least a first time-varying linear predictive coding synthesis filter (LPC-SF) having a transfer function substantially of a form:
, where ai's, for i=1,2,...,p represent a set of estimated prediction coefficients obtained by analyzing the corresponding time signal partition and p represents a predictor order.
(a) the signal is a speech waveform; and (b) the at least first synthesis filter substantially is at least a first time-varying linear predictive coding synthesis filter (LPC-SF) having a transfer function substantially of a form:
, where ai's, for i=1,2,...,p represent a set of estimated prediction coefficients obtained by analyzing the corresponding time signal partition and p represents a predictor order.
7. The device of claim 5, wherein at least one of:
(a) the LPC-SFs of a selected adjacent time signal partition and of a time partition immediately thereafter are substantially of a form:
H(j)(z) =
, where ai(j)'s, for i = 1, 2, 3, ..., p and j = 1, 2 represent a set of prediction coefficients in a selected adjacent time signal partition when j = 1 and of a current time signal partition immediately thereafter when j=2, respectively, p represents a predictor order such that an impulse response for the transfer function H(j)(z) is substantially p h(j)(n) = ?(n) + .SIGMA.ai(j)h(j)(n-i) , i=1 where ?(n) is an impulse function, and such that the impulse response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear interpolation of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) = .alpha.mh(1)(n) + .beta.mh(2)(n), where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition, thereby providing a transfer function of the interpolated synthesis filter substantially of a form:
Hm(z) = .alpha.mH(1)(z) + .beta.mH(2)(z) = , p where A'm(z) = 1 - .SIGMA.(.beta.mai(1) + .alpha.mai(2))z-i i=1 p and A(j)(z) = 1 - .SIGMA.ai(j)z-i for j = 1,2, i=1 wherein the perceptual weighting filter at the m-th subpartition of a current time interval signal partition substantially has a transfer function of the form:
Wm(z) = , where .gamma. is typically selected to be substantially 0.8;
(b) wherein the synthesis filter is approximated by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual weighting filter, wherein the all pole synthesis filter parameters are obtained substantially utilizing at least:
estimating means, responsive to selected interpolated impulse response samples, for estimating a first p+1 autocorrelation coefficients using selected truncated interpolated impulse response samples; and converting means, responsive to the estimated autocorrelation coefficients, for converting the autocorrelation coefficients to direct form prediction coefficients using a recursion algorithm; and (c) the estimated autocorrelation coefficients at the m-th subpartition can be expressed as: ?m(k) = .SIGMA.hm(n)hm(n+k) n for k = 0,1, ..., p and the summation is over all available partition impulse responses, such that ?m(k) = .alpha.m2?(1)(k) + .beta.m2?(2)(k) + .alpha.m.beta.m(?(12)(k) + ?(21)(k)) where ?(j)(k) = .SIGMA.h(j)(n)h(j)(n+k) for k = 0,1, ..., p and j=1,2, n are autocorrelation coefficients of uninterpolated impulse response of the adjacent and current partitions, and ?(ij)(k) = .SIGMA.h(i)(n)h(i)(n+k) for k = 0,1,...,p and i,j=1,2 where i?j, are cross-correlation coefficients between the uninterpolated impulse responses.
(a) the LPC-SFs of a selected adjacent time signal partition and of a time partition immediately thereafter are substantially of a form:
H(j)(z) =
, where ai(j)'s, for i = 1, 2, 3, ..., p and j = 1, 2 represent a set of prediction coefficients in a selected adjacent time signal partition when j = 1 and of a current time signal partition immediately thereafter when j=2, respectively, p represents a predictor order such that an impulse response for the transfer function H(j)(z) is substantially p h(j)(n) = ?(n) + .SIGMA.ai(j)h(j)(n-i) , i=1 where ?(n) is an impulse function, and such that the impulse response of the at least first synthesis filter at an m-th subpartition of a current time partition obtained through linear interpolation of h(1)(n) and h(2)(n) respectively, denoted below as hm(n), is substantially:
hm(n) = .alpha.mh(1)(n) + .beta.mh(2)(n), where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition, thereby providing a transfer function of the interpolated synthesis filter substantially of a form:
Hm(z) = .alpha.mH(1)(z) + .beta.mH(2)(z) = , p where A'm(z) = 1 - .SIGMA.(.beta.mai(1) + .alpha.mai(2))z-i i=1 p and A(j)(z) = 1 - .SIGMA.ai(j)z-i for j = 1,2, i=1 wherein the perceptual weighting filter at the m-th subpartition of a current time interval signal partition substantially has a transfer function of the form:
Wm(z) = , where .gamma. is typically selected to be substantially 0.8;
(b) wherein the synthesis filter is approximated by an all pole synthesis filter that is utilized to provide parameters for interpolating subpartitions in the LPC-SF filter and in the perceptual weighting filter, wherein the all pole synthesis filter parameters are obtained substantially utilizing at least:
estimating means, responsive to selected interpolated impulse response samples, for estimating a first p+1 autocorrelation coefficients using selected truncated interpolated impulse response samples; and converting means, responsive to the estimated autocorrelation coefficients, for converting the autocorrelation coefficients to direct form prediction coefficients using a recursion algorithm; and (c) the estimated autocorrelation coefficients at the m-th subpartition can be expressed as: ?m(k) = .SIGMA.hm(n)hm(n+k) n for k = 0,1, ..., p and the summation is over all available partition impulse responses, such that ?m(k) = .alpha.m2?(1)(k) + .beta.m2?(2)(k) + .alpha.m.beta.m(?(12)(k) + ?(21)(k)) where ?(j)(k) = .SIGMA.h(j)(n)h(j)(n+k) for k = 0,1, ..., p and j=1,2, n are autocorrelation coefficients of uninterpolated impulse response of the adjacent and current partitions, and ?(ij)(k) = .SIGMA.h(i)(n)h(i)(n+k) for k = 0,1,...,p and i,j=1,2 where i?j, are cross-correlation coefficients between the uninterpolated impulse responses.
8. The device of claim 5, wherein at least one of:
(a) the synthesis unit further includes a pitch synthesis unit, the pitch synthesis unit including at least a pitch analyzer and a time-varying pitch synthesis filter having a transfer function substantially of a form:
, where T represents an estimated pitch lag and .beta. represents gain of the pitch predictor;
(b) the excitation code vectors are stored in memory;
(c) the perceptual weighting unit includes at least a first perceptual weighting filter having a transfer function substantially of a form:
W(z) = , where .gamma. is typically selected to be substantially 0.8;
(d) determining an optimal excitation codevector from the codebook memory for each input reference vector includes signal processing every excitation codevector in the codebook memory for each input reference vector, then determining the optimal excitation codevector of those codevectors processed;
and (e) the fast codebook search device substantially further includes utilizing a simplified method to obtain the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ei, such that:
, where x represents an input target vector at a selected subpartition that is substantially equal to an input reference signal vector at a selected subpartition filtered by a corresponding interpolated weighting filter with a zero-input response of a corresponding interpolated weighted LPC-SF
subtracted from it, Ai represents a dot product of the vector x and an i-th filtered codevector yi,m at an m-th subpartition, and Bi represents the squared norm of the vector yi,m, and wherein 8 (e) further includes at least one of:
(1) the corresponding interpolated weighted LPC-SF has a transfer function of Hm(z/.gamma.), such that:
, where for an m-th subpartition, .gamma. is typically selected to be 0.8, and ai,m ,for i=1,2,...p, such that p is a predictor order, represent the parameters of corresponding interpolated LPC-SF, the impulse response of Hm(z/.gamma.), hwm(n), is substantially equal to:
hwm(n) = .gamma.nhm(n), and where hm(n) is an impulse response of corresponding LPC-SF, utilizing a fact that hm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n), at each interpolating subpartition, determined in a fast codebook search as a linear interpolation of two impulse responses of related previous and current uninterpolated weighted LPC-SFs:
hwm(n) - .alpha.mhw(1)(n) + .beta.mhw(2)(n) , where hw(j)(n) = .gamma.nh(i)(n) for j=1,2 are exponentially weighted uninterpolated impulse responses of the previous, when j=1, and the current, when j=2, LPC synthesis filters, and where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition;
(2) the filtered codevector yi,m is determined as a convolution of the i-th excitation codevector ci with the corresponding weighted impulse response hwm(n), the convolution being substantially:
yi,m = Fwmci, where Fwm =
and where k represents a dimension of a codevector, further utilizing the fact that hwm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector yi,m at each interpolating subpartition may be substantially determined as linear interpolation of two codevectors filtered by the related previous and current uninterpolated weighted LPC-SFs:
yi,m = .alpha.myi(1) + .beta.myi(2) , and where yi(j) = Fw(j)ci for j=1,2 and where matrices Fw(1) and Fw(2) have substantially a same format as the matrix Fwm, but with different elements hw(1)(n) and hw(2)(n) , respectively;
(3) further including a second determiner, responsive to the squared norm of a filtered codevector yi(1), the squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, for determining the squared norm Bi at each interpolating subpartition, substantially a weighted sum of a squared norm of a filtered codevector yi(1), a squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, substantially being:
Bi = .alpha.m2¦¦ yi(1)¦¦2 + .beta.m2¦¦ yi(2)¦¦2+2.alpha.m.beta.m<yi(1).yi(2)>, where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m isutilized for each subpartition; and (4) further including a first determiner for determination of the dot product Ai for each interpolating subpartition substantially comprising at least:
A) a backward filter, responsive to an input vector x and to the matrix Fwm , for determining a vector z such that z = Ftwmx; and where t represents a transpose operator; and B) a dot product determiner, responsive to the vector z and to the m-th excitation codevector, for forming a dot product such that:
Ai = < z. ci > , where ci is the ith excitation codevector.
(a) the synthesis unit further includes a pitch synthesis unit, the pitch synthesis unit including at least a pitch analyzer and a time-varying pitch synthesis filter having a transfer function substantially of a form:
, where T represents an estimated pitch lag and .beta. represents gain of the pitch predictor;
(b) the excitation code vectors are stored in memory;
(c) the perceptual weighting unit includes at least a first perceptual weighting filter having a transfer function substantially of a form:
W(z) = , where .gamma. is typically selected to be substantially 0.8;
(d) determining an optimal excitation codevector from the codebook memory for each input reference vector includes signal processing every excitation codevector in the codebook memory for each input reference vector, then determining the optimal excitation codevector of those codevectors processed;
and (e) the fast codebook search device substantially further includes utilizing a simplified method to obtain the perceptually weighted squared error between an input signal vector and a related synthesized codevector utilizing an i-th excitation codevector, denoting this error by Ei, such that:
, where x represents an input target vector at a selected subpartition that is substantially equal to an input reference signal vector at a selected subpartition filtered by a corresponding interpolated weighting filter with a zero-input response of a corresponding interpolated weighted LPC-SF
subtracted from it, Ai represents a dot product of the vector x and an i-th filtered codevector yi,m at an m-th subpartition, and Bi represents the squared norm of the vector yi,m, and wherein 8 (e) further includes at least one of:
(1) the corresponding interpolated weighted LPC-SF has a transfer function of Hm(z/.gamma.), such that:
, where for an m-th subpartition, .gamma. is typically selected to be 0.8, and ai,m ,for i=1,2,...p, such that p is a predictor order, represent the parameters of corresponding interpolated LPC-SF, the impulse response of Hm(z/.gamma.), hwm(n), is substantially equal to:
hwm(n) = .gamma.nhm(n), and where hm(n) is an impulse response of corresponding LPC-SF, utilizing a fact that hm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated LPC-SFs, hwm(n), at each interpolating subpartition, determined in a fast codebook search as a linear interpolation of two impulse responses of related previous and current uninterpolated weighted LPC-SFs:
hwm(n) - .alpha.mhw(1)(n) + .beta.mhw(2)(n) , where hw(j)(n) = .gamma.nh(i)(n) for j=1,2 are exponentially weighted uninterpolated impulse responses of the previous, when j=1, and the current, when j=2, LPC synthesis filters, and where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m is utilized for each subpartition;
(2) the filtered codevector yi,m is determined as a convolution of the i-th excitation codevector ci with the corresponding weighted impulse response hwm(n), the convolution being substantially:
yi,m = Fwmci, where Fwm =
and where k represents a dimension of a codevector, further utilizing the fact that hwm(n) is a linear interpolation of the impulse responses of related previous and current uninterpolated weighted LPC-SFs, the filtered codevector yi,m at each interpolating subpartition may be substantially determined as linear interpolation of two codevectors filtered by the related previous and current uninterpolated weighted LPC-SFs:
yi,m = .alpha.myi(1) + .beta.myi(2) , and where yi(j) = Fw(j)ci for j=1,2 and where matrices Fw(1) and Fw(2) have substantially a same format as the matrix Fwm, but with different elements hw(1)(n) and hw(2)(n) , respectively;
(3) further including a second determiner, responsive to the squared norm of a filtered codevector yi(1), the squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, for determining the squared norm Bi at each interpolating subpartition, substantially a weighted sum of a squared norm of a filtered codevector yi(1), a squared norm of the filtered codevector yi(2), and a dot product of those two filtered codevectors, substantially being:
Bi = .alpha.m2¦¦ yi(1)¦¦2 + .beta.m2¦¦ yi(2)¦¦2+2.alpha.m.beta.m<yi(1).yi(2)>, where .beta.m = 1- .alpha.m and 0 < .alpha.m < 1, where a different .alpha.m isutilized for each subpartition; and (4) further including a first determiner for determination of the dot product Ai for each interpolating subpartition substantially comprising at least:
A) a backward filter, responsive to an input vector x and to the matrix Fwm , for determining a vector z such that z = Ftwmx; and where t represents a transpose operator; and B) a dot product determiner, responsive to the vector z and to the m-th excitation codevector, for forming a dot product such that:
Ai = < z. ci > , where ci is the ith excitation codevector.
Applications Claiming Priority (2)
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|---|---|---|---|
| US669,831 | 1991-03-15 | ||
| US07/669,831 US5195168A (en) | 1991-03-15 | 1991-03-15 | Speech coder and method having spectral interpolation and fast codebook search |
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| CA2103785A1 CA2103785A1 (en) | 1992-09-16 |
| CA2103785C true CA2103785C (en) | 1997-04-22 |
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| EP (1) | EP0575511A1 (en) |
| JP (1) | JPH06506070A (en) |
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|---|---|---|---|---|
| US3631520A (en) * | 1968-08-19 | 1971-12-28 | Bell Telephone Labor Inc | Predictive coding of speech signals |
| US4133976A (en) * | 1978-04-07 | 1979-01-09 | Bell Telephone Laboratories, Incorporated | Predictive speech signal coding with reduced noise effects |
| US4220819A (en) * | 1979-03-30 | 1980-09-02 | Bell Telephone Laboratories, Incorporated | Residual excited predictive speech coding system |
| CA1299750C (en) * | 1986-01-03 | 1992-04-28 | Ira Alan Gerson | Optimal method of data reduction in a speech recognition system |
| US4896361A (en) * | 1988-01-07 | 1990-01-23 | Motorola, Inc. | Digital speech coder having improved vector excitation source |
| EP0364647B1 (en) * | 1988-10-19 | 1995-02-22 | International Business Machines Corporation | Improvement to vector quantizing coder |
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1991
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1992
- 1992-02-20 CA CA002103785A patent/CA2103785C/en not_active Expired - Fee Related
- 1992-02-20 WO PCT/US1992/001299 patent/WO1992016930A1/en not_active Application Discontinuation
- 1992-02-20 JP JP4508177A patent/JPH06506070A/en active Pending
- 1992-02-20 EP EP92908562A patent/EP0575511A1/en not_active Withdrawn
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| EP0575511A1 (en) | 1993-12-29 |
| WO1992016930A1 (en) | 1992-10-01 |
| US5195168A (en) | 1993-03-16 |
| JPH06506070A (en) | 1994-07-07 |
| EP0575511A4 (en) | 1994-02-02 |
| CA2103785A1 (en) | 1992-09-16 |
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