Abstract:
To perform pitch analysis for encoding a speech signal, a speech signal is sampled. The sampled speech signal is spectrally whitened to produce a spectral residual signal. Samples of the spectral residual signal are collected and the collected samples are autocorrelated. Maximum values of the correlated result are determined. Gain values are determined based on at least in part the maximum values of the correlated result. The gain values are quantized using a codebook to produce a codebook index and an associated frame delay. The codebook index and the frame delay represent a pitch of the speech signal to facilitate encoding the speech signal.

Description:
REFERENCES TO RELATED APPLICATIONS 
     This application is a continuation of application Ser. No. 08/950,658, filed Oct. 15, 1997, now U.S. Pat. No. 6,006,174, which is a continuation of application Ser. No. 08/670,986, filed Jun. 28, 1996, now abandoned, which is a continuation of application Ser. No. 08/104,174, filed Aug. 9, 1993, now abandoned, which is a continuation of application Ser. No. 07/592,330, filed Oct. 3, 1990, which issued on Aug. 10, 1993 as U.S. Pat. No. 5,235,670. 
    
    
     FIELD OF THE INVENTION 
     This invention relates to digital voice coders performing at relatively low voice rates but maintaining high voice quality. In particular, it relates to improved multipulse linear predictive voice coders. 
     BACKGROUND OF THE INVENTION 
     The multipulse coder incorporates the linear predictive all-pole filter (LPC filter). The basic function of a multipulse coder is finding a suitable excitation pattern for the LPC all-pole filter which produces an output that closely matches the original speech waveform. The excitation signal is a series of weighted impulses. The weight values and impulse locations are found in a systematic manner. The selection of a weight and location of an excitation impulse is obtained by minimizing an error criterion between the all-pole filter output and the original speech signal. Some multipulse coders incorporate a perceptual weighting filter in the error criterion function. This filter serves to frequency weight the error which in essence allows more error in the formant regions of the speech signal and less in low energy portions of the spectrum. Incorporation of pitch filters improve the performance of multipulse speech coders. This is done by modeling the long term redundancy of the speech signal thereby allowing the excitation signal to account for the pitch related properties of the signal. 
     SUMMARY OF THE INVENTION 
     The basic function of the present invention is the finding of a suitable excitation pattern that produces a synthetic speech signal which closely matches the original speech. A location and amplitude of an excitation pulse is selected by minimizing the mean-squared error between the real and synthetic speech signals. The above function is provided by using an excitation pattern containing a multiplicity of weighted pulses at timed positions. 
     The selection of the location and amplitude of an excitation pulse is obtained by minimizing an error criterion between a synthetic speech signal and the original speech. The error criterion function incorporates a perceptual weighting filter which shapes the error spectrum. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram of an 8 kbps multipulse LPC speech coder. 
     FIG. 2 is a block diagram of a sample/hold and A/D circuit used in the system of FIG.  1 . 
     FIG. 3 is a block diagram of the spectral whitening circuit of FIG.  1 . 
     FIG. 4 is a block diagram of the perceptual speech weighting circuit of FIG.  1 . 
     FIG. 5 is a block diagram of the reflection coefficient quantization circuit of FIG.  1 . 
     FIG. 6 is a block diagram of the LFC interpolation/weighting circuit of FIG.  1 . 
     FIG. 7 is a flow chart diagram of the pitch analysis block of FIG.  1 . 
     FIG. 8 is a flow chart diagram of the multipulse analysis block of FIG.  1 . 
     FIG. 9 is a block diagram of the impulse response generator of FIG.  1 . 
     FIG. 10 is a block diagram of the perceptual synthesizer circuit of FIG.  1 . 
     FIG. 11 is a block diagram of the ringdown generator circuit of FIG.  1 . 
     FIG. 12 is a diagrammatic view of the factorial tables address storage used in the system of FIG.  1 . 
    
    
     DETAILED DESCRIPTION 
     This invention incorporates improvements to the prior art of multipulse coders, specifically, a new type LPC spectral quantization, pitch filter implementation, incorporation of pitch synthesis filter in the multipulse analysis, and excitation encoding/decoding. 
     Shown in FIG. 1 is a block diagram of an 8 kbps multipulse LPC speech coder, generally designated  10 . 
     It comprises a pre-emphasis block  12  to receive the speech signals s(n). The pre-emphasized signals are applied to an LPC analysis block  14  as well as to a spectral whitening block  16  and to a perceptually weighted speech block  18 . 
     The output of the block  14  is applied to a reflection coefficient quantization and LPC conversion block  20 , whose output is applied both to the bit packing block  22  and to an LPC interpolation/weighting block  24 . 
     The output from block  20  to block  24  is indicated at  α  and the outputs from block  24  are indicated at  α ,  α   1 , and at  α   p ,  α   1   p . 
     The signal  α ,  α   1  is applied to the spectral whitening block  16  and the signal  α   p ,  α   1   p  is applied to the impulse generation block  26 . 
     The output of spectral whitening block  16  is applied to the pitch analysis block  28  whose output is applied to quantizer block  30 . The quantized output P from quantizer  30  is applied to the Sp(n) and also as a second input to the impulse response generation block  26 . The output of block  26 , indicated at h(n), is applied to the multipulse analysis block  32 . 
     The perceptual weighting block  18  receives both outputs from block  24  and its output, indicated at Sp(n), is applied to an adder  34  which also receives the output r(n) from a ringdown generator  36 . The ringdown component r(n) is a fixed signal due to the contributions of the previous frames. The output x(n) of the adder  34  is applied as a second input to the multipulse analysis block  32 . The two outputs Ê and Ĝ of the multipulse analysis block  32  are fed to the bit packing block  22 . 
     The signals  α ,  α   1 , P and Ê, Ĝ are fed to the perceptual synthesizer block  38  whose output y(n), comprising the combined weighted reflection coefficients, quantized spectral coefficients and multipulse analysis signals of previous frames, is applied to the block delay N/ 2   40 . The output of block  40  is applied to the ringdown generator  36 . 
     The output of the block  22  is fed to the synthesizer/postfilter  42 . 
     The operation of the aforesaid system is described as follows: The original speech is digitized using sample/hold and A/D circuitry  44  comprising a sample and hold block  46  and an analog to digital block  48 . (FIG.  2 ). The sampling rate is 8 kHz. The digitized speech signal, s(n), is analyzed on a block basis, meaning that before analysis can begin, N samples of s(n) must be acquired. Once a block of speech samples s(n) is acquired, it is passed to the preemphasis filter  12  which has a z-transform function 
     
       
           P ( z )=1 −α*z   −1   (1) 
       
     
     It is then passed to the LPC analysis block  14  from which the signal K is fed to the reflection coefficient quantizer and LPC converter whitening block  20 , (shown in detail in FIG.  3 ). The LPC analysis block  14  produces LPC reflection coefficients which are related to the all-pole filter coefficients. The reflection coefficients are then quantized in block  20  in the manner shown in detail in FIG. 5 wherein two sets of quantizer tables are previously stored. One set has been designed using training databases based on voiced speech, while the other has been designed using unvoiced speech. The reflection coefficients are quantized twice; once using the voiced quantizer  49  and once using the unvoiced quantizer  50 . Each quantized set of reflection coefficients is converted to its respective spectral coefficients, as at  52  and  54 , which, in turn, enables the computation of the log-spectral distance between the unquantized spectrum and the quantized spectrum. The set of quantized reflection coefficients which produces the smaller log-spectral distance shown at  56 , is then retained. The retained reflection coefficient parameters are encoded for transmission and also converted to the corresponding all-pole LPC filter coefficients in block  58 . 
     Following the reflection quantization and LPC coefficient conversion, the LPC filter parameters are interpolated using the scheme described herein. As previously discussed, LPC analysis is performed on speech of block length N which corresponds to N/8000 seconds (sampling rate=8000 Hz). Therefore, a set of filter coefficients is generated for every N samples of speech or every N/8000 sec. 
     In order to enhance spectral trajectory tracking, the LPC filter parameters are interpolated on a sub-frame basis at block  24  where the sub-frame rate is twice the frame rate. The interpolation scheme is implemented (as shown in detail in FIG. 6) as follows: let the LPC filter coefficients for frame k-1 be α 0  and for frame k be α 1 . The filter coefficients for the first sub-frame of frame k is then 
     
       
           α =( α   0 + α   1 )/2  (2) 
       
     
     and α parameters are applied to the second sub-frame. Therefore a different set of LPC filter parameters are available every 0.5*(N/8000) sec. 
     Pitch Analysis 
     Prior methods of pitch filter implementation for multipulse LPC coders have focused on closed loop pitch analysis methods (U.S. Pat. No. 4,701,954). However, such closed loop methods are computationally expensive. In the present invention the pitch analysis procedure indicated by block  28 , is performed in an open loop manner on the speech spectral residual signal. Open loop methods have reduced computational requirements. The spectral residual signal is generated using the inverse LPC filter which can be represented in the z-transform domain as A(z); A(z)=1/H(z) where H(z), is the LPC all-pole filter. This is known as spectral whitening and is represented by block  16 . This block  16  is shown in detail in FIG.  3 . The spectral whitening process removes the short-time sample correlation which in turn enhances pitch analysis. 
     A flow chart diagram of the pitch analysis block  28  of FIG. 1 is shown in FIG.  7 . The first step in the pitch analysis process is the collection of N samples of the spectral residual signal. This spectral residual signal is obtained from the pre-emphasized speech signal by the method illustrated in FIG.  3 . These residual samples are appended to the prior K retained residual samples to form a segment, r(n), where −K ≦ n ≦ N. 
     The autocorrelation Q(i) is performed for τ l   ≦ i ≦ τ h  or                Q        (   i   )       =       ∑     n   =     -   κ       N                       r        (   n   )            r        (     n   -   i     )                   (   3   )                 r   l     ≤   i   ≤     r   h                                              
     The limits of i are arbitrary but for speech sounds a typical range is between 20 and 147 (assuming 8 kHz sampling). The next step is to search Q(i) for the max value, M 1 , where 
     
       
           M   1 =max( Q ( i ))= Q ( k   1 )  (4) 
       
     
     The value k is stored and Q(k 1 −1), Q(k 1 ), and Q(K 1 +1) are set to a large negative value. We next find a second value M 2  where 
     
       
           M   2 =max( Q ( i ))= Q ( k   2 )  (5) 
       
     
     The values k 1  and k 2  correspond to delay values that produce the two largest correlation values. The values k 1  and k 2  are used to check for pitch period doubling. The following algorithm is employed: If the ABS(k 2 −2*k 1 )&lt;C, where C can be chosen to be equal to the number of taps (3 in this invention, then the delay value, D, is equal to k 2  otherwise D=k 1 . Once the frame delay value, D, is chosen the 3-tap gain terms are solved by first computing the matrix and vector values in eq. (6).                [           ∑       r        (   i   )            r        (     n   -   τ   -   1     )                     ∑       r        (   n   )            r        (     n   -   i     )                     ∑       r        (   n   )            r        (     n   -   i   +   1     )                 ]     =     [           ∑       r        (     n   -   i   -   1     )            r        (     n   -   i   -   1     )                 ∑       r        (     n   -   i     )            r        (     n   -   i   -   1     )                 ∑       r        (     n   -   i   +   1     )            r        (     n   -   i   -   1     )                     ∑       r        (     n   -   i   -   1     )            r        (     n   -   i     )                 ∑       r        (     n   -   i     )            r        (     n   -   i     )                 ∑       r        (     n   -   i   +   1     )            r        (     n   -   i     )                     ∑       r        (     n   -   i   -   1     )            r        (     n   -   i   +   1     )                 ∑       r        (     n   -   i     )            r        (     n   -   i   +   1     )                 ∑       r        (     n   -   i   +   1     )            r        (     n   -   i   +   1     )                 ]             (   6   )                                
     The matrix is solved using the Choleski matrix decomposition. Once the gain values are calculated, they are quantized using a 32 word vector codebook. The codebook index along with the frame delay parameter are transmitted. The P signifies the quantized delay value and index of the gain codebook. 
     Excitation Analysis 
     Multipulse&#39;s name stems from the operation of exciting a vocal tract model with multiple impulses. A location and amplitude of an excitation pulse is chosen by minimizing the mean-squared error between the real and synthetic speech signals. This system incorporates the perceptual weighting filter  18 . A detailed flow chart of the multipulse analysis is shown in FIG.  8 . The method of determining a pulse location and amplitude is accomplished in a systematic manner. The basic algorithm can be described as follows: let h(n) be the system impulse response of the pitch analysis filter and the LPC analysis filter in cascade; the synthetic speech is the system&#39;s response to the multipulse excitation. This is indicated as the excitation convolved with the system response or                  s   ^          (   n   )       =       ∑     k   =   1     n                       ex        (   k   )            h        (     n   -   k     )                   (   7   )                                
     where ex(n) is a set of weighted impulses located at positions n 1 , n 2 , . . . n j  or 
     
       
           ex ( n )=β 1 δ( n−n   1 )+β 2 δ( n−n   2 )+ . . . +β j δ( n−n   j )  (8) 
       
     
     The synthetic speech can be re-written as                  s   ^          (   n   )       =       ∑     j   =   1     J                       B   j          h        (     n   -     n   j       )                   (   9   )                                
     In the present invention, the excitation pulse search is performed one pulse at a time, therefore j=1. The error between the real and synthetic speech is 
     
       
           e ( n )= s   p ( n )− ŝ ( n )− r ( n )  (10) 
       
     
     The squared error              E   =       ∑     n   =   1     N                          2          (   n   )                 (   11   )                                
     or              E   =       ∑     n   =   1     N                       (         s   p          (   n   )       -       s   ^          (   n   )       -     r        (   n   )         )     2               (   12   )                                
     where s p (n) is the original speech after pre-emphasis and perceptual weighting (FIG. 4) and r(n) is a fixed signal component due to the previous frames&#39; contributions and is referred to as the ringdown component. FIGS. 10 and 11 show the manner in which this signal is generated, FIG. 10 illustrating the perceptual synthesizer  38  and FIG. 11 illustrating the ringdown generator  36 . The squared error is now written as              E   =       ∑     n   =   1     N                       (       x        (   n   )       -       B   1          h        (     n   -     n   j       )           )     2               (   13   )                                
     where x(n) is the speech signal s p (n)−r(n) as shown in FIG.  1 . 
     
       
           E=S− 2 BC+B   2   H   (14) 
       
     
     where              C   =       ∑     n   =   1       N   -   1                         x        (   n   )            h        (     n   -     n   j       )                   (   15   )                                
     and              S   =       ∑     n   =   1       N   -   1                         x   2          (   n   )                 (   16   )                                
     and              H   =       ∑     n   =   1       N   -   1                       h   (     n   -       n   1          h        (     n   -     n   1       )                       (   17   )                                
     The error, E, is minimized by setting the dE/dB=0 or 
     
       
           dE/dB =−2 C+ 2 HB= 0  (18) 
       
     
     or 
     
       
           B=C/H   (19) 
       
     
     The error, E, can then be written as 
     
       
           E=S−C   2   /H   (20) 
       
     
     From the above equations it is evident that two signals are required for multipulse analysis, namely h(n) and x(n). These two signals are input to the multipulse analysis block  32 . 
     The first step in excitation analysis is to generate the system impulse response. The system impulse response is the concatentation of the 3-tap pitch synthesis filter and the LPC weighted filter. The impulse response filter has the z-transform:                  H   p          (   z   )       =       1     1   -       ∑     l   =   1     3                       b   i          z       -   τ     -   i                    1     1   -       ∑     l   =   1     ρ                       α   i          μ   i          z     -   i                         (   20   )                                
     The b values are the pitch gain coefficients, the α values are the spectral filter coefficients, and μ is a filter weighting coefficient. The error signal, e(n), can be written in the z-transform domain as 
     
       
           E ( z )= X ( z )−β H   p ( z ) z   −n1   (21) 
       
     
     where X(z) is the z-transform of x(n) previously defined. The impulse response weight β, and impulse response time shift location n 1  are computed by minimizing the energy of the error signal, e(n). The time shift variable n 1  (1=1 for first pulse) is now varied from 1 to N. The value of n 1  is chosen such that it produces the smallest energy error E. Once n 1  is found β 1  can be calculated. Once the first location, n 1  and impulse weight, β 1 , are determined the synthetic signal is written as 
     
       
           ŝ ( n )=β 1   h ( n−n   1 )  (22) 
       
     
     When two weighted impulses are considered in the excitation sequence, the error energy can be written as 
     
       
           E =Σ( x ( n )−β 1   h ( n−n   1 )−β 2   h ( n−n   2 )) 2   
       
     
     Since the first pulse weight and location are known, the equation is rewritten as 
     
       
           E =Σ( x ′( n )−β 2   h ( n−n   2 )) 2   (23) 
       
     
     where 
     
       
           x ′( n )= x ( n )−β 1   h ( n−n   2 )  (24) 
       
     
     The procedure for determining β 2  and n 2  is identical to that of determining β 1  and n 1 . This procedure can be repeated p times. In the present instantiation p=5. The excitation pulse locations are encoded using an enumerative encoding scheme. 
     Excitation Encoding 
     A normal encoding scheme for 5 pulse locations would take 5*Int(log 2  N+0.5), where N is the number of possible locations. For p=5 and N=80, 35 bits are required. The approach taken here is to employ an enumerative encoding scheme. For the same conditions, the number of bits required is 25 bits. The first step is to order the pulse locations (i.e. 0 L1≦L2≦L3≦L4≦L5≦N−1 where L1=min(n 1 , n 2 , n 3 , n 4 , n 5 ) etc.). The 25 bit number, B, is:        B   =       (         L1           1         )     +     (         L2           2         )     +     (         L3           3         )     +     (         L4           4         )     +     (         L5           5         )                              
     Computing the 5 sets of factorials is prohibitive on a DSP device, therefore the approach taken here is to pre-compute the values and store them on a DSP ROM. This is shown in FIG.  12 . Many of the numbers require double precision (32 bits). A quick calculation yields a required storage (for N=80) of 790 words ((N−1)*2*5). This amount of storage can be reduced by first realizing () is simply L1; therefore no storage is required. Secondly, () contains only single precision numbers; therefore storage can be reduced to 553 words. The code is written such that the five addresses are computed from the pulse locations starting with the 5th location (Assumes pulse location range from 1 to 80). The address of the 5th pulse is 2*L5+393. The factor of 2 is due to double precision storage of L5&#39;s elements. The address of L4 is 2*L4+235, for L3, 2*L3+77, for L2, L2-1. The numbers stored at these locations are added and a 25-bit number representing the unique set of locations is produced. 
     A block diagram of the enumerative encoding schemes is listed. 
     Excitation Decoding 
     Decoding the 25-bit word at the receiver involves repeated subtractions. For example, given B is the 25-bit word, the 5th location is found by finding the value X such that          B        -   i                     (         79           5         )       &lt;   0             B   -     (         X           5         )       &lt;       0                 B     -     (           X   -   1             5         )       &gt;   0.                          
     then L5=X−1. Next let        B   =     B   -       (           L      5             5         )     .                              
     The fourth pulse location is found by finding a value X such that            B            -                  i          (           L5   -   1             4         )       &lt;     0                   B   -     (         X           4         )         &lt;       0                 B     -     (           X   -   1             4         )       &gt;   0                                       
     then L4=X−1. This is repeated for L3 and L2. The remaining number is L1.