SPcepXpc

Routine

void SPcepXpc (const float cep[], float pc[], int Np)

Purpose

Convert cepstral coefficients to predictor coefficients

Description

              Np       -k
  A(z) = 1 - SUM p(k) z  .
             k=1

The power spectrum corresponding to the all-pole LPC filter is

  S(w) = g^2 / |A(w)|^2 ,

where A(w) is short-hand notation for A(exp(jw)). The power spectrum is the Fourier transform of the (infinite) set of autocorrelation coefficients The cepstrum for the autocorrelation coefficients is given by the inverse Fourier transform of the log power spectrum. Equivalently the cepstral coefficients are the Fourier series coefficients of the (periodic) log power spectrum,

  ln[S(w)] = 2 ln[g] - ln[|A(w)|^2]

              inf
           =  SUM  c(k) exp(-jkw) .
             k=-inf

The cepstral coefficients are symmetric, c(-k) = c(k). For a minimum-phase A(z), the integral of ln[|A(w)|^2] is zero. The coefficient c(0) is then the average of the log power spectrum, c(0) = 2 ln[g]. This cepstral coefficient does not affect the values of the coefficients of A(z). An expression for the coefficients of A(z) is obtained by expanding ln[A(w)] in a Laurent series and taking the derivatives. This gives the recursion

                1  n-1
  p(n) = c(n) - -  SUM (n-k) c(n-k) p(k),  n=1,2,...,Np .
                n  k=1

Reference:

J. D. Markel and A. H. Gray, Jr., "Linear Prediction of Speech", Springer-Verlag, 1976.

Predictor coefficients are usually expressed algebraically as vectors with 1-offset indexing. The correspondence to the 0-offset C-arrays is as follows.

  p(1) <==> pc[0]       predictor coefficient corresponding to lag 1
  p(i) <==> pc[i-1]     1 <= i < Np

Parameters

-> const float cep[]

Cepstral coefficients (Np+1 values). The first cepstral coefficient cep[0] corresponds to the zero quefrency term and is not used in the calculation.

<- float pc[]

Vector of predictor coefficients (Np values). These are the coefficients of the predictor filter, with pc[0] being the predictor coefficient corresponding to lag 1, and pc[Np-1] corresponding to lag Np.

-> int Np

Number of predictor coefficients

Author / revision

See Also