mirror of
https://github.com/drowe67/codec2
synced 2026-08-14 19:31:34 -04:00
1238 lines
31 KiB
C
1238 lines
31 KiB
C
/*---------------------------------------------------------------------------*\
|
|
|
|
FILE........: quantise.c
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 31/5/92
|
|
|
|
Quantisation functions for the sinusoidal coder.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
/*
|
|
All rights reserved.
|
|
|
|
This program is free software; you can redistribute it and/or modify
|
|
it under the terms of the GNU Lesser General Public License version 2.1, as
|
|
published by the Free Software Foundation. This program is
|
|
distributed in the hope that it will be useful, but WITHOUT ANY
|
|
WARRANTY; without even the implied warranty of MERCHANTABILITY or
|
|
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
|
|
License for more details.
|
|
|
|
You should have received a copy of the GNU Lesser General Public License
|
|
along with this program; if not, see <http://www.gnu.org/licenses/>.
|
|
|
|
*/
|
|
|
|
#include <assert.h>
|
|
#include <ctype.h>
|
|
#include <stdio.h>
|
|
#include <stdlib.h>
|
|
#include <string.h>
|
|
#include <math.h>
|
|
|
|
#include "defines.h"
|
|
#include "dump.h"
|
|
#include "quantise.h"
|
|
#include "lpc.h"
|
|
#include "lsp.h"
|
|
#include "codec2_fft.h"
|
|
#include "phase.h"
|
|
#include "mbest.h"
|
|
|
|
#undef PROFILE
|
|
#include "machdep.h"
|
|
|
|
#define LSP_DELTA1 0.01 /* grid spacing for LSP root searches */
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION HEADERS
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
float speech_to_uq_lsps(float lsp[], float ak[], float Sn[], float w[],
|
|
int m_pitch, int order);
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTIONS
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
int lsp_bits(int i) {
|
|
return lsp_cb[i].log2m;
|
|
}
|
|
|
|
int lspd_bits(int i) {
|
|
return lsp_cbd[i].log2m;
|
|
}
|
|
|
|
int lsp_pred_vq_bits(int i) {
|
|
return lsp_cbjmv[i].log2m;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
quantise
|
|
|
|
Quantises vec by choosing the nearest vector in codebook cb, and
|
|
returns the vector index. The squared error of the quantised vector
|
|
is added to se.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
long quantise(const float * cb, float vec[], float w[], int k, int m, float *se)
|
|
/* float cb[][K]; current VQ codebook */
|
|
/* float vec[]; vector to quantise */
|
|
/* float w[]; weighting vector */
|
|
/* int k; dimension of vectors */
|
|
/* int m; size of codebook */
|
|
/* float *se; accumulated squared error */
|
|
{
|
|
float e; /* current error */
|
|
long besti; /* best index so far */
|
|
float beste; /* best error so far */
|
|
long j;
|
|
int i;
|
|
float diff;
|
|
|
|
besti = 0;
|
|
beste = 1E32;
|
|
for(j=0; j<m; j++) {
|
|
e = 0.0;
|
|
for(i=0; i<k; i++) {
|
|
diff = cb[j*k+i]-vec[i];
|
|
e += (diff*w[i] * diff*w[i]);
|
|
}
|
|
if (e < beste) {
|
|
beste = e;
|
|
besti = j;
|
|
}
|
|
}
|
|
|
|
*se += beste;
|
|
|
|
return(besti);
|
|
}
|
|
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
encode_lspds_scalar()
|
|
|
|
Scalar/VQ LSP difference-in-frequency quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void encode_lspds_scalar(
|
|
int indexes[],
|
|
float lsp[],
|
|
int order
|
|
)
|
|
{
|
|
int i,k,m;
|
|
float lsp_hz[order];
|
|
float lsp__hz[order];
|
|
float dlsp[order];
|
|
float dlsp_[order];
|
|
float wt[order];
|
|
const float *cb;
|
|
float se;
|
|
|
|
for(i=0; i<order; i++) {
|
|
wt[i] = 1.0;
|
|
}
|
|
|
|
/* convert from radians to Hz so we can use human readable
|
|
frequencies */
|
|
|
|
for(i=0; i<order; i++)
|
|
lsp_hz[i] = (4000.0/PI)*lsp[i];
|
|
|
|
wt[0] = 1.0;
|
|
for(i=0; i<order; i++) {
|
|
|
|
/* find difference from previous quantised lsp */
|
|
|
|
if (i)
|
|
dlsp[i] = lsp_hz[i] - lsp__hz[i-1];
|
|
else
|
|
dlsp[0] = lsp_hz[0];
|
|
|
|
k = lsp_cbd[i].k;
|
|
m = lsp_cbd[i].m;
|
|
cb = lsp_cbd[i].cb;
|
|
indexes[i] = quantise(cb, &dlsp[i], wt, k, m, &se);
|
|
dlsp_[i] = cb[indexes[i]*k];
|
|
|
|
if (i)
|
|
lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
|
|
else
|
|
lsp__hz[0] = dlsp_[0];
|
|
}
|
|
|
|
}
|
|
|
|
|
|
void decode_lspds_scalar(
|
|
float lsp_[],
|
|
int indexes[],
|
|
int order
|
|
)
|
|
{
|
|
int i,k;
|
|
float lsp__hz[order];
|
|
float dlsp_[order];
|
|
const float *cb;
|
|
|
|
for(i=0; i<order; i++) {
|
|
|
|
k = lsp_cbd[i].k;
|
|
cb = lsp_cbd[i].cb;
|
|
dlsp_[i] = cb[indexes[i]*k];
|
|
|
|
if (i)
|
|
lsp__hz[i] = lsp__hz[i-1] + dlsp_[i];
|
|
else
|
|
lsp__hz[0] = dlsp_[0];
|
|
|
|
lsp_[i] = (PI/4000.0)*lsp__hz[i];
|
|
}
|
|
|
|
}
|
|
|
|
#define MIN(a,b) ((a)<(b)?(a):(b))
|
|
#define MAX_ENTRIES 16384
|
|
|
|
void compute_weights(const float *x, float *w, int ndim)
|
|
{
|
|
int i;
|
|
w[0] = MIN(x[0], x[1]-x[0]);
|
|
for (i=1;i<ndim-1;i++)
|
|
w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
|
|
w[ndim-1] = MIN(x[ndim-1]-x[ndim-2], PI-x[ndim-1]);
|
|
|
|
for (i=0;i<ndim;i++)
|
|
w[i] = 1./(.01+w[i]);
|
|
}
|
|
|
|
int find_nearest(const float *codebook, int nb_entries, float *x, int ndim)
|
|
{
|
|
int i, j;
|
|
float min_dist = 1e15;
|
|
int nearest = 0;
|
|
|
|
for (i=0;i<nb_entries;i++)
|
|
{
|
|
float dist=0;
|
|
for (j=0;j<ndim;j++)
|
|
dist += (x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
|
|
if (dist<min_dist)
|
|
{
|
|
min_dist = dist;
|
|
nearest = i;
|
|
}
|
|
}
|
|
return nearest;
|
|
}
|
|
|
|
int find_nearest_weighted(const float *codebook, int nb_entries, float *x, const float *w, int ndim)
|
|
{
|
|
int i, j;
|
|
float min_dist = 1e15;
|
|
int nearest = 0;
|
|
|
|
for (i=0;i<nb_entries;i++)
|
|
{
|
|
float dist=0;
|
|
for (j=0;j<ndim;j++)
|
|
dist += w[j]*(x[j]-codebook[i*ndim+j])*(x[j]-codebook[i*ndim+j]);
|
|
if (dist<min_dist)
|
|
{
|
|
min_dist = dist;
|
|
nearest = i;
|
|
}
|
|
}
|
|
return nearest;
|
|
}
|
|
|
|
void lspjmv_quantise(float *x, float *xq, int order)
|
|
{
|
|
int i, n1, n2, n3;
|
|
float err[order], err2[order], err3[order];
|
|
float w[order], w2[order], w3[order];
|
|
const float *codebook1 = lsp_cbjmv[0].cb;
|
|
const float *codebook2 = lsp_cbjmv[1].cb;
|
|
const float *codebook3 = lsp_cbjmv[2].cb;
|
|
|
|
w[0] = MIN(x[0], x[1]-x[0]);
|
|
for (i=1;i<order-1;i++)
|
|
w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
|
|
w[order-1] = MIN(x[order-1]-x[order-2], PI-x[order-1]);
|
|
|
|
compute_weights(x, w, order);
|
|
|
|
n1 = find_nearest(codebook1, lsp_cbjmv[0].m, x, order);
|
|
|
|
for (i=0;i<order;i++)
|
|
{
|
|
xq[i] = codebook1[order*n1+i];
|
|
err[i] = x[i] - xq[i];
|
|
}
|
|
for (i=0;i<order/2;i++)
|
|
{
|
|
err2[i] = err[2*i];
|
|
err3[i] = err[2*i+1];
|
|
w2[i] = w[2*i];
|
|
w3[i] = w[2*i+1];
|
|
}
|
|
n2 = find_nearest_weighted(codebook2, lsp_cbjmv[1].m, err2, w2, order/2);
|
|
n3 = find_nearest_weighted(codebook3, lsp_cbjmv[2].m, err3, w3, order/2);
|
|
|
|
for (i=0;i<order/2;i++)
|
|
{
|
|
xq[2*i] += codebook2[order*n2/2+i];
|
|
xq[2*i+1] += codebook3[order*n3/2+i];
|
|
}
|
|
}
|
|
|
|
int check_lsp_order(float lsp[], int order)
|
|
{
|
|
int i;
|
|
float tmp;
|
|
int swaps = 0;
|
|
|
|
for(i=1; i<order; i++)
|
|
if (lsp[i] < lsp[i-1]) {
|
|
//fprintf(stderr, "swap %d\n",i);
|
|
swaps++;
|
|
tmp = lsp[i-1];
|
|
lsp[i-1] = lsp[i]-0.1;
|
|
lsp[i] = tmp+0.1;
|
|
i = 1; /* start check again, as swap may have caused out of order */
|
|
}
|
|
|
|
return swaps;
|
|
}
|
|
|
|
void force_min_lsp_dist(float lsp[], int order)
|
|
{
|
|
int i;
|
|
|
|
for(i=1; i<order; i++)
|
|
if ((lsp[i]-lsp[i-1]) < 0.01) {
|
|
lsp[i] += 0.01;
|
|
}
|
|
}
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
lpc_post_filter()
|
|
|
|
Applies a post filter to the LPC synthesis filter power spectrum
|
|
Pw, which suppresses the inter-formant energy.
|
|
|
|
The algorithm is from p267 (Section 8.6) of "Digital Speech",
|
|
edited by A.M. Kondoz, 1994 published by Wiley and Sons. Chapter 8
|
|
of this text is on the MBE vocoder, and this is a freq domain
|
|
adaptation of post filtering commonly used in CELP.
|
|
|
|
I used the Octave simulation lpcpf.m to get an understanding of the
|
|
algorithm.
|
|
|
|
Requires two more FFTs which is significantly more MIPs. However
|
|
it should be possible to implement this more efficiently in the
|
|
time domain. Just not sure how to handle relative time delays
|
|
between the synthesis stage and updating these coeffs. A smaller
|
|
FFT size might also be acceptable to save CPU.
|
|
|
|
TODO:
|
|
[ ] sync var names between Octave and C version
|
|
[ ] doc gain normalisation
|
|
[ ] I think the first FFT is not rqd as we do the same
|
|
thing in aks_to_M2().
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void lpc_post_filter(codec2_fftr_cfg fftr_fwd_cfg, float Pw[], float ak[],
|
|
int order, int dump, float beta, float gamma, int bass_boost, float E)
|
|
{
|
|
int i;
|
|
float x[FFT_ENC]; /* input to FFTs */
|
|
COMP Ww[FFT_ENC/2+1]; /* weighting spectrum */
|
|
float Rw[FFT_ENC/2+1]; /* R = WA */
|
|
float e_before, e_after, gain;
|
|
float Pfw;
|
|
float max_Rw, min_Rw;
|
|
float coeff;
|
|
PROFILE_VAR(tstart, tfft1, taw, tfft2, tww, tr);
|
|
|
|
PROFILE_SAMPLE(tstart);
|
|
|
|
/* Determine weighting filter spectrum W(exp(jw)) ---------------*/
|
|
|
|
for(i=0; i<FFT_ENC; i++) {
|
|
x[i] = 0.0;
|
|
}
|
|
|
|
x[0] = ak[0];
|
|
coeff = gamma;
|
|
for(i=1; i<=order; i++) {
|
|
x[i] = ak[i] * coeff;
|
|
coeff *= gamma;
|
|
}
|
|
codec2_fftr(fftr_fwd_cfg, x, Ww);
|
|
|
|
PROFILE_SAMPLE_AND_LOG(tfft2, taw, " fft2");
|
|
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Ww[i].real = Ww[i].real*Ww[i].real + Ww[i].imag*Ww[i].imag;
|
|
}
|
|
|
|
PROFILE_SAMPLE_AND_LOG(tww, tfft2, " Ww");
|
|
|
|
/* Determined combined filter R = WA ---------------------------*/
|
|
|
|
max_Rw = 0.0; min_Rw = 1E32;
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Rw[i] = sqrtf(Ww[i].real * Pw[i]);
|
|
if (Rw[i] > max_Rw)
|
|
max_Rw = Rw[i];
|
|
if (Rw[i] < min_Rw)
|
|
min_Rw = Rw[i];
|
|
|
|
}
|
|
|
|
PROFILE_SAMPLE_AND_LOG(tr, tww, " R");
|
|
|
|
#ifdef DUMP
|
|
if (dump)
|
|
dump_Rw(Rw);
|
|
#endif
|
|
|
|
/* create post filter mag spectrum and apply ------------------*/
|
|
|
|
/* measure energy before post filtering */
|
|
|
|
e_before = 1E-4;
|
|
for(i=0; i<FFT_ENC/2; i++)
|
|
e_before += Pw[i];
|
|
|
|
/* apply post filter and measure energy */
|
|
|
|
#ifdef DUMP
|
|
if (dump)
|
|
dump_Pwb(Pw);
|
|
#endif
|
|
|
|
|
|
e_after = 1E-4;
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Pfw = powf(Rw[i], beta);
|
|
Pw[i] *= Pfw * Pfw;
|
|
e_after += Pw[i];
|
|
}
|
|
gain = e_before/e_after;
|
|
|
|
/* apply gain factor to normalise energy, and LPC Energy */
|
|
|
|
gain *= E;
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Pw[i] *= gain;
|
|
}
|
|
|
|
if (bass_boost) {
|
|
/* add 3dB to first 1 kHz to account for LP effect of PF */
|
|
|
|
for(i=0; i<FFT_ENC/8; i++) {
|
|
Pw[i] *= 1.4*1.4;
|
|
}
|
|
}
|
|
|
|
PROFILE_SAMPLE_AND_LOG2(tr, " filt");
|
|
}
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
aks_to_M2()
|
|
|
|
Transforms the linear prediction coefficients to spectral amplitude
|
|
samples. This function determines A(m) from the average energy per
|
|
band using an FFT.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void aks_to_M2(
|
|
codec2_fftr_cfg fftr_fwd_cfg,
|
|
float ak[], /* LPC's */
|
|
int order,
|
|
MODEL *model, /* sinusoidal model parameters for this frame */
|
|
float E, /* energy term */
|
|
float *snr, /* signal to noise ratio for this frame in dB */
|
|
int dump, /* true to dump sample to dump file */
|
|
int sim_pf, /* true to simulate a post filter */
|
|
int pf, /* true to enable actual LPC post filter */
|
|
int bass_boost, /* enable LPC filter 0-1kHz 3dB boost */
|
|
float beta,
|
|
float gamma, /* LPC post filter parameters */
|
|
COMP Aw[] /* output power spectrum */
|
|
)
|
|
{
|
|
int i,m; /* loop variables */
|
|
int am,bm; /* limits of current band */
|
|
float r; /* no. rads/bin */
|
|
float Em; /* energy in band */
|
|
float Am; /* spectral amplitude sample */
|
|
float signal, noise;
|
|
PROFILE_VAR(tstart, tfft, tpw, tpf);
|
|
|
|
PROFILE_SAMPLE(tstart);
|
|
|
|
r = TWO_PI/(FFT_ENC);
|
|
|
|
/* Determine DFT of A(exp(jw)) --------------------------------------------*/
|
|
{
|
|
float a[FFT_ENC]; /* input to FFT for power spectrum */
|
|
|
|
for(i=0; i<FFT_ENC; i++) {
|
|
a[i] = 0.0;
|
|
}
|
|
|
|
for(i=0; i<=order; i++)
|
|
a[i] = ak[i];
|
|
codec2_fftr(fftr_fwd_cfg, a, Aw);
|
|
}
|
|
PROFILE_SAMPLE_AND_LOG(tfft, tstart, " fft");
|
|
|
|
/* Determine power spectrum P(w) = E/(A(exp(jw))^2 ------------------------*/
|
|
|
|
float Pw[FFT_ENC/2];
|
|
|
|
#ifndef FDV_ARM_MATH
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Pw[i] = 1.0/(Aw[i].real*Aw[i].real + Aw[i].imag*Aw[i].imag + 1E-6);
|
|
}
|
|
#else
|
|
// this difference may seem strange, but the gcc for STM32F4 generates almost 5 times
|
|
// faster code with the two loops: 1120 ms -> 242 ms
|
|
// so please leave it as is or improve further
|
|
// since this code is called 4 times it results in almost 4ms gain (21ms -> 17ms per audio frame decode @ 1300 )
|
|
|
|
for(i=0; i<FFT_ENC/2; i++)
|
|
{
|
|
Pw[i] = Aw[i].real * Aw[i].real + Aw[i].imag * Aw[i].imag + 1E-6;
|
|
}
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Pw[i] = 1.0/(Pw[i]);
|
|
}
|
|
#endif
|
|
|
|
PROFILE_SAMPLE_AND_LOG(tpw, tfft, " Pw");
|
|
|
|
if (pf)
|
|
lpc_post_filter(fftr_fwd_cfg, Pw, ak, order, dump, beta, gamma, bass_boost, E);
|
|
else {
|
|
for(i=0; i<FFT_ENC/2; i++) {
|
|
Pw[i] *= E;
|
|
}
|
|
}
|
|
|
|
PROFILE_SAMPLE_AND_LOG(tpf, tpw, " LPC post filter");
|
|
|
|
#ifdef DUMP
|
|
if (dump)
|
|
dump_Pw(Pw);
|
|
#endif
|
|
|
|
/* Determine magnitudes from P(w) ----------------------------------------*/
|
|
|
|
/* when used just by decoder {A} might be all zeroes so init signal
|
|
and noise to prevent log(0) errors */
|
|
|
|
signal = 1E-30; noise = 1E-32;
|
|
|
|
for(m=1; m<=model->L; m++) {
|
|
am = (int)((m - 0.5)*model->Wo/r + 0.5);
|
|
bm = (int)((m + 0.5)*model->Wo/r + 0.5);
|
|
|
|
// FIXME: With arm_rfft_fast_f32 we have to use this
|
|
// otherwise sometimes a to high bm is calculated
|
|
// which causes trouble later in the calculation
|
|
// chain
|
|
// it seems for some reason model->Wo is calculated somewhat too high
|
|
if (bm>FFT_ENC/2)
|
|
{
|
|
bm = FFT_ENC/2;
|
|
}
|
|
Em = 0.0;
|
|
|
|
for(i=am; i<bm; i++)
|
|
Em += Pw[i];
|
|
Am = sqrtf(Em);
|
|
|
|
signal += model->A[m]*model->A[m];
|
|
noise += (model->A[m] - Am)*(model->A[m] - Am);
|
|
|
|
/* This code significantly improves perf of LPC model, in
|
|
particular when combined with phase0. The LPC spectrum tends
|
|
to track just under the peaks of the spectral envelope, and
|
|
just above nulls. This algorithm does the reverse to
|
|
compensate - raising the amplitudes of spectral peaks, while
|
|
attenuating the null. This enhances the formants, and
|
|
suppresses the energy between formants. */
|
|
|
|
if (sim_pf) {
|
|
if (Am > model->A[m])
|
|
Am *= 0.7;
|
|
if (Am < model->A[m])
|
|
Am *= 1.4;
|
|
}
|
|
model->A[m] = Am;
|
|
}
|
|
*snr = 10.0*log10f(signal/noise);
|
|
|
|
PROFILE_SAMPLE_AND_LOG2(tpf, " rec");
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_Wo()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Encodes Wo using a WO_LEVELS quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
int encode_Wo(C2CONST *c2const, float Wo, int bits)
|
|
{
|
|
int index, Wo_levels = 1<<bits;
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
float norm;
|
|
|
|
norm = (Wo - Wo_min)/(Wo_max - Wo_min);
|
|
index = floorf(Wo_levels * norm + 0.5);
|
|
if (index < 0 ) index = 0;
|
|
if (index > (Wo_levels-1)) index = Wo_levels-1;
|
|
|
|
return index;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_Wo()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Decodes Wo using a WO_LEVELS quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
float decode_Wo(C2CONST *c2const, int index, int bits)
|
|
{
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
float step;
|
|
float Wo;
|
|
int Wo_levels = 1<<bits;
|
|
|
|
step = (Wo_max - Wo_min)/Wo_levels;
|
|
Wo = Wo_min + step*(index);
|
|
|
|
return Wo;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_log_Wo()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Encodes Wo in the log domain using a WO_LEVELS quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
int encode_log_Wo(C2CONST *c2const, float Wo, int bits)
|
|
{
|
|
int index, Wo_levels = 1<<bits;
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
float norm;
|
|
|
|
norm = (log10f(Wo) - log10f(Wo_min))/(log10f(Wo_max) - log10f(Wo_min));
|
|
index = floorf(Wo_levels * norm + 0.5);
|
|
if (index < 0 ) index = 0;
|
|
if (index > (Wo_levels-1)) index = Wo_levels-1;
|
|
|
|
return index;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_log_Wo()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Decodes Wo using a WO_LEVELS quantiser in the log domain.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
float decode_log_Wo(C2CONST *c2const, int index, int bits)
|
|
{
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
float step;
|
|
float Wo;
|
|
int Wo_levels = 1<<bits;
|
|
|
|
step = (log10f(Wo_max) - log10f(Wo_min))/Wo_levels;
|
|
Wo = log10f(Wo_min) + step*(index);
|
|
|
|
return POW10F(Wo);
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: speech_to_uq_lsps()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Analyse a windowed frame of time domain speech to determine LPCs
|
|
which are the converted to LSPs for quantisation and transmission
|
|
over the channel.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
float speech_to_uq_lsps(float lsp[],
|
|
float ak[],
|
|
float Sn[],
|
|
float w[],
|
|
int m_pitch,
|
|
int order
|
|
)
|
|
{
|
|
int i, roots;
|
|
float Wn[m_pitch];
|
|
float R[order+1];
|
|
float e, E;
|
|
|
|
e = 0.0;
|
|
for(i=0; i<m_pitch; i++) {
|
|
Wn[i] = Sn[i]*w[i];
|
|
e += Wn[i]*Wn[i];
|
|
}
|
|
|
|
/* trap 0 energy case as LPC analysis will fail */
|
|
|
|
if (e == 0.0) {
|
|
for(i=0; i<order; i++)
|
|
lsp[i] = (PI/order)*(float)i;
|
|
return 0.0;
|
|
}
|
|
|
|
autocorrelate(Wn, R, m_pitch, order);
|
|
levinson_durbin(R, ak, order);
|
|
|
|
E = 0.0;
|
|
for(i=0; i<=order; i++)
|
|
E += ak[i]*R[i];
|
|
|
|
/* 15 Hz BW expansion as I can't hear the difference and it may help
|
|
help occasional fails in the LSP root finding. Important to do this
|
|
after energy calculation to avoid -ve energy values.
|
|
*/
|
|
|
|
for(i=0; i<=order; i++)
|
|
ak[i] *= powf(0.994,(float)i);
|
|
|
|
roots = lpc_to_lsp(ak, order, lsp, 5, LSP_DELTA1);
|
|
if (roots != order) {
|
|
/* if root finding fails use some benign LSP values instead */
|
|
for(i=0; i<order; i++)
|
|
lsp[i] = (PI/order)*(float)i;
|
|
}
|
|
|
|
return E;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_lsps_scalar()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Scalar LSP quantiser. From a vector of unquantised (floating point)
|
|
LSPs finds the quantised LSP indexes.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void encode_lsps_scalar(int indexes[], float lsp[], int order)
|
|
{
|
|
int i,k,m;
|
|
float wt[1];
|
|
float lsp_hz[order];
|
|
const float * cb;
|
|
float se;
|
|
|
|
/* convert from radians to Hz so we can use human readable
|
|
frequencies */
|
|
|
|
for(i=0; i<order; i++)
|
|
lsp_hz[i] = (4000.0/PI)*lsp[i];
|
|
|
|
/* scalar quantisers */
|
|
|
|
wt[0] = 1.0;
|
|
for(i=0; i<order; i++) {
|
|
k = lsp_cb[i].k;
|
|
m = lsp_cb[i].m;
|
|
cb = lsp_cb[i].cb;
|
|
indexes[i] = quantise(cb, &lsp_hz[i], wt, k, m, &se);
|
|
}
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_lsps_scalar()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
From a vector of quantised LSP indexes, returns the quantised
|
|
(floating point) LSPs.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void decode_lsps_scalar(float lsp[], int indexes[], int order)
|
|
{
|
|
int i,k;
|
|
float lsp_hz[order];
|
|
const float * cb;
|
|
|
|
for(i=0; i<order; i++) {
|
|
k = lsp_cb[i].k;
|
|
cb = lsp_cb[i].cb;
|
|
lsp_hz[i] = cb[indexes[i]*k];
|
|
}
|
|
|
|
/* convert back to radians */
|
|
|
|
for(i=0; i<order; i++)
|
|
lsp[i] = (PI/4000.0)*lsp_hz[i];
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_lsps_vq()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 15 Feb 2012
|
|
|
|
Multi-stage VQ LSP quantiser developed by Jean-Marc Valin.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void encode_lsps_vq(int *indexes, float *x, float *xq, int order)
|
|
{
|
|
int i, n1, n2, n3;
|
|
float err[order], err2[order], err3[order];
|
|
float w[order], w2[order], w3[order];
|
|
const float *codebook1 = lsp_cbjmv[0].cb;
|
|
const float *codebook2 = lsp_cbjmv[1].cb;
|
|
const float *codebook3 = lsp_cbjmv[2].cb;
|
|
|
|
w[0] = MIN(x[0], x[1]-x[0]);
|
|
for (i=1;i<order-1;i++)
|
|
w[i] = MIN(x[i]-x[i-1], x[i+1]-x[i]);
|
|
w[order-1] = MIN(x[order-1]-x[order-2], PI-x[order-1]);
|
|
|
|
compute_weights(x, w, order);
|
|
|
|
n1 = find_nearest(codebook1, lsp_cbjmv[0].m, x, order);
|
|
|
|
for (i=0;i<order;i++)
|
|
{
|
|
xq[i] = codebook1[order*n1+i];
|
|
err[i] = x[i] - xq[i];
|
|
}
|
|
for (i=0;i<order/2;i++)
|
|
{
|
|
err2[i] = err[2*i];
|
|
err3[i] = err[2*i+1];
|
|
w2[i] = w[2*i];
|
|
w3[i] = w[2*i+1];
|
|
}
|
|
n2 = find_nearest_weighted(codebook2, lsp_cbjmv[1].m, err2, w2, order/2);
|
|
n3 = find_nearest_weighted(codebook3, lsp_cbjmv[2].m, err3, w3, order/2);
|
|
|
|
indexes[0] = n1;
|
|
indexes[1] = n2;
|
|
indexes[2] = n3;
|
|
}
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_lsps_vq()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 15 Feb 2012
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void decode_lsps_vq(int *indexes, float *xq, int order, int stages)
|
|
{
|
|
int i, n1, n2, n3;
|
|
const float *codebook1 = lsp_cbjmv[0].cb;
|
|
const float *codebook2 = lsp_cbjmv[1].cb;
|
|
const float *codebook3 = lsp_cbjmv[2].cb;
|
|
|
|
n1 = indexes[0];
|
|
n2 = indexes[1];
|
|
n3 = indexes[2];
|
|
|
|
for (i=0;i<order;i++) {
|
|
xq[i] = codebook1[order*n1+i];
|
|
}
|
|
|
|
if (stages != 1) {
|
|
for (i=0;i<order/2;i++) {
|
|
xq[2*i] += codebook2[order*n2/2+i];
|
|
xq[2*i+1] += codebook3[order*n3/2+i];
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: bw_expand_lsps()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Applies Bandwidth Expansion (BW) to a vector of LSPs. Prevents any
|
|
two LSPs getting too close together after quantisation. We know
|
|
from experiment that LSP quantisation errors < 12.5Hz (25Hz step
|
|
size) are inaudible so we use that as the minimum LSP separation.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void bw_expand_lsps(float lsp[], int order, float min_sep_low, float min_sep_high)
|
|
{
|
|
int i;
|
|
|
|
for(i=1; i<4; i++) {
|
|
|
|
if ((lsp[i] - lsp[i-1]) < min_sep_low*(PI/4000.0))
|
|
lsp[i] = lsp[i-1] + min_sep_low*(PI/4000.0);
|
|
|
|
}
|
|
|
|
/* As quantiser gaps increased, larger BW expansion was required
|
|
to prevent twinkly noises. This may need more experiment for
|
|
different quanstisers.
|
|
*/
|
|
|
|
for(i=4; i<order; i++) {
|
|
if (lsp[i] - lsp[i-1] < min_sep_high*(PI/4000.0))
|
|
lsp[i] = lsp[i-1] + min_sep_high*(PI/4000.0);
|
|
}
|
|
}
|
|
|
|
void bw_expand_lsps2(float lsp[],
|
|
int order
|
|
)
|
|
{
|
|
int i;
|
|
|
|
for(i=1; i<4; i++) {
|
|
|
|
if ((lsp[i] - lsp[i-1]) < 100.0*(PI/4000.0))
|
|
lsp[i] = lsp[i-1] + 100.0*(PI/4000.0);
|
|
|
|
}
|
|
|
|
/* As quantiser gaps increased, larger BW expansion was required
|
|
to prevent twinkly noises. This may need more experiment for
|
|
different quanstisers.
|
|
*/
|
|
|
|
for(i=4; i<order; i++) {
|
|
if (lsp[i] - lsp[i-1] < 200.0*(PI/4000.0))
|
|
lsp[i] = lsp[i-1] + 200.0*(PI/4000.0);
|
|
}
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: apply_lpc_correction()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Apply first harmonic LPC correction at decoder. This helps improve
|
|
low pitch males after LPC modelling, like hts1a and morig.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void apply_lpc_correction(MODEL *model)
|
|
{
|
|
if (model->Wo < (PI*150.0/4000)) {
|
|
model->A[1] *= 0.032;
|
|
}
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_energy()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Encodes LPC energy using an E_LEVELS quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
int encode_energy(float e, int bits)
|
|
{
|
|
int index, e_levels = 1<<bits;
|
|
float e_min = E_MIN_DB;
|
|
float e_max = E_MAX_DB;
|
|
float norm;
|
|
|
|
e = 10.0*log10f(e);
|
|
norm = (e - e_min)/(e_max - e_min);
|
|
index = floorf(e_levels * norm + 0.5);
|
|
if (index < 0 ) index = 0;
|
|
if (index > (e_levels-1)) index = e_levels-1;
|
|
|
|
return index;
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_energy()
|
|
AUTHOR......: David Rowe
|
|
DATE CREATED: 22/8/2010
|
|
|
|
Decodes energy using a E_LEVELS quantiser.
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
float decode_energy(int index, int bits)
|
|
{
|
|
float e_min = E_MIN_DB;
|
|
float e_max = E_MAX_DB;
|
|
float step;
|
|
float e;
|
|
int e_levels = 1<<bits;
|
|
|
|
step = (e_max - e_min)/e_levels;
|
|
e = e_min + step*(index);
|
|
e = POW10F(e/10.0);
|
|
|
|
return e;
|
|
}
|
|
|
|
|
|
static float ge_coeff[2] = {0.8, 0.9};
|
|
|
|
void compute_weights2(const float *x, const float *xp, float *w)
|
|
{
|
|
w[0] = 30;
|
|
w[1] = 1;
|
|
if (x[1]<0)
|
|
{
|
|
w[0] *= .6;
|
|
w[1] *= .3;
|
|
}
|
|
if (x[1]<-10)
|
|
{
|
|
w[0] *= .3;
|
|
w[1] *= .3;
|
|
}
|
|
/* Higher weight if pitch is stable */
|
|
if (fabsf(x[0]-xp[0])<.2)
|
|
{
|
|
w[0] *= 2;
|
|
w[1] *= 1.5;
|
|
} else if (fabsf(x[0]-xp[0])>.5) /* Lower if not stable */
|
|
{
|
|
w[0] *= .5;
|
|
}
|
|
|
|
/* Lower weight for low energy */
|
|
if (x[1] < xp[1]-10)
|
|
{
|
|
w[1] *= .5;
|
|
}
|
|
if (x[1] < xp[1]-20)
|
|
{
|
|
w[1] *= .5;
|
|
}
|
|
|
|
//w[0] = 30;
|
|
//w[1] = 1;
|
|
|
|
/* Square the weights because it's applied on the squared error */
|
|
w[0] *= w[0];
|
|
w[1] *= w[1];
|
|
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: quantise_WoE()
|
|
AUTHOR......: Jean-Marc Valin & David Rowe
|
|
DATE CREATED: 29 Feb 2012
|
|
|
|
Experimental joint Wo and LPC energy vector quantiser developed by
|
|
Jean-Marc Valin. Exploits correlations between the difference in
|
|
the log pitch and log energy from frame to frame. For example
|
|
both the pitch and energy tend to only change by small amounts
|
|
during voiced speech, however it is important that these changes be
|
|
coded carefully. During unvoiced speech they both change a lot but
|
|
the ear is less sensitive to errors so coarser quantisation is OK.
|
|
|
|
The ear is sensitive to log energy and loq pitch so we quantise in
|
|
these domains. That way the error measure used to quantise the
|
|
values is close to way the ear senses errors.
|
|
|
|
See http://jmspeex.livejournal.com/10446.html
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void quantise_WoE(C2CONST *c2const, MODEL *model, float *e, float xq[])
|
|
{
|
|
int i, n1;
|
|
float x[2];
|
|
float err[2];
|
|
float w[2];
|
|
const float *codebook1 = ge_cb[0].cb;
|
|
int nb_entries = ge_cb[0].m;
|
|
int ndim = ge_cb[0].k;
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
float Fs = c2const->Fs;
|
|
|
|
/* VQ is only trained for Fs = 8000 Hz */
|
|
|
|
assert(Fs == 8000);
|
|
|
|
x[0] = log10f((model->Wo/PI)*4000.0/50.0)/log10f(2);
|
|
x[1] = 10.0*log10f(1e-4 + *e);
|
|
|
|
compute_weights2(x, xq, w);
|
|
for (i=0;i<ndim;i++)
|
|
err[i] = x[i]-ge_coeff[i]*xq[i];
|
|
n1 = find_nearest_weighted(codebook1, nb_entries, err, w, ndim);
|
|
|
|
for (i=0;i<ndim;i++)
|
|
{
|
|
xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
|
|
err[i] -= codebook1[ndim*n1+i];
|
|
}
|
|
|
|
/*
|
|
x = log2(4000*Wo/(PI*50));
|
|
2^x = 4000*Wo/(PI*50)
|
|
Wo = (2^x)*(PI*50)/4000;
|
|
*/
|
|
|
|
model->Wo = powf(2.0, xq[0])*(PI*50.0)/4000.0;
|
|
|
|
/* bit errors can make us go out of range leading to all sorts of
|
|
probs like seg faults */
|
|
|
|
if (model->Wo > Wo_max) model->Wo = Wo_max;
|
|
if (model->Wo < Wo_min) model->Wo = Wo_min;
|
|
|
|
model->L = PI/model->Wo; /* if we quantise Wo re-compute L */
|
|
|
|
*e = POW10F(xq[1]/10.0);
|
|
}
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: encode_WoE()
|
|
AUTHOR......: Jean-Marc Valin & David Rowe
|
|
DATE CREATED: 11 May 2012
|
|
|
|
Joint Wo and LPC energy vector quantiser developed my Jean-Marc
|
|
Valin. Returns index, and updated states xq[].
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
int encode_WoE(MODEL *model, float e, float xq[])
|
|
{
|
|
int i, n1;
|
|
float x[2];
|
|
float err[2];
|
|
float w[2];
|
|
const float *codebook1 = ge_cb[0].cb;
|
|
int nb_entries = ge_cb[0].m;
|
|
int ndim = ge_cb[0].k;
|
|
|
|
assert((1<<WO_E_BITS) == nb_entries);
|
|
|
|
if (e < 0.0) e = 0; /* occasional small negative energies due LPC round off I guess */
|
|
|
|
x[0] = log10f((model->Wo/PI)*4000.0/50.0)/log10f(2);
|
|
x[1] = 10.0*log10f(1e-4 + e);
|
|
|
|
compute_weights2(x, xq, w);
|
|
for (i=0;i<ndim;i++)
|
|
err[i] = x[i]-ge_coeff[i]*xq[i];
|
|
n1 = find_nearest_weighted(codebook1, nb_entries, err, w, ndim);
|
|
|
|
for (i=0;i<ndim;i++)
|
|
{
|
|
xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
|
|
err[i] -= codebook1[ndim*n1+i];
|
|
}
|
|
|
|
//printf("enc: %f %f (%f)(%f) \n", xq[0], xq[1], e, 10.0*log10(1e-4 + e));
|
|
return n1;
|
|
}
|
|
|
|
|
|
/*---------------------------------------------------------------------------*\
|
|
|
|
FUNCTION....: decode_WoE()
|
|
AUTHOR......: Jean-Marc Valin & David Rowe
|
|
DATE CREATED: 11 May 2012
|
|
|
|
Joint Wo and LPC energy vector quantiser developed my Jean-Marc
|
|
Valin. Given index and states xq[], returns Wo & E, and updates
|
|
states xq[].
|
|
|
|
\*---------------------------------------------------------------------------*/
|
|
|
|
void decode_WoE(C2CONST *c2const, MODEL *model, float *e, float xq[], int n1)
|
|
{
|
|
int i;
|
|
const float *codebook1 = ge_cb[0].cb;
|
|
int ndim = ge_cb[0].k;
|
|
float Wo_min = c2const->Wo_min;
|
|
float Wo_max = c2const->Wo_max;
|
|
|
|
for (i=0;i<ndim;i++)
|
|
{
|
|
xq[i] = ge_coeff[i]*xq[i] + codebook1[ndim*n1+i];
|
|
}
|
|
|
|
//printf("dec: %f %f\n", xq[0], xq[1]);
|
|
model->Wo = powf(2.0, xq[0])*(PI*50.0)/4000.0;
|
|
|
|
/* bit errors can make us go out of range leading to all sorts of
|
|
probs like seg faults */
|
|
|
|
if (model->Wo > Wo_max) model->Wo = Wo_max;
|
|
if (model->Wo < Wo_min) model->Wo = Wo_min;
|
|
|
|
model->L = PI/model->Wo; /* if we quantise Wo re-compute L */
|
|
|
|
*e = POW10F(xq[1]/10.0);
|
|
}
|
|
|