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272d0c164d
apply_welch_window_even_c: 617.5 apply_welch_window_even_rvv_f64: 235.0 apply_welch_window_odd_c: 709.0 apply_welch_window_odd_rvv_f64: 256.5
336 lines
9.7 KiB
C
336 lines
9.7 KiB
C
/*
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* LPC utility code
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* Copyright (c) 2006 Justin Ruggles <justin.ruggles@gmail.com>
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*
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* This file is part of FFmpeg.
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*
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* FFmpeg is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* FFmpeg is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with FFmpeg; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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*/
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#include "libavutil/common.h"
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#include "libavutil/lls.h"
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#include "libavutil/mem_internal.h"
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#define LPC_USE_DOUBLE
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#include "lpc.h"
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#include "libavutil/avassert.h"
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/**
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* Apply Welch window function to audio block
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*/
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static void lpc_apply_welch_window_c(const int32_t *data, ptrdiff_t len,
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double *w_data)
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{
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int i, n2;
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double w;
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double c;
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if (len == 1) {
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w_data[0] = 0.0;
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return;
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}
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n2 = (len >> 1);
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c = 2.0 / (len - 1.0);
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if (len & 1) {
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for(i=0; i<n2; i++) {
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w = c - i - 1.0;
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w = 1.0 - (w * w);
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w_data[i] = data[i] * w;
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w_data[len-1-i] = data[len-1-i] * w;
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}
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w_data[n2] = 0.0;
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return;
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}
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w_data+=n2;
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data+=n2;
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for(i=0; i<n2; i++) {
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w = c - n2 + i;
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w = 1.0 - (w * w);
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w_data[-i-1] = data[-i-1] * w;
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w_data[+i ] = data[+i ] * w;
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}
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}
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/**
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* Calculate autocorrelation data from audio samples
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* A Welch window function is applied before calculation.
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*/
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static void lpc_compute_autocorr_c(const double *data, ptrdiff_t len, int lag,
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double *autoc)
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{
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int i, j;
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for(j=0; j<lag; j+=2){
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double sum0 = 1.0, sum1 = 1.0;
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for(i=j; i<len; i++){
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sum0 += data[i] * data[i-j];
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sum1 += data[i] * data[i-j-1];
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}
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autoc[j ] = sum0;
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autoc[j+1] = sum1;
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}
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if(j==lag){
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double sum = 1.0;
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for(i=j-1; i<len; i+=2){
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sum += data[i ] * data[i-j ]
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+ data[i+1] * data[i-j+1];
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}
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autoc[j] = sum;
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}
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}
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/**
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* Quantize LPC coefficients
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*/
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static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
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int32_t *lpc_out, int *shift, int min_shift,
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int max_shift, int zero_shift)
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{
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int i;
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double cmax, error;
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int32_t qmax;
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int sh;
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/* define maximum levels */
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qmax = (1 << (precision - 1)) - 1;
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/* find maximum coefficient value */
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cmax = 0.0;
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for(i=0; i<order; i++) {
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cmax= FFMAX(cmax, fabs(lpc_in[i]));
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}
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/* if maximum value quantizes to zero, return all zeros */
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if(cmax * (1 << max_shift) < 1.0) {
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*shift = zero_shift;
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memset(lpc_out, 0, sizeof(int32_t) * order);
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return;
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}
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/* calculate level shift which scales max coeff to available bits */
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sh = max_shift;
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while((cmax * (1 << sh) > qmax) && (sh > min_shift)) {
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sh--;
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}
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/* since negative shift values are unsupported in decoder, scale down
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coefficients instead */
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if(sh == 0 && cmax > qmax) {
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double scale = ((double)qmax) / cmax;
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for(i=0; i<order; i++) {
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lpc_in[i] *= scale;
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}
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}
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/* output quantized coefficients and level shift */
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error=0;
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for(i=0; i<order; i++) {
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error -= lpc_in[i] * (1 << sh);
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lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
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error -= lpc_out[i];
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}
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*shift = sh;
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}
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static int estimate_best_order(double *ref, int min_order, int max_order)
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{
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int i, est;
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est = min_order;
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for(i=max_order-1; i>=min_order-1; i--) {
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if(ref[i] > 0.10) {
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est = i+1;
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break;
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}
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}
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return est;
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}
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int ff_lpc_calc_ref_coefs(LPCContext *s,
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const int32_t *samples, int order, double *ref)
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{
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double autoc[MAX_LPC_ORDER + 1];
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s->lpc_apply_welch_window(samples, s->blocksize, s->windowed_samples);
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s->lpc_compute_autocorr(s->windowed_samples, s->blocksize, order, autoc);
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compute_ref_coefs(autoc, order, ref, NULL);
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return order;
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}
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double ff_lpc_calc_ref_coefs_f(LPCContext *s, const float *samples, int len,
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int order, double *ref)
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{
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int i;
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double signal = 0.0f, avg_err = 0.0f;
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double autoc[MAX_LPC_ORDER+1] = {0}, error[MAX_LPC_ORDER+1] = {0};
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const double a = 0.5f, b = 1.0f - a;
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/* Apply windowing */
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for (i = 0; i <= len / 2; i++) {
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double weight = a - b*cos((2*M_PI*i)/(len - 1));
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s->windowed_samples[i] = weight*samples[i];
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s->windowed_samples[len-1-i] = weight*samples[len-1-i];
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}
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s->lpc_compute_autocorr(s->windowed_samples, len, order, autoc);
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signal = autoc[0];
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compute_ref_coefs(autoc, order, ref, error);
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for (i = 0; i < order; i++)
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avg_err = (avg_err + error[i])/2.0f;
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return avg_err ? signal/avg_err : NAN;
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}
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/**
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* Calculate LPC coefficients for multiple orders
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*
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* @param lpc_type LPC method for determining coefficients,
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* see #FFLPCType for details
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*/
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int ff_lpc_calc_coefs(LPCContext *s,
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const int32_t *samples, int blocksize, int min_order,
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int max_order, int precision,
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int32_t coefs[][MAX_LPC_ORDER], int *shift,
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enum FFLPCType lpc_type, int lpc_passes,
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int omethod, int min_shift, int max_shift, int zero_shift)
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{
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double autoc[MAX_LPC_ORDER+1];
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double ref[MAX_LPC_ORDER] = { 0 };
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double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
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int i, j, pass = 0;
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int opt_order;
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av_assert2(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER &&
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lpc_type > FF_LPC_TYPE_FIXED);
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av_assert0(lpc_type == FF_LPC_TYPE_CHOLESKY || lpc_type == FF_LPC_TYPE_LEVINSON);
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/* reinit LPC context if parameters have changed */
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if (blocksize != s->blocksize || max_order != s->max_order ||
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lpc_type != s->lpc_type) {
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ff_lpc_end(s);
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ff_lpc_init(s, blocksize, max_order, lpc_type);
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}
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if(lpc_passes <= 0)
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lpc_passes = 2;
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if (lpc_type == FF_LPC_TYPE_LEVINSON || (lpc_type == FF_LPC_TYPE_CHOLESKY && lpc_passes > 1)) {
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s->lpc_apply_welch_window(samples, blocksize, s->windowed_samples);
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s->lpc_compute_autocorr(s->windowed_samples, blocksize, max_order, autoc);
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compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
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for(i=0; i<max_order; i++)
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ref[i] = fabs(lpc[i][i]);
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pass++;
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}
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if (lpc_type == FF_LPC_TYPE_CHOLESKY) {
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LLSModel *m = s->lls_models;
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LOCAL_ALIGNED(32, double, var, [FFALIGN(MAX_LPC_ORDER+1,4)]);
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double av_uninit(weight);
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memset(var, 0, FFALIGN(MAX_LPC_ORDER+1,4)*sizeof(*var));
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for(j=0; j<max_order; j++)
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m[0].coeff[max_order-1][j] = -lpc[max_order-1][j];
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for(; pass<lpc_passes; pass++){
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avpriv_init_lls(&m[pass&1], max_order);
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weight=0;
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for(i=max_order; i<blocksize; i++){
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for(j=0; j<=max_order; j++)
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var[j]= samples[i-j];
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if(pass){
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double eval, inv, rinv;
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eval= m[pass&1].evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
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eval= (512>>pass) + fabs(eval - var[0]);
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inv = 1/eval;
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rinv = sqrt(inv);
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for(j=0; j<=max_order; j++)
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var[j] *= rinv;
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weight += inv;
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}else
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weight++;
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m[pass&1].update_lls(&m[pass&1], var);
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}
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avpriv_solve_lls(&m[pass&1], 0.001, 0);
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}
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for(i=0; i<max_order; i++){
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for(j=0; j<max_order; j++)
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lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
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ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
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}
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for(i=max_order-1; i>0; i--)
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ref[i] = ref[i-1] - ref[i];
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}
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opt_order = max_order;
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if(omethod == ORDER_METHOD_EST) {
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opt_order = estimate_best_order(ref, min_order, max_order);
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i = opt_order-1;
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quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i],
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min_shift, max_shift, zero_shift);
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} else {
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for(i=min_order-1; i<max_order; i++) {
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quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i],
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min_shift, max_shift, zero_shift);
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}
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}
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return opt_order;
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}
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av_cold int ff_lpc_init(LPCContext *s, int blocksize, int max_order,
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enum FFLPCType lpc_type)
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{
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s->blocksize = blocksize;
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s->max_order = max_order;
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s->lpc_type = lpc_type;
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s->windowed_buffer = av_mallocz((blocksize + 2 + FFALIGN(max_order, 4)) *
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sizeof(*s->windowed_samples));
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if (!s->windowed_buffer)
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return AVERROR(ENOMEM);
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s->windowed_samples = s->windowed_buffer + FFALIGN(max_order, 4);
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s->lpc_apply_welch_window = lpc_apply_welch_window_c;
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s->lpc_compute_autocorr = lpc_compute_autocorr_c;
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#if ARCH_RISCV
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ff_lpc_init_riscv(s);
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#elif ARCH_X86
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ff_lpc_init_x86(s);
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#endif
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return 0;
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}
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av_cold void ff_lpc_end(LPCContext *s)
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{
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av_freep(&s->windowed_buffer);
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}
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