/* * LPC utility code * Copyright (c) 2006 Justin Ruggles <justin.ruggles@gmail.com> * * This file is part of FFmpeg. * * FFmpeg is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * FFmpeg 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 * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with FFmpeg; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "libavutil/common.h" #include "libavutil/lls2.h" #define LPC_USE_DOUBLE #include "lpc.h" #include "libavutil/avassert.h" /** * Apply Welch window function to audio block */ static void lpc_apply_welch_window_c(const int32_t *data, int len, double *w_data) { int i, n2; double w; double c; /* The optimization in commit fa4ed8c does not support odd len. * If someone wants odd len extend that change. */ av_assert2(!(len & 1)); n2 = (len >> 1); c = 2.0 / (len - 1.0); w_data+=n2; data+=n2; for(i=0; i<n2; i++) { w = c - n2 + i; w = 1.0 - (w * w); w_data[-i-1] = data[-i-1] * w; w_data[+i ] = data[+i ] * w; } } /** * Calculate autocorrelation data from audio samples * A Welch window function is applied before calculation. */ static void lpc_compute_autocorr_c(const double *data, int len, int lag, double *autoc) { int i, j; for(j=0; j<lag; j+=2){ double sum0 = 1.0, sum1 = 1.0; for(i=j; i<len; i++){ sum0 += data[i] * data[i-j]; sum1 += data[i] * data[i-j-1]; } autoc[j ] = sum0; autoc[j+1] = sum1; } if(j==lag){ double sum = 1.0; for(i=j-1; i<len; i+=2){ sum += data[i ] * data[i-j ] + data[i+1] * data[i-j+1]; } autoc[j] = sum; } } /** * Quantize LPC coefficients */ static void quantize_lpc_coefs(double *lpc_in, int order, int precision, int32_t *lpc_out, int *shift, int max_shift, int zero_shift) { int i; double cmax, error; int32_t qmax; int sh; /* define maximum levels */ qmax = (1 << (precision - 1)) - 1; /* find maximum coefficient value */ cmax = 0.0; for(i=0; i<order; i++) { cmax= FFMAX(cmax, fabs(lpc_in[i])); } /* if maximum value quantizes to zero, return all zeros */ if(cmax * (1 << max_shift) < 1.0) { *shift = zero_shift; memset(lpc_out, 0, sizeof(int32_t) * order); return; } /* calculate level shift which scales max coeff to available bits */ sh = max_shift; while((cmax * (1 << sh) > qmax) && (sh > 0)) { sh--; } /* since negative shift values are unsupported in decoder, scale down coefficients instead */ if(sh == 0 && cmax > qmax) { double scale = ((double)qmax) / cmax; for(i=0; i<order; i++) { lpc_in[i] *= scale; } } /* output quantized coefficients and level shift */ error=0; for(i=0; i<order; i++) { error -= lpc_in[i] * (1 << sh); lpc_out[i] = av_clip(lrintf(error), -qmax, qmax); error -= lpc_out[i]; } *shift = sh; } static int estimate_best_order(double *ref, int min_order, int max_order) { int i, est; est = min_order; for(i=max_order-1; i>=min_order-1; i--) { if(ref[i] > 0.10) { est = i+1; break; } } return est; } int ff_lpc_calc_ref_coefs(LPCContext *s, const int32_t *samples, int order, double *ref) { double autoc[MAX_LPC_ORDER + 1]; s->lpc_apply_welch_window(samples, s->blocksize, s->windowed_samples); s->lpc_compute_autocorr(s->windowed_samples, s->blocksize, order, autoc); compute_ref_coefs(autoc, order, ref, NULL); return order; } /** * Calculate LPC coefficients for multiple orders * * @param lpc_type LPC method for determining coefficients, * see #FFLPCType for details */ int ff_lpc_calc_coefs(LPCContext *s, const int32_t *samples, int blocksize, int min_order, int max_order, int precision, int32_t coefs[][MAX_LPC_ORDER], int *shift, enum FFLPCType lpc_type, int lpc_passes, int omethod, int max_shift, int zero_shift) { double autoc[MAX_LPC_ORDER+1]; double ref[MAX_LPC_ORDER]; double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER]; int i, j, pass = 0; int opt_order; av_assert2(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER && lpc_type > FF_LPC_TYPE_FIXED); av_assert0(lpc_type == FF_LPC_TYPE_CHOLESKY || lpc_type == FF_LPC_TYPE_LEVINSON); /* reinit LPC context if parameters have changed */ if (blocksize != s->blocksize || max_order != s->max_order || lpc_type != s->lpc_type) { ff_lpc_end(s); ff_lpc_init(s, blocksize, max_order, lpc_type); } if(lpc_passes <= 0) lpc_passes = 2; if (lpc_type == FF_LPC_TYPE_LEVINSON || (lpc_type == FF_LPC_TYPE_CHOLESKY && lpc_passes > 1)) { s->lpc_apply_welch_window(samples, blocksize, s->windowed_samples); s->lpc_compute_autocorr(s->windowed_samples, blocksize, max_order, autoc); compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1); for(i=0; i<max_order; i++) ref[i] = fabs(lpc[i][i]); pass++; } if (lpc_type == FF_LPC_TYPE_CHOLESKY) { LLSModel2 m[2]; LOCAL_ALIGNED(32, double, var, [FFALIGN(MAX_LPC_ORDER+1,4)]); double av_uninit(weight); memset(var, 0, FFALIGN(MAX_LPC_ORDER+1,4)*sizeof(*var)); for(j=0; j<max_order; j++) m[0].coeff[max_order-1][j] = -lpc[max_order-1][j]; for(; pass<lpc_passes; pass++){ avpriv_init_lls2(&m[pass&1], max_order); weight=0; for(i=max_order; i<blocksize; i++){ for(j=0; j<=max_order; j++) var[j]= samples[i-j]; if(pass){ double eval, inv, rinv; eval= m[pass&1].evaluate_lls(&m[(pass-1)&1], var+1, max_order-1); eval= (512>>pass) + fabs(eval - var[0]); inv = 1/eval; rinv = sqrt(inv); for(j=0; j<=max_order; j++) var[j] *= rinv; weight += inv; }else weight++; m[pass&1].update_lls(&m[pass&1], var); } avpriv_solve_lls2(&m[pass&1], 0.001, 0); } for(i=0; i<max_order; i++){ for(j=0; j<max_order; j++) lpc[i][j]=-m[(pass-1)&1].coeff[i][j]; ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000; } for(i=max_order-1; i>0; i--) ref[i] = ref[i-1] - ref[i]; } opt_order = max_order; if(omethod == ORDER_METHOD_EST) { opt_order = estimate_best_order(ref, min_order, max_order); i = opt_order-1; quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift); } else { for(i=min_order-1; i<max_order; i++) { quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift); } } return opt_order; } av_cold int ff_lpc_init(LPCContext *s, int blocksize, int max_order, enum FFLPCType lpc_type) { s->blocksize = blocksize; s->max_order = max_order; s->lpc_type = lpc_type; s->windowed_buffer = av_mallocz((blocksize + 2 + FFALIGN(max_order, 4)) * sizeof(*s->windowed_samples)); if (!s->windowed_buffer) return AVERROR(ENOMEM); s->windowed_samples = s->windowed_buffer + FFALIGN(max_order, 4); s->lpc_apply_welch_window = lpc_apply_welch_window_c; s->lpc_compute_autocorr = lpc_compute_autocorr_c; if (ARCH_X86) ff_lpc_init_x86(s); return 0; } av_cold void ff_lpc_end(LPCContext *s) { av_freep(&s->windowed_buffer); }