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  1. /*
  2. * LPC utility code
  3. * Copyright (c) 2006 Justin Ruggles <justin.ruggles@gmail.com>
  4. *
  5. * This file is part of Libav.
  6. *
  7. * Libav is free software; you can redistribute it and/or
  8. * modify it under the terms of the GNU Lesser General Public
  9. * License as published by the Free Software Foundation; either
  10. * version 2.1 of the License, or (at your option) any later version.
  11. *
  12. * Libav is distributed in the hope that it will be useful,
  13. * but WITHOUT ANY WARRANTY; without even the implied warranty of
  14. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  15. * Lesser General Public License for more details.
  16. *
  17. * You should have received a copy of the GNU Lesser General Public
  18. * License along with Libav; if not, write to the Free Software
  19. * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
  20. */
  21. #include "libavutil/lls.h"
  22. #define LPC_USE_DOUBLE
  23. #include "lpc.h"
  24. /**
  25. * Apply Welch window function to audio block
  26. */
  27. static void lpc_apply_welch_window_c(const int32_t *data, int len,
  28. double *w_data)
  29. {
  30. int i, n2;
  31. double w;
  32. double c;
  33. /* The optimization in commit fa4ed8c does not support odd len.
  34. * If someone wants odd len extend that change. */
  35. assert(!(len & 1));
  36. n2 = (len >> 1);
  37. c = 2.0 / (len - 1.0);
  38. w_data+=n2;
  39. data+=n2;
  40. for(i=0; i<n2; i++) {
  41. w = c - n2 + i;
  42. w = 1.0 - (w * w);
  43. w_data[-i-1] = data[-i-1] * w;
  44. w_data[+i ] = data[+i ] * w;
  45. }
  46. }
  47. /**
  48. * Calculate autocorrelation data from audio samples
  49. * A Welch window function is applied before calculation.
  50. */
  51. static void lpc_compute_autocorr_c(const double *data, int len, int lag,
  52. double *autoc)
  53. {
  54. int i, j;
  55. for(j=0; j<lag; j+=2){
  56. double sum0 = 1.0, sum1 = 1.0;
  57. for(i=j; i<len; i++){
  58. sum0 += data[i] * data[i-j];
  59. sum1 += data[i] * data[i-j-1];
  60. }
  61. autoc[j ] = sum0;
  62. autoc[j+1] = sum1;
  63. }
  64. if(j==lag){
  65. double sum = 1.0;
  66. for(i=j-1; i<len; i+=2){
  67. sum += data[i ] * data[i-j ]
  68. + data[i+1] * data[i-j+1];
  69. }
  70. autoc[j] = sum;
  71. }
  72. }
  73. /**
  74. * Quantize LPC coefficients
  75. */
  76. static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
  77. int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
  78. {
  79. int i;
  80. double cmax, error;
  81. int32_t qmax;
  82. int sh;
  83. /* define maximum levels */
  84. qmax = (1 << (precision - 1)) - 1;
  85. /* find maximum coefficient value */
  86. cmax = 0.0;
  87. for(i=0; i<order; i++) {
  88. cmax= FFMAX(cmax, fabs(lpc_in[i]));
  89. }
  90. /* if maximum value quantizes to zero, return all zeros */
  91. if(cmax * (1 << max_shift) < 1.0) {
  92. *shift = zero_shift;
  93. memset(lpc_out, 0, sizeof(int32_t) * order);
  94. return;
  95. }
  96. /* calculate level shift which scales max coeff to available bits */
  97. sh = max_shift;
  98. while((cmax * (1 << sh) > qmax) && (sh > 0)) {
  99. sh--;
  100. }
  101. /* since negative shift values are unsupported in decoder, scale down
  102. coefficients instead */
  103. if(sh == 0 && cmax > qmax) {
  104. double scale = ((double)qmax) / cmax;
  105. for(i=0; i<order; i++) {
  106. lpc_in[i] *= scale;
  107. }
  108. }
  109. /* output quantized coefficients and level shift */
  110. error=0;
  111. for(i=0; i<order; i++) {
  112. error -= lpc_in[i] * (1 << sh);
  113. lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
  114. error -= lpc_out[i];
  115. }
  116. *shift = sh;
  117. }
  118. static int estimate_best_order(double *ref, int min_order, int max_order)
  119. {
  120. int i, est;
  121. est = min_order;
  122. for(i=max_order-1; i>=min_order-1; i--) {
  123. if(ref[i] > 0.10) {
  124. est = i+1;
  125. break;
  126. }
  127. }
  128. return est;
  129. }
  130. /**
  131. * Calculate LPC coefficients for multiple orders
  132. *
  133. * @param lpc_type LPC method for determining coefficients,
  134. * see #FFLPCType for details
  135. */
  136. int ff_lpc_calc_coefs(LPCContext *s,
  137. const int32_t *samples, int blocksize, int min_order,
  138. int max_order, int precision,
  139. int32_t coefs[][MAX_LPC_ORDER], int *shift,
  140. enum FFLPCType lpc_type, int lpc_passes,
  141. int omethod, int max_shift, int zero_shift)
  142. {
  143. double autoc[MAX_LPC_ORDER+1];
  144. double ref[MAX_LPC_ORDER];
  145. double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
  146. int i, j, pass;
  147. int opt_order;
  148. assert(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER &&
  149. lpc_type > FF_LPC_TYPE_FIXED);
  150. /* reinit LPC context if parameters have changed */
  151. if (blocksize != s->blocksize || max_order != s->max_order ||
  152. lpc_type != s->lpc_type) {
  153. ff_lpc_end(s);
  154. ff_lpc_init(s, blocksize, max_order, lpc_type);
  155. }
  156. if (lpc_type == FF_LPC_TYPE_LEVINSON) {
  157. double *windowed_samples = s->windowed_samples + max_order;
  158. s->lpc_apply_welch_window(samples, blocksize, windowed_samples);
  159. s->lpc_compute_autocorr(windowed_samples, blocksize, max_order, autoc);
  160. compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
  161. for(i=0; i<max_order; i++)
  162. ref[i] = fabs(lpc[i][i]);
  163. } else if (lpc_type == FF_LPC_TYPE_CHOLESKY) {
  164. LLSModel m[2];
  165. double var[MAX_LPC_ORDER+1], av_uninit(weight);
  166. for(pass=0; pass<lpc_passes; pass++){
  167. av_init_lls(&m[pass&1], max_order);
  168. weight=0;
  169. for(i=max_order; i<blocksize; i++){
  170. for(j=0; j<=max_order; j++)
  171. var[j]= samples[i-j];
  172. if(pass){
  173. double eval, inv, rinv;
  174. eval= av_evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
  175. eval= (512>>pass) + fabs(eval - var[0]);
  176. inv = 1/eval;
  177. rinv = sqrt(inv);
  178. for(j=0; j<=max_order; j++)
  179. var[j] *= rinv;
  180. weight += inv;
  181. }else
  182. weight++;
  183. av_update_lls(&m[pass&1], var, 1.0);
  184. }
  185. av_solve_lls(&m[pass&1], 0.001, 0);
  186. }
  187. for(i=0; i<max_order; i++){
  188. for(j=0; j<max_order; j++)
  189. lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
  190. ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
  191. }
  192. for(i=max_order-1; i>0; i--)
  193. ref[i] = ref[i-1] - ref[i];
  194. }
  195. opt_order = max_order;
  196. if(omethod == ORDER_METHOD_EST) {
  197. opt_order = estimate_best_order(ref, min_order, max_order);
  198. i = opt_order-1;
  199. quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
  200. } else {
  201. for(i=min_order-1; i<max_order; i++) {
  202. quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
  203. }
  204. }
  205. return opt_order;
  206. }
  207. av_cold int ff_lpc_init(LPCContext *s, int blocksize, int max_order,
  208. enum FFLPCType lpc_type)
  209. {
  210. s->blocksize = blocksize;
  211. s->max_order = max_order;
  212. s->lpc_type = lpc_type;
  213. if (lpc_type == FF_LPC_TYPE_LEVINSON) {
  214. s->windowed_samples = av_mallocz((blocksize + max_order + 2) *
  215. sizeof(*s->windowed_samples));
  216. if (!s->windowed_samples)
  217. return AVERROR(ENOMEM);
  218. } else {
  219. s->windowed_samples = NULL;
  220. }
  221. s->lpc_apply_welch_window = lpc_apply_welch_window_c;
  222. s->lpc_compute_autocorr = lpc_compute_autocorr_c;
  223. if (HAVE_MMX)
  224. ff_lpc_init_x86(s);
  225. return 0;
  226. }
  227. av_cold void ff_lpc_end(LPCContext *s)
  228. {
  229. av_freep(&s->windowed_samples);
  230. }