You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

271 lines
7.8KB

  1. /**
  2. * LPC utility code
  3. * Copyright (c) 2006 Justin Ruggles <justin.ruggles@gmail.com>
  4. *
  5. * This file is part of FFmpeg.
  6. *
  7. * FFmpeg 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. * FFmpeg 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 FFmpeg; 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 apply_welch_window_c(const int32_t *data, int len, double *w_data)
  28. {
  29. int i, n2;
  30. double w;
  31. double c;
  32. assert(!(len&1)); //the optimization in r11881 does not support odd len
  33. //if someone wants odd len extend the change in r11881
  34. n2 = (len >> 1);
  35. c = 2.0 / (len - 1.0);
  36. w_data+=n2;
  37. data+=n2;
  38. for(i=0; i<n2; i++) {
  39. w = c - n2 + i;
  40. w = 1.0 - (w * w);
  41. w_data[-i-1] = data[-i-1] * w;
  42. w_data[+i ] = data[+i ] * w;
  43. }
  44. }
  45. /**
  46. * Calculate autocorrelation data from audio samples
  47. * A Welch window function is applied before calculation.
  48. */
  49. static void lpc_compute_autocorr_c(const double *data, int len, int lag,
  50. double *autoc)
  51. {
  52. int i, j;
  53. for(j=0; j<lag; j+=2){
  54. double sum0 = 1.0, sum1 = 1.0;
  55. for(i=j; i<len; i++){
  56. sum0 += data[i] * data[i-j];
  57. sum1 += data[i] * data[i-j-1];
  58. }
  59. autoc[j ] = sum0;
  60. autoc[j+1] = sum1;
  61. }
  62. if(j==lag){
  63. double sum = 1.0;
  64. for(i=j-1; i<len; i+=2){
  65. sum += data[i ] * data[i-j ]
  66. + data[i+1] * data[i-j+1];
  67. }
  68. autoc[j] = sum;
  69. }
  70. }
  71. /**
  72. * Quantize LPC coefficients
  73. */
  74. static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
  75. int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
  76. {
  77. int i;
  78. double cmax, error;
  79. int32_t qmax;
  80. int sh;
  81. /* define maximum levels */
  82. qmax = (1 << (precision - 1)) - 1;
  83. /* find maximum coefficient value */
  84. cmax = 0.0;
  85. for(i=0; i<order; i++) {
  86. cmax= FFMAX(cmax, fabs(lpc_in[i]));
  87. }
  88. /* if maximum value quantizes to zero, return all zeros */
  89. if(cmax * (1 << max_shift) < 1.0) {
  90. *shift = zero_shift;
  91. memset(lpc_out, 0, sizeof(int32_t) * order);
  92. return;
  93. }
  94. /* calculate level shift which scales max coeff to available bits */
  95. sh = max_shift;
  96. while((cmax * (1 << sh) > qmax) && (sh > 0)) {
  97. sh--;
  98. }
  99. /* since negative shift values are unsupported in decoder, scale down
  100. coefficients instead */
  101. if(sh == 0 && cmax > qmax) {
  102. double scale = ((double)qmax) / cmax;
  103. for(i=0; i<order; i++) {
  104. lpc_in[i] *= scale;
  105. }
  106. }
  107. /* output quantized coefficients and level shift */
  108. error=0;
  109. for(i=0; i<order; i++) {
  110. error -= lpc_in[i] * (1 << sh);
  111. lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
  112. error -= lpc_out[i];
  113. }
  114. *shift = sh;
  115. }
  116. static int estimate_best_order(double *ref, int min_order, int max_order)
  117. {
  118. int i, est;
  119. est = min_order;
  120. for(i=max_order-1; i>=min_order-1; i--) {
  121. if(ref[i] > 0.10) {
  122. est = i+1;
  123. break;
  124. }
  125. }
  126. return est;
  127. }
  128. /**
  129. * Calculate LPC coefficients for multiple orders
  130. *
  131. * @param use_lpc LPC method for determining coefficients
  132. * 0 = LPC with fixed pre-defined coeffs
  133. * 1 = LPC with coeffs determined by Levinson-Durbin recursion
  134. * 2+ = LPC with coeffs determined by Cholesky factorization using (use_lpc-1) passes.
  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 AVLPCType 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 > AV_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 == AV_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 == AV_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 AVLPCType lpc_type)
  209. {
  210. s->blocksize = blocksize;
  211. s->max_order = max_order;
  212. s->lpc_type = lpc_type;
  213. if (lpc_type == AV_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 = 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. }