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.

276 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/common.h"
  22. #include "libavutil/lls.h"
  23. #define LPC_USE_DOUBLE
  24. #include "lpc.h"
  25. #include "libavutil/avassert.h"
  26. /**
  27. * Apply Welch window function to audio block
  28. */
  29. static void lpc_apply_welch_window_c(const int32_t *data, int len,
  30. double *w_data)
  31. {
  32. int i, n2;
  33. double w;
  34. double c;
  35. /* The optimization in commit fa4ed8c does not support odd len.
  36. * If someone wants odd len extend that change. */
  37. av_assert2(!(len & 1));
  38. n2 = (len >> 1);
  39. c = 2.0 / (len - 1.0);
  40. w_data+=n2;
  41. data+=n2;
  42. for(i=0; i<n2; i++) {
  43. w = c - n2 + i;
  44. w = 1.0 - (w * w);
  45. w_data[-i-1] = data[-i-1] * w;
  46. w_data[+i ] = data[+i ] * w;
  47. }
  48. }
  49. /**
  50. * Calculate autocorrelation data from audio samples
  51. * A Welch window function is applied before calculation.
  52. */
  53. static void lpc_compute_autocorr_c(const double *data, int len, int lag,
  54. double *autoc)
  55. {
  56. int i, j;
  57. for(j=0; j<lag; j+=2){
  58. double sum0 = 1.0, sum1 = 1.0;
  59. for(i=j; i<len; i++){
  60. sum0 += data[i] * data[i-j];
  61. sum1 += data[i] * data[i-j-1];
  62. }
  63. autoc[j ] = sum0;
  64. autoc[j+1] = sum1;
  65. }
  66. if(j==lag){
  67. double sum = 1.0;
  68. for(i=j-1; i<len; i+=2){
  69. sum += data[i ] * data[i-j ]
  70. + data[i+1] * data[i-j+1];
  71. }
  72. autoc[j] = sum;
  73. }
  74. }
  75. /**
  76. * Quantize LPC coefficients
  77. */
  78. static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
  79. int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
  80. {
  81. int i;
  82. double cmax, error;
  83. int32_t qmax;
  84. int sh;
  85. /* define maximum levels */
  86. qmax = (1 << (precision - 1)) - 1;
  87. /* find maximum coefficient value */
  88. cmax = 0.0;
  89. for(i=0; i<order; i++) {
  90. cmax= FFMAX(cmax, fabs(lpc_in[i]));
  91. }
  92. /* if maximum value quantizes to zero, return all zeros */
  93. if(cmax * (1 << max_shift) < 1.0) {
  94. *shift = zero_shift;
  95. memset(lpc_out, 0, sizeof(int32_t) * order);
  96. return;
  97. }
  98. /* calculate level shift which scales max coeff to available bits */
  99. sh = max_shift;
  100. while((cmax * (1 << sh) > qmax) && (sh > 0)) {
  101. sh--;
  102. }
  103. /* since negative shift values are unsupported in decoder, scale down
  104. coefficients instead */
  105. if(sh == 0 && cmax > qmax) {
  106. double scale = ((double)qmax) / cmax;
  107. for(i=0; i<order; i++) {
  108. lpc_in[i] *= scale;
  109. }
  110. }
  111. /* output quantized coefficients and level shift */
  112. error=0;
  113. for(i=0; i<order; i++) {
  114. error -= lpc_in[i] * (1 << sh);
  115. lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
  116. error -= lpc_out[i];
  117. }
  118. *shift = sh;
  119. }
  120. static int estimate_best_order(double *ref, int min_order, int max_order)
  121. {
  122. int i, est;
  123. est = min_order;
  124. for(i=max_order-1; i>=min_order-1; i--) {
  125. if(ref[i] > 0.10) {
  126. est = i+1;
  127. break;
  128. }
  129. }
  130. return est;
  131. }
  132. /**
  133. * Calculate LPC coefficients for multiple orders
  134. *
  135. * @param lpc_type LPC method for determining coefficients,
  136. * see #FFLPCType for details
  137. */
  138. int ff_lpc_calc_coefs(LPCContext *s,
  139. const int32_t *samples, int blocksize, int min_order,
  140. int max_order, int precision,
  141. int32_t coefs[][MAX_LPC_ORDER], int *shift,
  142. enum FFLPCType lpc_type, int lpc_passes,
  143. int omethod, int max_shift, int zero_shift)
  144. {
  145. double autoc[MAX_LPC_ORDER+1];
  146. double ref[MAX_LPC_ORDER];
  147. double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
  148. int i, j, pass;
  149. int opt_order;
  150. av_assert2(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER &&
  151. lpc_type > FF_LPC_TYPE_FIXED);
  152. /* reinit LPC context if parameters have changed */
  153. if (blocksize != s->blocksize || max_order != s->max_order ||
  154. lpc_type != s->lpc_type) {
  155. ff_lpc_end(s);
  156. ff_lpc_init(s, blocksize, max_order, lpc_type);
  157. }
  158. if (lpc_type == FF_LPC_TYPE_LEVINSON) {
  159. double *windowed_samples = s->windowed_samples + max_order;
  160. s->lpc_apply_welch_window(samples, blocksize, windowed_samples);
  161. s->lpc_compute_autocorr(windowed_samples, blocksize, max_order, autoc);
  162. compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
  163. for(i=0; i<max_order; i++)
  164. ref[i] = fabs(lpc[i][i]);
  165. } else if (lpc_type == FF_LPC_TYPE_CHOLESKY) {
  166. LLSModel m[2];
  167. double var[MAX_LPC_ORDER+1], av_uninit(weight);
  168. if(lpc_passes <= 0)
  169. lpc_passes = 2;
  170. for(pass=0; pass<lpc_passes; pass++){
  171. av_init_lls(&m[pass&1], max_order);
  172. weight=0;
  173. for(i=max_order; i<blocksize; i++){
  174. for(j=0; j<=max_order; j++)
  175. var[j]= samples[i-j];
  176. if(pass){
  177. double eval, inv, rinv;
  178. eval= av_evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
  179. eval= (512>>pass) + fabs(eval - var[0]);
  180. inv = 1/eval;
  181. rinv = sqrt(inv);
  182. for(j=0; j<=max_order; j++)
  183. var[j] *= rinv;
  184. weight += inv;
  185. }else
  186. weight++;
  187. av_update_lls(&m[pass&1], var, 1.0);
  188. }
  189. av_solve_lls(&m[pass&1], 0.001, 0);
  190. }
  191. for(i=0; i<max_order; i++){
  192. for(j=0; j<max_order; j++)
  193. lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
  194. ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
  195. }
  196. for(i=max_order-1; i>0; i--)
  197. ref[i] = ref[i-1] - ref[i];
  198. }
  199. opt_order = max_order;
  200. if(omethod == ORDER_METHOD_EST) {
  201. opt_order = estimate_best_order(ref, min_order, max_order);
  202. i = opt_order-1;
  203. quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
  204. } else {
  205. for(i=min_order-1; i<max_order; i++) {
  206. quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
  207. }
  208. }
  209. return opt_order;
  210. }
  211. av_cold int ff_lpc_init(LPCContext *s, int blocksize, int max_order,
  212. enum FFLPCType lpc_type)
  213. {
  214. s->blocksize = blocksize;
  215. s->max_order = max_order;
  216. s->lpc_type = lpc_type;
  217. if (lpc_type == FF_LPC_TYPE_LEVINSON) {
  218. s->windowed_samples = av_mallocz((blocksize + max_order + 2) *
  219. sizeof(*s->windowed_samples));
  220. if (!s->windowed_samples)
  221. return AVERROR(ENOMEM);
  222. } else {
  223. s->windowed_samples = NULL;
  224. }
  225. s->lpc_apply_welch_window = lpc_apply_welch_window_c;
  226. s->lpc_compute_autocorr = lpc_compute_autocorr_c;
  227. if (HAVE_MMX)
  228. ff_lpc_init_x86(s);
  229. return 0;
  230. }
  231. av_cold void ff_lpc_end(LPCContext *s)
  232. {
  233. av_freep(&s->windowed_samples);
  234. }