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lpc.c
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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 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 
22 #include "libavutil/common.h"
23 #include "libavutil/lls2.h"
24 
25 #define LPC_USE_DOUBLE
26 #include "lpc.h"
27 #include "libavutil/avassert.h"
28 
29 
30 /**
31  * Apply Welch window function to audio block
32  */
33 static void lpc_apply_welch_window_c(const int32_t *data, int len,
34  double *w_data)
35 {
36  int i, n2;
37  double w;
38  double c;
39 
40  /* The optimization in commit fa4ed8c does not support odd len.
41  * If someone wants odd len extend that change. */
42  av_assert2(!(len & 1));
43 
44  n2 = (len >> 1);
45  c = 2.0 / (len - 1.0);
46 
47  w_data+=n2;
48  data+=n2;
49  for(i=0; i<n2; i++) {
50  w = c - n2 + i;
51  w = 1.0 - (w * w);
52  w_data[-i-1] = data[-i-1] * w;
53  w_data[+i ] = data[+i ] * w;
54  }
55 }
56 
57 /**
58  * Calculate autocorrelation data from audio samples
59  * A Welch window function is applied before calculation.
60  */
61 static void lpc_compute_autocorr_c(const double *data, int len, int lag,
62  double *autoc)
63 {
64  int i, j;
65 
66  for(j=0; j<lag; j+=2){
67  double sum0 = 1.0, sum1 = 1.0;
68  for(i=j; i<len; i++){
69  sum0 += data[i] * data[i-j];
70  sum1 += data[i] * data[i-j-1];
71  }
72  autoc[j ] = sum0;
73  autoc[j+1] = sum1;
74  }
75 
76  if(j==lag){
77  double sum = 1.0;
78  for(i=j-1; i<len; i+=2){
79  sum += data[i ] * data[i-j ]
80  + data[i+1] * data[i-j+1];
81  }
82  autoc[j] = sum;
83  }
84 }
85 
86 /**
87  * Quantize LPC coefficients
88  */
89 static void quantize_lpc_coefs(double *lpc_in, int order, int precision,
90  int32_t *lpc_out, int *shift, int max_shift, int zero_shift)
91 {
92  int i;
93  double cmax, error;
94  int32_t qmax;
95  int sh;
96 
97  /* define maximum levels */
98  qmax = (1 << (precision - 1)) - 1;
99 
100  /* find maximum coefficient value */
101  cmax = 0.0;
102  for(i=0; i<order; i++) {
103  cmax= FFMAX(cmax, fabs(lpc_in[i]));
104  }
105 
106  /* if maximum value quantizes to zero, return all zeros */
107  if(cmax * (1 << max_shift) < 1.0) {
108  *shift = zero_shift;
109  memset(lpc_out, 0, sizeof(int32_t) * order);
110  return;
111  }
112 
113  /* calculate level shift which scales max coeff to available bits */
114  sh = max_shift;
115  while((cmax * (1 << sh) > qmax) && (sh > 0)) {
116  sh--;
117  }
118 
119  /* since negative shift values are unsupported in decoder, scale down
120  coefficients instead */
121  if(sh == 0 && cmax > qmax) {
122  double scale = ((double)qmax) / cmax;
123  for(i=0; i<order; i++) {
124  lpc_in[i] *= scale;
125  }
126  }
127 
128  /* output quantized coefficients and level shift */
129  error=0;
130  for(i=0; i<order; i++) {
131  error -= lpc_in[i] * (1 << sh);
132  lpc_out[i] = av_clip(lrintf(error), -qmax, qmax);
133  error -= lpc_out[i];
134  }
135  *shift = sh;
136 }
137 
138 static int estimate_best_order(double *ref, int min_order, int max_order)
139 {
140  int i, est;
141 
142  est = min_order;
143  for(i=max_order-1; i>=min_order-1; i--) {
144  if(ref[i] > 0.10) {
145  est = i+1;
146  break;
147  }
148  }
149  return est;
150 }
151 
153  const int32_t *samples, int order, double *ref)
154 {
155  double autoc[MAX_LPC_ORDER + 1];
156 
158  s->lpc_compute_autocorr(s->windowed_samples, s->blocksize, order, autoc);
159  compute_ref_coefs(autoc, order, ref, NULL);
160 
161  return order;
162 }
163 
164 /**
165  * Calculate LPC coefficients for multiple orders
166  *
167  * @param lpc_type LPC method for determining coefficients,
168  * see #FFLPCType for details
169  */
171  const int32_t *samples, int blocksize, int min_order,
172  int max_order, int precision,
173  int32_t coefs[][MAX_LPC_ORDER], int *shift,
174  enum FFLPCType lpc_type, int lpc_passes,
175  int omethod, int max_shift, int zero_shift)
176 {
177  double autoc[MAX_LPC_ORDER+1];
178  double ref[MAX_LPC_ORDER];
179  double lpc[MAX_LPC_ORDER][MAX_LPC_ORDER];
180  int i, j, pass = 0;
181  int opt_order;
182 
183  av_assert2(max_order >= MIN_LPC_ORDER && max_order <= MAX_LPC_ORDER &&
184  lpc_type > FF_LPC_TYPE_FIXED);
185  av_assert0(lpc_type == FF_LPC_TYPE_CHOLESKY || lpc_type == FF_LPC_TYPE_LEVINSON);
186 
187  /* reinit LPC context if parameters have changed */
188  if (blocksize != s->blocksize || max_order != s->max_order ||
189  lpc_type != s->lpc_type) {
190  ff_lpc_end(s);
191  ff_lpc_init(s, blocksize, max_order, lpc_type);
192  }
193 
194  if(lpc_passes <= 0)
195  lpc_passes = 2;
196 
197  if (lpc_type == FF_LPC_TYPE_LEVINSON || (lpc_type == FF_LPC_TYPE_CHOLESKY && lpc_passes > 1)) {
198  s->lpc_apply_welch_window(samples, blocksize, s->windowed_samples);
199 
200  s->lpc_compute_autocorr(s->windowed_samples, blocksize, max_order, autoc);
201 
202  compute_lpc_coefs(autoc, max_order, &lpc[0][0], MAX_LPC_ORDER, 0, 1);
203 
204  for(i=0; i<max_order; i++)
205  ref[i] = fabs(lpc[i][i]);
206 
207  pass++;
208  }
209 
210  if (lpc_type == FF_LPC_TYPE_CHOLESKY) {
211  LLSModel2 m[2];
212  LOCAL_ALIGNED(32, double, var, [FFALIGN(MAX_LPC_ORDER+1,4)]);
213  double av_uninit(weight);
214  memset(var, 0, FFALIGN(MAX_LPC_ORDER+1,4)*sizeof(*var));
215 
216  for(j=0; j<max_order; j++)
217  m[0].coeff[max_order-1][j] = -lpc[max_order-1][j];
218 
219  for(; pass<lpc_passes; pass++){
220  avpriv_init_lls2(&m[pass&1], max_order);
221 
222  weight=0;
223  for(i=max_order; i<blocksize; i++){
224  for(j=0; j<=max_order; j++)
225  var[j]= samples[i-j];
226 
227  if(pass){
228  double eval, inv, rinv;
229  eval= m[pass&1].evaluate_lls(&m[(pass-1)&1], var+1, max_order-1);
230  eval= (512>>pass) + fabs(eval - var[0]);
231  inv = 1/eval;
232  rinv = sqrt(inv);
233  for(j=0; j<=max_order; j++)
234  var[j] *= rinv;
235  weight += inv;
236  }else
237  weight++;
238 
239  m[pass&1].update_lls(&m[pass&1], var);
240  }
241  avpriv_solve_lls2(&m[pass&1], 0.001, 0);
242  }
243 
244  for(i=0; i<max_order; i++){
245  for(j=0; j<max_order; j++)
246  lpc[i][j]=-m[(pass-1)&1].coeff[i][j];
247  ref[i]= sqrt(m[(pass-1)&1].variance[i] / weight) * (blocksize - max_order) / 4000;
248  }
249  for(i=max_order-1; i>0; i--)
250  ref[i] = ref[i-1] - ref[i];
251  }
252 
253  opt_order = max_order;
254 
255  if(omethod == ORDER_METHOD_EST) {
256  opt_order = estimate_best_order(ref, min_order, max_order);
257  i = opt_order-1;
258  quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
259  } else {
260  for(i=min_order-1; i<max_order; i++) {
261  quantize_lpc_coefs(lpc[i], i+1, precision, coefs[i], &shift[i], max_shift, zero_shift);
262  }
263  }
264 
265  return opt_order;
266 }
267 
268 av_cold int ff_lpc_init(LPCContext *s, int blocksize, int max_order,
269  enum FFLPCType lpc_type)
270 {
271  s->blocksize = blocksize;
272  s->max_order = max_order;
273  s->lpc_type = lpc_type;
274 
275  s->windowed_buffer = av_mallocz((blocksize + 2 + FFALIGN(max_order, 4)) *
276  sizeof(*s->windowed_samples));
277  if (!s->windowed_buffer)
278  return AVERROR(ENOMEM);
279  s->windowed_samples = s->windowed_buffer + FFALIGN(max_order, 4);
280 
283 
284  if (ARCH_X86)
285  ff_lpc_init_x86(s);
286 
287  return 0;
288 }
289 
291 {
293 }