PocketSphinx  5prealpha
ptm_mgau.c
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37 
38 /* System headers */
39 #include <stdio.h>
40 #include <stdlib.h>
41 #include <string.h>
42 #include <assert.h>
43 #include <limits.h>
44 #include <math.h>
45 #if defined(__ADSPBLACKFIN__)
46 #elif !defined(_WIN32_WCE)
47 #include <sys/types.h>
48 #endif
49 
50 /* SphinxBase headers */
51 #include <sphinx_config.h>
52 #include <sphinxbase/cmd_ln.h>
53 #include <sphinxbase/fixpoint.h>
54 #include <sphinxbase/ckd_alloc.h>
55 #include <sphinxbase/bio.h>
56 #include <sphinxbase/err.h>
57 #include <sphinxbase/prim_type.h>
58 
59 /* Local headers */
60 #include "tied_mgau_common.h"
61 #include "ptm_mgau.h"
62 
63 static ps_mgaufuncs_t ptm_mgau_funcs = {
64  "ptm",
65  ptm_mgau_frame_eval, /* frame_eval */
66  ptm_mgau_mllr_transform, /* transform */
67  ptm_mgau_free /* free */
68 };
69 
70 #define COMPUTE_GMM_MAP(_idx) \
71  diff[_idx] = obs[_idx] - mean[_idx]; \
72  sqdiff[_idx] = MFCCMUL(diff[_idx], diff[_idx]); \
73  compl[_idx] = MFCCMUL(sqdiff[_idx], var[_idx]);
74 #define COMPUTE_GMM_REDUCE(_idx) \
75  d = GMMSUB(d, compl[_idx]);
76 
77 static void
78 insertion_sort_topn(ptm_topn_t *topn, int i, int32 d)
79 {
80  ptm_topn_t vtmp;
81  int j;
82 
83  topn[i].score = d;
84  if (i == 0)
85  return;
86  vtmp = topn[i];
87  for (j = i - 1; j >= 0 && d > topn[j].score; j--) {
88  topn[j + 1] = topn[j];
89  }
90  topn[j + 1] = vtmp;
91 }
92 
93 static int
94 eval_topn(ptm_mgau_t *s, int cb, int feat, mfcc_t *z)
95 {
96  ptm_topn_t *topn;
97  int i, ceplen;
98 
99  topn = s->f->topn[cb][feat];
100  ceplen = s->g->featlen[feat];
101 
102  for (i = 0; i < s->max_topn; i++) {
103  mfcc_t *mean, diff[4], sqdiff[4], compl[4]; /* diff, diff^2, component likelihood */
104  mfcc_t *var, d;
105  mfcc_t *obs;
106  int32 cw, j;
107 
108  cw = topn[i].cw;
109  mean = s->g->mean[cb][feat][0] + cw * ceplen;
110  var = s->g->var[cb][feat][0] + cw * ceplen;
111  d = s->g->det[cb][feat][cw];
112  obs = z;
113  for (j = 0; j < ceplen % 4; ++j) {
114  diff[0] = *obs++ - *mean++;
115  sqdiff[0] = MFCCMUL(diff[0], diff[0]);
116  compl[0] = MFCCMUL(sqdiff[0], *var);
117  d = GMMSUB(d, compl[0]);
118  ++var;
119  }
120  /* We could vectorize this but it's unlikely to make much
121  * difference as the outer loop here isn't very big. */
122  for (;j < ceplen; j += 4) {
123  COMPUTE_GMM_MAP(0);
124  COMPUTE_GMM_MAP(1);
125  COMPUTE_GMM_MAP(2);
126  COMPUTE_GMM_MAP(3);
127  COMPUTE_GMM_REDUCE(0);
128  COMPUTE_GMM_REDUCE(1);
129  COMPUTE_GMM_REDUCE(2);
130  COMPUTE_GMM_REDUCE(3);
131  var += 4;
132  obs += 4;
133  mean += 4;
134  }
135  insertion_sort_topn(topn, i, (int32)d);
136  }
137 
138  return topn[0].score;
139 }
140 
141 /* This looks bad, but it actually isn't. Less than 1% of eval_cb's
142  * time is spent doing this. */
143 static void
144 insertion_sort_cb(ptm_topn_t **cur, ptm_topn_t *worst, ptm_topn_t *best,
145  int cw, int32 intd)
146 {
147  for (*cur = worst - 1; *cur >= best && intd >= (*cur)->score; --*cur)
148  memcpy(*cur + 1, *cur, sizeof(**cur));
149  ++*cur;
150  (*cur)->cw = cw;
151  (*cur)->score = intd;
152 }
153 
154 static int
155 eval_cb(ptm_mgau_t *s, int cb, int feat, mfcc_t *z)
156 {
157  ptm_topn_t *worst, *best, *topn;
158  mfcc_t *mean;
159  mfcc_t *var, *det, *detP, *detE;
160  int32 i, ceplen;
161 
162  best = topn = s->f->topn[cb][feat];
163  worst = topn + (s->max_topn - 1);
164  mean = s->g->mean[cb][feat][0];
165  var = s->g->var[cb][feat][0];
166  det = s->g->det[cb][feat];
167  detE = det + s->g->n_density;
168  ceplen = s->g->featlen[feat];
169 
170  for (detP = det; detP < detE; ++detP) {
171  mfcc_t diff[4], sqdiff[4], compl[4]; /* diff, diff^2, component likelihood */
172  mfcc_t d, thresh;
173  mfcc_t *obs;
174  ptm_topn_t *cur;
175  int32 cw, j;
176 
177  d = *detP;
178  thresh = (mfcc_t) worst->score; /* Avoid int-to-float conversions */
179  obs = z;
180  cw = (int)(detP - det);
181 
182  /* Unroll the loop starting with the first dimension(s). In
183  * theory this might be a bit faster if this Gaussian gets
184  * "knocked out" by C0. In practice not. */
185  for (j = 0; (j < ceplen % 4) && (d >= thresh); ++j) {
186  diff[0] = *obs++ - *mean++;
187  sqdiff[0] = MFCCMUL(diff[0], diff[0]);
188  compl[0] = MFCCMUL(sqdiff[0], *var++);
189  d = GMMSUB(d, compl[0]);
190  }
191  /* Now do 4 dimensions at a time. You'd think that GCC would
192  * vectorize this? Apparently not. And it's right, because
193  * that won't make this any faster, at least on x86-64. */
194  for (; j < ceplen && d >= thresh; j += 4) {
195  COMPUTE_GMM_MAP(0);
196  COMPUTE_GMM_MAP(1);
197  COMPUTE_GMM_MAP(2);
198  COMPUTE_GMM_MAP(3);
199  COMPUTE_GMM_REDUCE(0);
200  COMPUTE_GMM_REDUCE(1);
201  COMPUTE_GMM_REDUCE(2);
202  COMPUTE_GMM_REDUCE(3);
203  var += 4;
204  obs += 4;
205  mean += 4;
206  }
207  if (j < ceplen) {
208  /* terminated early, so not in topn */
209  mean += (ceplen - j);
210  var += (ceplen - j);
211  continue;
212  }
213  if (d < thresh)
214  continue;
215  for (i = 0; i < s->max_topn; i++) {
216  /* already there, so don't need to insert */
217  if (topn[i].cw == cw)
218  break;
219  }
220  if (i < s->max_topn)
221  continue; /* already there. Don't insert */
222  insertion_sort_cb(&cur, worst, best, cw, (int32)d);
223  }
224 
225  return best->score;
226 }
227 
231 static int
232 ptm_mgau_codebook_eval(ptm_mgau_t *s, mfcc_t **z, int frame)
233 {
234  int i, j;
235 
236  /* First evaluate top-N from previous frame. */
237  for (i = 0; i < s->g->n_mgau; ++i)
238  for (j = 0; j < s->g->n_feat; ++j)
239  eval_topn(s, i, j, z[j]);
240 
241  /* If frame downsampling is in effect, possibly do nothing else. */
242  if (frame % s->ds_ratio)
243  return 0;
244 
245  /* Evaluate remaining codebooks. */
246  for (i = 0; i < s->g->n_mgau; ++i) {
247  if (bitvec_is_clear(s->f->mgau_active, i))
248  continue;
249  for (j = 0; j < s->g->n_feat; ++j) {
250  eval_cb(s, i, j, z[j]);
251  }
252  }
253  return 0;
254 }
255 
265 static int
266 ptm_mgau_codebook_norm(ptm_mgau_t *s, mfcc_t **z, int frame)
267 {
268  int i, j;
269 
270  for (j = 0; j < s->g->n_feat; ++j) {
271  int32 norm = WORST_SCORE;
272  for (i = 0; i < s->g->n_mgau; ++i) {
273  if (bitvec_is_clear(s->f->mgau_active, i))
274  continue;
275  if (norm < s->f->topn[i][j][0].score >> SENSCR_SHIFT)
276  norm = s->f->topn[i][j][0].score >> SENSCR_SHIFT;
277  }
278  assert(norm != WORST_SCORE);
279  for (i = 0; i < s->g->n_mgau; ++i) {
280  int32 k;
281  if (bitvec_is_clear(s->f->mgau_active, i))
282  continue;
283  for (k = 0; k < s->max_topn; ++k) {
284  s->f->topn[i][j][k].score >>= SENSCR_SHIFT;
285  s->f->topn[i][j][k].score -= norm;
286  s->f->topn[i][j][k].score = -s->f->topn[i][j][k].score;
287  if (s->f->topn[i][j][k].score > MAX_NEG_ASCR)
288  s->f->topn[i][j][k].score = MAX_NEG_ASCR;
289  }
290  }
291  }
292 
293  return 0;
294 }
295 
296 static int
297 ptm_mgau_calc_cb_active(ptm_mgau_t *s, uint8 *senone_active,
298  int32 n_senone_active, int compallsen)
299 {
300  int i, lastsen;
301 
302  if (compallsen) {
303  bitvec_set_all(s->f->mgau_active, s->g->n_mgau);
304  return 0;
305  }
306  bitvec_clear_all(s->f->mgau_active, s->g->n_mgau);
307  for (lastsen = i = 0; i < n_senone_active; ++i) {
308  int sen = senone_active[i] + lastsen;
309  int cb = s->sen2cb[sen];
310  bitvec_set(s->f->mgau_active, cb);
311  lastsen = sen;
312  }
313  E_DEBUG(1, ("Active codebooks:"));
314  for (i = 0; i < s->g->n_mgau; ++i) {
315  if (bitvec_is_clear(s->f->mgau_active, i))
316  continue;
317  E_DEBUGCONT(1, (" %d", i));
318  }
319  E_DEBUGCONT(1, ("\n"));
320  return 0;
321 }
322 
326 static int
327 ptm_mgau_senone_eval(ptm_mgau_t *s, int16 *senone_scores,
328  uint8 *senone_active, int32 n_senone_active,
329  int compall)
330 {
331  int i, lastsen, bestscore;
332 
333  memset(senone_scores, 0, s->n_sen * sizeof(*senone_scores));
334  /* FIXME: This is the non-cache-efficient way to do this. We want
335  * to evaluate one codeword at a time but this requires us to have
336  * a reverse codebook to senone mapping, which we don't have
337  * (yet), since different codebooks have different top-N
338  * codewords. */
339  if (compall)
340  n_senone_active = s->n_sen;
341  bestscore = 0x7fffffff;
342  for (lastsen = i = 0; i < n_senone_active; ++i) {
343  int sen, f, cb;
344  int ascore;
345 
346  if (compall)
347  sen = i;
348  else
349  sen = senone_active[i] + lastsen;
350  lastsen = sen;
351  cb = s->sen2cb[sen];
352 
353  if (bitvec_is_clear(s->f->mgau_active, cb)) {
354  int j;
355  /* Because senone_active is deltas we can't really "knock
356  * out" senones from pruned codebooks, and in any case,
357  * it wouldn't make any difference to the search code,
358  * which doesn't expect senone_active to change. */
359  for (f = 0; f < s->g->n_feat; ++f) {
360  for (j = 0; j < s->max_topn; ++j) {
361  s->f->topn[cb][f][j].score = MAX_NEG_ASCR;
362  }
363  }
364  }
365  /* For each feature, log-sum codeword scores + mixw to get
366  * feature density, then sum (multiply) to get ascore */
367  ascore = 0;
368  for (f = 0; f < s->g->n_feat; ++f) {
369  ptm_topn_t *topn;
370  int j, fden = 0;
371  topn = s->f->topn[cb][f];
372  for (j = 0; j < s->max_topn; ++j) {
373  int mixw;
374  /* Find mixture weight for this codeword. */
375  if (s->mixw_cb) {
376  int dcw = s->mixw[f][topn[j].cw][sen/2];
377  dcw = (dcw & 1) ? dcw >> 4 : dcw & 0x0f;
378  mixw = s->mixw_cb[dcw];
379  }
380  else {
381  mixw = s->mixw[f][topn[j].cw][sen];
382  }
383  if (j == 0)
384  fden = mixw + topn[j].score;
385  else
386  fden = fast_logmath_add(s->lmath_8b, fden,
387  mixw + topn[j].score);
388  E_DEBUG(3, ("fden[%d][%d] l+= %d + %d = %d\n",
389  sen, f, mixw, topn[j].score, fden));
390  }
391  ascore += fden;
392  }
393  if (ascore < bestscore) bestscore = ascore;
394  senone_scores[sen] = ascore;
395  }
396  /* Normalize the scores again (finishing the job we started above
397  * in ptm_mgau_codebook_eval...) */
398  for (i = 0; i < s->n_sen; ++i) {
399  senone_scores[i] -= bestscore;
400  }
401 
402  return 0;
403 }
404 
408 int32
410  int16 *senone_scores,
411  uint8 *senone_active,
412  int32 n_senone_active,
413  mfcc_t ** featbuf, int32 frame,
414  int32 compallsen)
415 {
416  ptm_mgau_t *s = (ptm_mgau_t *)ps;
417  int fast_eval_idx;
418 
419  /* Find the appropriate frame in the rotating history buffer
420  * corresponding to the requested input frame. No bounds checking
421  * is done here, which just means you'll get semi-random crap if
422  * you request a frame in the future or one that's too far in the
423  * past. Since the history buffer is just used for fast match
424  * that might not be fatal. */
425  fast_eval_idx = frame % s->n_fast_hist;
426  s->f = s->hist + fast_eval_idx;
427  /* Compute the top-N codewords for every codebook, unless this
428  * is a past frame, in which case we already have them (we
429  * hope!) */
430  if (frame >= ps_mgau_base(ps)->frame_idx) {
431  ptm_fast_eval_t *lastf;
432  /* Get the previous frame's top-N information (on the
433  * first frame of the input this is just all WORST_DIST,
434  * no harm in that) */
435  if (fast_eval_idx == 0)
436  lastf = s->hist + s->n_fast_hist - 1;
437  else
438  lastf = s->hist + fast_eval_idx - 1;
439  /* Copy in initial top-N info */
440  memcpy(s->f->topn[0][0], lastf->topn[0][0],
441  s->g->n_mgau * s->g->n_feat * s->max_topn * sizeof(ptm_topn_t));
442  /* Generate initial active codebook list (this might not be
443  * necessary) */
444  ptm_mgau_calc_cb_active(s, senone_active, n_senone_active, compallsen);
445  /* Now evaluate top-N, prune, and evaluate remaining codebooks. */
446  ptm_mgau_codebook_eval(s, featbuf, frame);
447  ptm_mgau_codebook_norm(s, featbuf, frame);
448  }
449  /* Evaluate intersection of active senones and active codebooks. */
450  ptm_mgau_senone_eval(s, senone_scores, senone_active,
451  n_senone_active, compallsen);
452 
453  return 0;
454 }
455 
456 static int32
457 read_sendump(ptm_mgau_t *s, bin_mdef_t *mdef, char const *file)
458 {
459  FILE *fp;
460  char line[1000];
461  int32 i, n, r, c;
462  int32 do_swap, do_mmap;
463  size_t offset;
464  int n_clust = 0;
465  int n_feat = s->g->n_feat;
466  int n_density = s->g->n_density;
467  int n_sen = bin_mdef_n_sen(mdef);
468  int n_bits = 8;
469 
470  s->n_sen = n_sen; /* FIXME: Should have been done earlier */
471  do_mmap = cmd_ln_boolean_r(s->config, "-mmap");
472 
473  if ((fp = fopen(file, "rb")) == NULL)
474  return -1;
475 
476  E_INFO("Loading senones from dump file %s\n", file);
477  /* Read title size, title */
478  if (fread(&n, sizeof(int32), 1, fp) != 1) {
479  E_ERROR_SYSTEM("Failed to read title size from %s", file);
480  goto error_out;
481  }
482  /* This is extremely bogus */
483  do_swap = 0;
484  if (n < 1 || n > 999) {
485  SWAP_INT32(&n);
486  if (n < 1 || n > 999) {
487  E_ERROR("Title length %x in dump file %s out of range\n", n, file);
488  goto error_out;
489  }
490  do_swap = 1;
491  }
492  if (fread(line, sizeof(char), n, fp) != n) {
493  E_ERROR_SYSTEM("Cannot read title");
494  goto error_out;
495  }
496  if (line[n - 1] != '\0') {
497  E_ERROR("Bad title in dump file\n");
498  goto error_out;
499  }
500  E_INFO("%s\n", line);
501 
502  /* Read header size, header */
503  if (fread(&n, sizeof(n), 1, fp) != 1) {
504  E_ERROR_SYSTEM("Failed to read header size from %s", file);
505  goto error_out;
506  }
507  if (do_swap) SWAP_INT32(&n);
508  if (fread(line, sizeof(char), n, fp) != n) {
509  E_ERROR_SYSTEM("Cannot read header");
510  goto error_out;
511  }
512  if (line[n - 1] != '\0') {
513  E_ERROR("Bad header in dump file\n");
514  goto error_out;
515  }
516 
517  /* Read other header strings until string length = 0 */
518  for (;;) {
519  if (fread(&n, sizeof(n), 1, fp) != 1) {
520  E_ERROR_SYSTEM("Failed to read header string size from %s", file);
521  goto error_out;
522  }
523  if (do_swap) SWAP_INT32(&n);
524  if (n == 0)
525  break;
526  if (fread(line, sizeof(char), n, fp) != n) {
527  E_ERROR_SYSTEM("Cannot read header");
528  goto error_out;
529  }
530  /* Look for a cluster count, if present */
531  if (!strncmp(line, "feature_count ", strlen("feature_count "))) {
532  n_feat = atoi(line + strlen("feature_count "));
533  }
534  if (!strncmp(line, "mixture_count ", strlen("mixture_count "))) {
535  n_density = atoi(line + strlen("mixture_count "));
536  }
537  if (!strncmp(line, "model_count ", strlen("model_count "))) {
538  n_sen = atoi(line + strlen("model_count "));
539  }
540  if (!strncmp(line, "cluster_count ", strlen("cluster_count "))) {
541  n_clust = atoi(line + strlen("cluster_count "));
542  }
543  if (!strncmp(line, "cluster_bits ", strlen("cluster_bits "))) {
544  n_bits = atoi(line + strlen("cluster_bits "));
545  }
546  }
547 
548  /* Defaults for #rows, #columns in mixw array. */
549  c = n_sen;
550  r = n_density;
551  if (n_clust == 0) {
552  /* Older mixw files have them here, and they might be padded. */
553  if (fread(&r, sizeof(r), 1, fp) != 1) {
554  E_ERROR_SYSTEM("Cannot read #rows");
555  goto error_out;
556  }
557  if (do_swap) SWAP_INT32(&r);
558  if (fread(&c, sizeof(c), 1, fp) != 1) {
559  E_ERROR_SYSTEM("Cannot read #columns");
560  goto error_out;
561  }
562  if (do_swap) SWAP_INT32(&c);
563  E_INFO("Rows: %d, Columns: %d\n", r, c);
564  }
565 
566  if (n_feat != s->g->n_feat) {
567  E_ERROR("Number of feature streams mismatch: %d != %d\n",
568  n_feat, s->g->n_feat);
569  goto error_out;
570  }
571  if (n_density != s->g->n_density) {
572  E_ERROR("Number of densities mismatch: %d != %d\n",
573  n_density, s->g->n_density);
574  goto error_out;
575  }
576  if (n_sen != s->n_sen) {
577  E_ERROR("Number of senones mismatch: %d != %d\n",
578  n_sen, s->n_sen);
579  goto error_out;
580  }
581 
582  if (!((n_clust == 0) || (n_clust == 15) || (n_clust == 16))) {
583  E_ERROR("Cluster count must be 0, 15, or 16\n");
584  goto error_out;
585  }
586  if (n_clust == 15)
587  ++n_clust;
588 
589  if (!((n_bits == 8) || (n_bits == 4))) {
590  E_ERROR("Cluster count must be 4 or 8\n");
591  goto error_out;
592  }
593 
594  if (do_mmap) {
595  E_INFO("Using memory-mapped I/O for senones\n");
596  }
597  offset = ftell(fp);
598 
599  /* Allocate memory for pdfs (or memory map them) */
600  if (do_mmap) {
601  s->sendump_mmap = mmio_file_read(file);
602  /* Get cluster codebook if any. */
603  if (n_clust) {
604  s->mixw_cb = ((uint8 *) mmio_file_ptr(s->sendump_mmap)) + offset;
605  offset += n_clust;
606  }
607  }
608  else {
609  /* Get cluster codebook if any. */
610  if (n_clust) {
611  s->mixw_cb = ckd_calloc(1, n_clust);
612  if (fread(s->mixw_cb, 1, n_clust, fp) != (size_t) n_clust) {
613  E_ERROR("Failed to read %d bytes from sendump\n", n_clust);
614  goto error_out;
615  }
616  }
617  }
618 
619  /* Set up pointers, or read, or whatever */
620  if (s->sendump_mmap) {
621  s->mixw = ckd_calloc_2d(n_feat, n_density, sizeof(*s->mixw));
622  for (n = 0; n < n_feat; n++) {
623  int step = c;
624  if (n_bits == 4)
625  step = (step + 1) / 2;
626  for (i = 0; i < r; i++) {
627  s->mixw[n][i] = ((uint8 *) mmio_file_ptr(s->sendump_mmap)) + offset;
628  offset += step;
629  }
630  }
631  }
632  else {
633  s->mixw = ckd_calloc_3d(n_feat, n_density, n_sen, sizeof(***s->mixw));
634  /* Read pdf values and ids */
635  for (n = 0; n < n_feat; n++) {
636  int step = c;
637  if (n_bits == 4)
638  step = (step + 1) / 2;
639  for (i = 0; i < r; i++) {
640  if (fread(s->mixw[n][i], sizeof(***s->mixw), step, fp)
641  != (size_t) step) {
642  E_ERROR("Failed to read %d bytes from sendump\n", step);
643  goto error_out;
644  }
645  }
646  }
647  }
648 
649  fclose(fp);
650  return 0;
651 error_out:
652  fclose(fp);
653  return -1;
654 }
655 
656 static int32
657 read_mixw(ptm_mgau_t * s, char const *file_name, double SmoothMin)
658 {
659  char **argname, **argval;
660  char eofchk;
661  FILE *fp;
662  int32 byteswap, chksum_present;
663  uint32 chksum;
664  float32 *pdf;
665  int32 i, f, c, n;
666  int32 n_sen;
667  int32 n_feat;
668  int32 n_comp;
669  int32 n_err;
670 
671  E_INFO("Reading mixture weights file '%s'\n", file_name);
672 
673  if ((fp = fopen(file_name, "rb")) == NULL)
674  E_FATAL_SYSTEM("Failed to open mixture file '%s' for reading", file_name);
675 
676  /* Read header, including argument-value info and 32-bit byteorder magic */
677  if (bio_readhdr(fp, &argname, &argval, &byteswap) < 0)
678  E_FATAL("Failed to read header from '%s'\n", file_name);
679 
680  /* Parse argument-value list */
681  chksum_present = 0;
682  for (i = 0; argname[i]; i++) {
683  if (strcmp(argname[i], "version") == 0) {
684  if (strcmp(argval[i], MGAU_MIXW_VERSION) != 0)
685  E_WARN("Version mismatch(%s): %s, expecting %s\n",
686  file_name, argval[i], MGAU_MIXW_VERSION);
687  }
688  else if (strcmp(argname[i], "chksum0") == 0) {
689  chksum_present = 1; /* Ignore the associated value */
690  }
691  }
692  bio_hdrarg_free(argname, argval);
693  argname = argval = NULL;
694 
695  chksum = 0;
696 
697  /* Read #senones, #features, #codewords, arraysize */
698  if ((bio_fread(&n_sen, sizeof(int32), 1, fp, byteswap, &chksum) != 1)
699  || (bio_fread(&n_feat, sizeof(int32), 1, fp, byteswap, &chksum) !=
700  1)
701  || (bio_fread(&n_comp, sizeof(int32), 1, fp, byteswap, &chksum) !=
702  1)
703  || (bio_fread(&n, sizeof(int32), 1, fp, byteswap, &chksum) != 1)) {
704  E_FATAL("bio_fread(%s) (arraysize) failed\n", file_name);
705  }
706  if (n_feat != s->g->n_feat)
707  E_FATAL("#Features streams(%d) != %d\n", n_feat, s->g->n_feat);
708  if (n != n_sen * n_feat * n_comp) {
709  E_FATAL
710  ("%s: #float32s(%d) doesn't match header dimensions: %d x %d x %d\n",
711  file_name, i, n_sen, n_feat, n_comp);
712  }
713 
714  /* n_sen = number of mixture weights per codeword, which is
715  * fixed at the number of senones since we have only one codebook.
716  */
717  s->n_sen = n_sen;
718 
719  /* Quantized mixture weight arrays. */
720  s->mixw = ckd_calloc_3d(s->g->n_feat, s->g->n_density,
721  n_sen, sizeof(***s->mixw));
722 
723  /* Temporary structure to read in floats before conversion to (int32) logs3 */
724  pdf = (float32 *) ckd_calloc(n_comp, sizeof(float32));
725 
726  /* Read senone probs data, normalize, floor, convert to logs3, truncate to 8 bits */
727  n_err = 0;
728  for (i = 0; i < n_sen; i++) {
729  for (f = 0; f < n_feat; f++) {
730  if (bio_fread((void *) pdf, sizeof(float32),
731  n_comp, fp, byteswap, &chksum) != n_comp) {
732  E_FATAL("bio_fread(%s) (arraydata) failed\n", file_name);
733  }
734 
735  /* Normalize and floor */
736  if (vector_sum_norm(pdf, n_comp) <= 0.0)
737  n_err++;
738  vector_floor(pdf, n_comp, SmoothMin);
739  vector_sum_norm(pdf, n_comp);
740 
741  /* Convert to LOG, quantize, and transpose */
742  for (c = 0; c < n_comp; c++) {
743  int32 qscr;
744 
745  qscr = -logmath_log(s->lmath_8b, pdf[c]);
746  if ((qscr > MAX_NEG_MIXW) || (qscr < 0))
747  qscr = MAX_NEG_MIXW;
748  s->mixw[f][c][i] = qscr;
749  }
750  }
751  }
752  if (n_err > 0)
753  E_WARN("Weight normalization failed for %d mixture weights components\n", n_err);
754 
755  ckd_free(pdf);
756 
757  if (chksum_present)
758  bio_verify_chksum(fp, byteswap, chksum);
759 
760  if (fread(&eofchk, 1, 1, fp) == 1)
761  E_FATAL("More data than expected in %s\n", file_name);
762 
763  fclose(fp);
764 
765  E_INFO("Read %d x %d x %d mixture weights\n", n_sen, n_feat, n_comp);
766  return n_sen;
767 }
768 
769 ps_mgau_t *
770 ptm_mgau_init(acmod_t *acmod, bin_mdef_t *mdef)
771 {
772  ptm_mgau_t *s;
773  ps_mgau_t *ps;
774  char const *sendump_path;
775  int i;
776 
777  s = ckd_calloc(1, sizeof(*s));
778  s->config = acmod->config;
779 
780  s->lmath = logmath_retain(acmod->lmath);
781  /* Log-add table. */
782  s->lmath_8b = logmath_init(logmath_get_base(acmod->lmath), SENSCR_SHIFT, TRUE);
783  if (s->lmath_8b == NULL)
784  goto error_out;
785  /* Ensure that it is only 8 bits wide so that fast_logmath_add() works. */
786  if (logmath_get_width(s->lmath_8b) != 1) {
787  E_ERROR("Log base %f is too small to represent add table in 8 bits\n",
788  logmath_get_base(s->lmath_8b));
789  goto error_out;
790  }
791 
792  /* Read means and variances. */
793  if ((s->g = gauden_init(cmd_ln_str_r(s->config, "_mean"),
794  cmd_ln_str_r(s->config, "_var"),
795  cmd_ln_float32_r(s->config, "-varfloor"),
796  s->lmath)) == NULL) {
797  E_ERROR("Failed to read means and variances\n");
798  goto error_out;
799  }
800 
801  /* We only support 256 codebooks or less (like 640k or 2GB, this
802  * should be enough for anyone) */
803  if (s->g->n_mgau > 256) {
804  E_INFO("Number of codebooks exceeds 256: %d\n", s->g->n_mgau);
805  goto error_out;
806  }
807  if (s->g->n_mgau != bin_mdef_n_ciphone(mdef)) {
808  E_INFO("Number of codebooks doesn't match number of ciphones, doesn't look like PTM: %d != %d\n", s->g->n_mgau, bin_mdef_n_ciphone(mdef));
809  goto error_out;
810  }
811  /* Verify n_feat and veclen, against acmod. */
812  if (s->g->n_feat != feat_dimension1(acmod->fcb)) {
813  E_ERROR("Number of streams does not match: %d != %d\n",
814  s->g->n_feat, feat_dimension1(acmod->fcb));
815  goto error_out;
816  }
817  for (i = 0; i < s->g->n_feat; ++i) {
818  if (s->g->featlen[i] != feat_dimension2(acmod->fcb, i)) {
819  E_ERROR("Dimension of stream %d does not match: %d != %d\n",
820  s->g->featlen[i], feat_dimension2(acmod->fcb, i));
821  goto error_out;
822  }
823  }
824  /* Read mixture weights. */
825  if ((sendump_path = cmd_ln_str_r(s->config, "_sendump"))) {
826  if (read_sendump(s, acmod->mdef, sendump_path) < 0) {
827  goto error_out;
828  }
829  }
830  else {
831  if (read_mixw(s, cmd_ln_str_r(s->config, "_mixw"),
832  cmd_ln_float32_r(s->config, "-mixwfloor")) < 0) {
833  goto error_out;
834  }
835  }
836  s->ds_ratio = cmd_ln_int32_r(s->config, "-ds");
837  s->max_topn = cmd_ln_int32_r(s->config, "-topn");
838  E_INFO("Maximum top-N: %d\n", s->max_topn);
839 
840  /* Assume mapping of senones to their base phones, though this
841  * will become more flexible in the future. */
842  s->sen2cb = ckd_calloc(s->n_sen, sizeof(*s->sen2cb));
843  for (i = 0; i < s->n_sen; ++i)
844  s->sen2cb[i] = bin_mdef_sen2cimap(acmod->mdef, i);
845 
846  /* Allocate fast-match history buffers. We need enough for the
847  * phoneme lookahead window, plus the current frame, plus one for
848  * good measure? (FIXME: I don't remember why) */
849  s->n_fast_hist = cmd_ln_int32_r(s->config, "-pl_window") + 2;
850  s->hist = ckd_calloc(s->n_fast_hist, sizeof(*s->hist));
851  /* s->f will be a rotating pointer into s->hist. */
852  s->f = s->hist;
853  for (i = 0; i < s->n_fast_hist; ++i) {
854  int j, k, m;
855  /* Top-N codewords for every codebook and feature. */
856  s->hist[i].topn = ckd_calloc_3d(s->g->n_mgau, s->g->n_feat,
857  s->max_topn, sizeof(ptm_topn_t));
858  /* Initialize them to sane (yet arbitrary) defaults. */
859  for (j = 0; j < s->g->n_mgau; ++j) {
860  for (k = 0; k < s->g->n_feat; ++k) {
861  for (m = 0; m < s->max_topn; ++m) {
862  s->hist[i].topn[j][k][m].cw = m;
863  s->hist[i].topn[j][k][m].score = WORST_DIST;
864  }
865  }
866  }
867  /* Active codebook mapping (just codebook, not features,
868  at least not yet) */
869  s->hist[i].mgau_active = bitvec_alloc(s->g->n_mgau);
870  /* Start with them all on, prune them later. */
871  bitvec_set_all(s->hist[i].mgau_active, s->g->n_mgau);
872  }
873 
874  ps = (ps_mgau_t *)s;
875  ps->vt = &ptm_mgau_funcs;
876  return ps;
877 error_out:
878  ptm_mgau_free(ps_mgau_base(s));
879  return NULL;
880 }
881 
882 int
883 ptm_mgau_mllr_transform(ps_mgau_t *ps,
884  ps_mllr_t *mllr)
885 {
886  ptm_mgau_t *s = (ptm_mgau_t *)ps;
887  return gauden_mllr_transform(s->g, mllr, s->config);
888 }
889 
890 void
891 ptm_mgau_free(ps_mgau_t *ps)
892 {
893  int i;
894  ptm_mgau_t *s = (ptm_mgau_t *)ps;
895 
896  logmath_free(s->lmath);
897  logmath_free(s->lmath_8b);
898  if (s->sendump_mmap) {
899  ckd_free_2d(s->mixw);
900  mmio_file_unmap(s->sendump_mmap);
901  }
902  else {
903  ckd_free_3d(s->mixw);
904  }
905  ckd_free(s->sen2cb);
906 
907  for (i = 0; i < s->n_fast_hist; i++) {
908  ckd_free_3d(s->hist[i].topn);
909  bitvec_free(s->hist[i].mgau_active);
910  }
911  ckd_free(s->hist);
912 
913  gauden_free(s->g);
914  ckd_free(s);
915 }
int32 n_density
Number gaussian densities in each codebook-feature stream.
Definition: ms_gauden.h:90
ptm_topn_t *** topn
Top-N for each codebook (mgau x feature x topn)
Definition: ptm_mgau.h:64
void gauden_free(gauden_t *g)
Release memory allocated by gauden_init.
Definition: ms_gauden.c:358
mfcc_t *** det
log(determinant) for each variance vector; actually, log(sqrt(2*pi*det))
Definition: ms_gauden.h:85
uint8 * sen2cb
Senone to codebook mapping.
Definition: ptm_mgau.h:73
logmath_t * lmath
Log-math computation.
Definition: acmod.h:151
int n_fast_hist
Number of past frames tracked.
Definition: ptm_mgau.h:82
gauden_t * g
Set of Gaussians.
Definition: ptm_mgau.h:71
int32 gauden_mllr_transform(gauden_t *s, ps_mllr_t *mllr, cmd_ln_t *config)
Transform Gaussians according to an MLLR matrix (or, eventually, more).
Definition: ms_gauden.c:509
gauden_t * gauden_init(char const *meanfile, char const *varfile, float32 varfloor, logmath_t *lmath)
Read mixture gaussian codebooks from the given files.
Definition: ms_gauden.c:311
int ptm_mgau_frame_eval(ps_mgau_t *s, int16 *senone_scores, uint8 *senone_active, int32 n_senone_active, mfcc_t **featbuf, int32 frame, int32 compallsen)
Compute senone scores for the active senones.
Definition: ptm_mgau.c:409
Fast phonetically-tied mixture evaluation.
cmd_ln_t * config
Configuration.
Definition: acmod.h:150
#define WORST_SCORE
Large &quot;bad&quot; score.
Definition: hmm.h:84
int32 * featlen
feature length for each feature
Definition: ms_gauden.h:91
#define GMMSUB(a, b)
Subtract GMM component b (assumed to be positive) and saturate.
int32 n_mgau
Number codebooks.
Definition: ms_gauden.h:88
Feature space linear transform structure.
Definition: acmod.h:82
#define SENSCR_SHIFT
Shift count for senone scores.
Definition: hmm.h:73
mfcc_t **** mean
mean[codebook][feature][codeword] vector
Definition: ms_gauden.h:83
feat_t * fcb
Dynamic feature computation.
Definition: acmod.h:156
cmd_ln_t * config
Configuration parameters.
Definition: ptm_mgau.h:70
uint8 *** mixw
Mixture weight distributions by feature, codeword, senone.
Definition: ptm_mgau.h:74
ptm_fast_eval_t * hist
Fast evaluation info for past frames.
Definition: ptm_mgau.h:80
int32 n_feat
Number feature streams in each codebook.
Definition: ms_gauden.h:89
ptm_fast_eval_t * f
Fast eval info for current frame.
Definition: ptm_mgau.h:81
int32 cw
Codeword index.
Definition: ptm_mgau.h:59
int32 score
Score.
Definition: ptm_mgau.h:60
ps_mgaufuncs_t * vt
vtable of mgau functions.
Definition: acmod.h:114
LOGMATH_INLINE int fast_logmath_add(logmath_t *lmath, int mlx, int mly)
Quickly log-add two negated log probabilities.
bin_mdef_t * mdef
Model definition.
Definition: acmod.h:159
bitvec_t * mgau_active
Set of active codebooks.
Definition: ptm_mgau.h:65
#define MAX_NEG_ASCR
Maximum negated acoustic score value.
int32 n_sen
Number of senones.
Definition: ptm_mgau.h:72
#define MAX_NEG_MIXW
Maximum negated mixture weight value.
Acoustic model structure.
Definition: acmod.h:148
mfcc_t **** var
like mean; diagonal covariance vector only
Definition: ms_gauden.h:84
Common code shared between SC and PTM (tied-state) models.