/* -*- c-basic-offset: 4; indent-tabs-mode: nil -*- */ /* ==================================================================== * Copyright (c) 1999-2010 Carnegie Mellon University. All rights * reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * * This work was supported in part by funding from the Defense Advanced * Research Projects Agency and the National Science Foundation of the * United States of America, and the CMU Sphinx Speech Consortium. * * THIS SOFTWARE IS PROVIDED BY CARNEGIE MELLON UNIVERSITY ``AS IS'' AND * ANY EXPRESSED OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, * THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL CARNEGIE MELLON UNIVERSITY * NOR ITS EMPLOYEES BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, * SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT * LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, * DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * * ==================================================================== * */ /* System headers */ #include <stdio.h> #include <stdlib.h> #include <string.h> #include <assert.h> #include <limits.h> #include <math.h> #if defined(__ADSPBLACKFIN__) #elif !defined(_WIN32_WCE) #include <sys/types.h> #endif /* SphinxBase headers */ #include <sphinx_config.h> #include <sphinxbase/cmd_ln.h> #include <sphinxbase/fixpoint.h> #include <sphinxbase/ckd_alloc.h> #include <sphinxbase/bio.h> #include <sphinxbase/err.h> #include <sphinxbase/prim_type.h> /* Local headers */ #include "tied_mgau_common.h" #include "ptm_mgau.h" static ps_mgaufuncs_t ptm_mgau_funcs = { "ptm", ptm_mgau_frame_eval, /* frame_eval */ ptm_mgau_mllr_transform, /* transform */ ptm_mgau_free /* free */ }; #define COMPUTE_GMM_MAP(_idx) \ diff[_idx] = obs[_idx] - mean[_idx]; \ sqdiff[_idx] = MFCCMUL(diff[_idx], diff[_idx]); \ compl[_idx] = MFCCMUL(sqdiff[_idx], var[_idx]); #define COMPUTE_GMM_REDUCE(_idx) \ d = GMMSUB(d, compl[_idx]); static void insertion_sort_topn(ptm_topn_t *topn, int i, int32 d) { ptm_topn_t vtmp; int j; topn[i].score = d; if (i == 0) return; vtmp = topn[i]; for (j = i - 1; j >= 0 && d > topn[j].score; j--) { topn[j + 1] = topn[j]; } topn[j + 1] = vtmp; } static int eval_topn(ptm_mgau_t *s, int cb, int feat, mfcc_t *z) { ptm_topn_t *topn; int i, ceplen; topn = s->f->topn[cb][feat]; ceplen = s->g->featlen[feat]; for (i = 0; i < s->max_topn; i++) { mfcc_t *mean, diff[4], sqdiff[4], compl[4]; /* diff, diff^2, component likelihood */ mfcc_t *var, d; mfcc_t *obs; int32 cw, j; cw = topn[i].cw; mean = s->g->mean[cb][feat][0] + cw * ceplen; var = s->g->var[cb][feat][0] + cw * ceplen; d = s->g->det[cb][feat][cw]; obs = z; for (j = 0; j < ceplen % 4; ++j) { diff[0] = *obs++ - *mean++; sqdiff[0] = MFCCMUL(diff[0], diff[0]); compl[0] = MFCCMUL(sqdiff[0], *var); d = GMMSUB(d, compl[0]); ++var; } /* We could vectorize this but it's unlikely to make much * difference as the outer loop here isn't very big. */ for (;j < ceplen; j += 4) { COMPUTE_GMM_MAP(0); COMPUTE_GMM_MAP(1); COMPUTE_GMM_MAP(2); COMPUTE_GMM_MAP(3); COMPUTE_GMM_REDUCE(0); COMPUTE_GMM_REDUCE(1); COMPUTE_GMM_REDUCE(2); COMPUTE_GMM_REDUCE(3); var += 4; obs += 4; mean += 4; } insertion_sort_topn(topn, i, (int32)d); } return topn[0].score; } /* This looks bad, but it actually isn't. Less than 1% of eval_cb's * time is spent doing this. */ static void insertion_sort_cb(ptm_topn_t **cur, ptm_topn_t *worst, ptm_topn_t *best, int cw, int32 intd) { for (*cur = worst - 1; *cur >= best && intd >= (*cur)->score; --*cur) memcpy(*cur + 1, *cur, sizeof(**cur)); ++*cur; (*cur)->cw = cw; (*cur)->score = intd; } static int eval_cb(ptm_mgau_t *s, int cb, int feat, mfcc_t *z) { ptm_topn_t *worst, *best, *topn; mfcc_t *mean; mfcc_t *var, *det, *detP, *detE; int32 i, ceplen; best = topn = s->f->topn[cb][feat]; worst = topn + (s->max_topn - 1); mean = s->g->mean[cb][feat][0]; var = s->g->var[cb][feat][0]; det = s->g->det[cb][feat]; detE = det + s->g->n_density; ceplen = s->g->featlen[feat]; for (detP = det; detP < detE; ++detP) { mfcc_t diff[4], sqdiff[4], compl[4]; /* diff, diff^2, component likelihood */ mfcc_t d, thresh; mfcc_t *obs; ptm_topn_t *cur; int32 cw, j; d = *detP; thresh = (mfcc_t) worst->score; /* Avoid int-to-float conversions */ obs = z; cw = (int)(detP - det); /* Unroll the loop starting with the first dimension(s). In * theory this might be a bit faster if this Gaussian gets * "knocked out" by C0. In practice not. */ for (j = 0; (j < ceplen % 4) && (d >= thresh); ++j) { diff[0] = *obs++ - *mean++; sqdiff[0] = MFCCMUL(diff[0], diff[0]); compl[0] = MFCCMUL(sqdiff[0], *var++); d = GMMSUB(d, compl[0]); } /* Now do 4 dimensions at a time. You'd think that GCC would * vectorize this? Apparently not. And it's right, because * that won't make this any faster, at least on x86-64. */ for (; j < ceplen && d >= thresh; j += 4) { COMPUTE_GMM_MAP(0); COMPUTE_GMM_MAP(1); COMPUTE_GMM_MAP(2); COMPUTE_GMM_MAP(3); COMPUTE_GMM_REDUCE(0); COMPUTE_GMM_REDUCE(1); COMPUTE_GMM_REDUCE(2); COMPUTE_GMM_REDUCE(3); var += 4; obs += 4; mean += 4; } if (j < ceplen) { /* terminated early, so not in topn */ mean += (ceplen - j); var += (ceplen - j); continue; } if (d < thresh) continue; for (i = 0; i < s->max_topn; i++) { /* already there, so don't need to insert */ if (topn[i].cw == cw) break; } if (i < s->max_topn) continue; /* already there. Don't insert */ insertion_sort_cb(&cur, worst, best, cw, (int32)d); } return best->score; } /** * Compute top-N densities for active codebooks (and prune) */ static int ptm_mgau_codebook_eval(ptm_mgau_t *s, mfcc_t **z, int frame) { int i, j; /* First evaluate top-N from previous frame. */ for (i = 0; i < s->g->n_mgau; ++i) for (j = 0; j < s->g->n_feat; ++j) eval_topn(s, i, j, z[j]); /* If frame downsampling is in effect, possibly do nothing else. */ if (frame % s->ds_ratio) return 0; /* Evaluate remaining codebooks. */ for (i = 0; i < s->g->n_mgau; ++i) { if (bitvec_is_clear(s->f->mgau_active, i)) continue; for (j = 0; j < s->g->n_feat; ++j) { eval_cb(s, i, j, z[j]); } } return 0; } /** * Normalize densities to produce "posterior probabilities", * i.e. things with a reasonable dynamic range, then scale and * clamp them to the acceptable range. This is actually done * solely to ensure that we can use fast_logmath_add(). Note that * unless we share the same normalizer across all codebooks for * each feature stream we get defective scores (that's why these * loops are inside out - doing it per-feature should give us * greater precision). */ static int ptm_mgau_codebook_norm(ptm_mgau_t *s, mfcc_t **z, int frame) { int i, j; for (j = 0; j < s->g->n_feat; ++j) { int32 norm = WORST_SCORE; for (i = 0; i < s->g->n_mgau; ++i) { if (bitvec_is_clear(s->f->mgau_active, i)) continue; if (norm < s->f->topn[i][j][0].score >> SENSCR_SHIFT) norm = s->f->topn[i][j][0].score >> SENSCR_SHIFT; } assert(norm != WORST_SCORE); for (i = 0; i < s->g->n_mgau; ++i) { int32 k; if (bitvec_is_clear(s->f->mgau_active, i)) continue; for (k = 0; k < s->max_topn; ++k) { s->f->topn[i][j][k].score >>= SENSCR_SHIFT; s->f->topn[i][j][k].score -= norm; s->f->topn[i][j][k].score = -s->f->topn[i][j][k].score; if (s->f->topn[i][j][k].score > MAX_NEG_ASCR) s->f->topn[i][j][k].score = MAX_NEG_ASCR; } } } return 0; } static int ptm_mgau_calc_cb_active(ptm_mgau_t *s, uint8 *senone_active, int32 n_senone_active, int compallsen) { int i, lastsen; if (compallsen) { bitvec_set_all(s->f->mgau_active, s->g->n_mgau); return 0; } bitvec_clear_all(s->f->mgau_active, s->g->n_mgau); for (lastsen = i = 0; i < n_senone_active; ++i) { int sen = senone_active[i] + lastsen; int cb = s->sen2cb[sen]; bitvec_set(s->f->mgau_active, cb); lastsen = sen; } E_DEBUG(1, ("Active codebooks:")); for (i = 0; i < s->g->n_mgau; ++i) { if (bitvec_is_clear(s->f->mgau_active, i)) continue; E_DEBUGCONT(1, (" %d", i)); } E_DEBUGCONT(1, ("\n")); return 0; } /** * Compute senone scores from top-N densities for active codebooks. */ static int ptm_mgau_senone_eval(ptm_mgau_t *s, int16 *senone_scores, uint8 *senone_active, int32 n_senone_active, int compall) { int i, lastsen, bestscore; memset(senone_scores, 0, s->n_sen * sizeof(*senone_scores)); /* FIXME: This is the non-cache-efficient way to do this. We want * to evaluate one codeword at a time but this requires us to have * a reverse codebook to senone mapping, which we don't have * (yet), since different codebooks have different top-N * codewords. */ if (compall) n_senone_active = s->n_sen; bestscore = 0x7fffffff; for (lastsen = i = 0; i < n_senone_active; ++i) { int sen, f, cb; int ascore; if (compall) sen = i; else sen = senone_active[i] + lastsen; lastsen = sen; cb = s->sen2cb[sen]; if (bitvec_is_clear(s->f->mgau_active, cb)) { int j; /* Because senone_active is deltas we can't really "knock * out" senones from pruned codebooks, and in any case, * it wouldn't make any difference to the search code, * which doesn't expect senone_active to change. */ for (f = 0; f < s->g->n_feat; ++f) { for (j = 0; j < s->max_topn; ++j) { s->f->topn[cb][f][j].score = MAX_NEG_ASCR; } } } /* For each feature, log-sum codeword scores + mixw to get * feature density, then sum (multiply) to get ascore */ ascore = 0; for (f = 0; f < s->g->n_feat; ++f) { ptm_topn_t *topn; int j, fden = 0; topn = s->f->topn[cb][f]; for (j = 0; j < s->max_topn; ++j) { int mixw; /* Find mixture weight for this codeword. */ if (s->mixw_cb) { int dcw = s->mixw[f][topn[j].cw][sen/2]; dcw = (dcw & 1) ? dcw >> 4 : dcw & 0x0f; mixw = s->mixw_cb[dcw]; } else { mixw = s->mixw[f][topn[j].cw][sen]; } if (j == 0) fden = mixw + topn[j].score; else fden = fast_logmath_add(s->lmath_8b, fden, mixw + topn[j].score); E_DEBUG(3, ("fden[%d][%d] l+= %d + %d = %d\n", sen, f, mixw, topn[j].score, fden)); } ascore += fden; } if (ascore < bestscore) bestscore = ascore; senone_scores[sen] = ascore; } /* Normalize the scores again (finishing the job we started above * in ptm_mgau_codebook_eval...) */ for (i = 0; i < s->n_sen; ++i) { senone_scores[i] -= bestscore; } return 0; } /** * Compute senone scores for the active senones. */ int32 ptm_mgau_frame_eval(ps_mgau_t *ps, int16 *senone_scores, uint8 *senone_active, int32 n_senone_active, mfcc_t ** featbuf, int32 frame, int32 compallsen) { ptm_mgau_t *s = (ptm_mgau_t *)ps; int fast_eval_idx; /* Find the appropriate frame in the rotating history buffer * corresponding to the requested input frame. No bounds checking * is done here, which just means you'll get semi-random crap if * you request a frame in the future or one that's too far in the * past. Since the history buffer is just used for fast match * that might not be fatal. */ fast_eval_idx = frame % s->n_fast_hist; s->f = s->hist + fast_eval_idx; /* Compute the top-N codewords for every codebook, unless this * is a past frame, in which case we already have them (we * hope!) */ if (frame >= ps_mgau_base(ps)->frame_idx) { ptm_fast_eval_t *lastf; /* Get the previous frame's top-N information (on the * first frame of the input this is just all WORST_DIST, * no harm in that) */ if (fast_eval_idx == 0) lastf = s->hist + s->n_fast_hist - 1; else lastf = s->hist + fast_eval_idx - 1; /* Copy in initial top-N info */ memcpy(s->f->topn[0][0], lastf->topn[0][0], s->g->n_mgau * s->g->n_feat * s->max_topn * sizeof(ptm_topn_t)); /* Generate initial active codebook list (this might not be * necessary) */ ptm_mgau_calc_cb_active(s, senone_active, n_senone_active, compallsen); /* Now evaluate top-N, prune, and evaluate remaining codebooks. */ ptm_mgau_codebook_eval(s, featbuf, frame); ptm_mgau_codebook_norm(s, featbuf, frame); } /* Evaluate intersection of active senones and active codebooks. */ ptm_mgau_senone_eval(s, senone_scores, senone_active, n_senone_active, compallsen); return 0; } static int32 read_sendump(ptm_mgau_t *s, bin_mdef_t *mdef, char const *file) { FILE *fp; char line[1000]; int32 i, n, r, c; int32 do_swap, do_mmap; size_t offset; int n_clust = 0; int n_feat = s->g->n_feat; int n_density = s->g->n_density; int n_sen = bin_mdef_n_sen(mdef); int n_bits = 8; s->n_sen = n_sen; /* FIXME: Should have been done earlier */ do_mmap = cmd_ln_boolean_r(s->config, "-mmap"); if ((fp = fopen(file, "rb")) == NULL) return -1; E_INFO("Loading senones from dump file %s\n", file); /* Read title size, title */ if (fread(&n, sizeof(int32), 1, fp) != 1) { E_ERROR_SYSTEM("Failed to read title size from %s", file); goto error_out; } /* This is extremely bogus */ do_swap = 0; if (n < 1 || n > 999) { SWAP_INT32(&n); if (n < 1 || n > 999) { E_ERROR("Title length %x in dump file %s out of range\n", n, file); goto error_out; } do_swap = 1; } if (fread(line, sizeof(char), n, fp) != n) { E_ERROR_SYSTEM("Cannot read title"); goto error_out; } if (line[n - 1] != '\0') { E_ERROR("Bad title in dump file\n"); goto error_out; } E_INFO("%s\n", line); /* Read header size, header */ if (fread(&n, sizeof(n), 1, fp) != 1) { E_ERROR_SYSTEM("Failed to read header size from %s", file); goto error_out; } if (do_swap) SWAP_INT32(&n); if (fread(line, sizeof(char), n, fp) != n) { E_ERROR_SYSTEM("Cannot read header"); goto error_out; } if (line[n - 1] != '\0') { E_ERROR("Bad header in dump file\n"); goto error_out; } /* Read other header strings until string length = 0 */ for (;;) { if (fread(&n, sizeof(n), 1, fp) != 1) { E_ERROR_SYSTEM("Failed to read header string size from %s", file); goto error_out; } if (do_swap) SWAP_INT32(&n); if (n == 0) break; if (fread(line, sizeof(char), n, fp) != n) { E_ERROR_SYSTEM("Cannot read header"); goto error_out; } /* Look for a cluster count, if present */ if (!strncmp(line, "feature_count ", strlen("feature_count "))) { n_feat = atoi(line + strlen("feature_count ")); } if (!strncmp(line, "mixture_count ", strlen("mixture_count "))) { n_density = atoi(line + strlen("mixture_count ")); } if (!strncmp(line, "model_count ", strlen("model_count "))) { n_sen = atoi(line + strlen("model_count ")); } if (!strncmp(line, "cluster_count ", strlen("cluster_count "))) { n_clust = atoi(line + strlen("cluster_count ")); } if (!strncmp(line, "cluster_bits ", strlen("cluster_bits "))) { n_bits = atoi(line + strlen("cluster_bits ")); } } /* Defaults for #rows, #columns in mixw array. */ c = n_sen; r = n_density; if (n_clust == 0) { /* Older mixw files have them here, and they might be padded. */ if (fread(&r, sizeof(r), 1, fp) != 1) { E_ERROR_SYSTEM("Cannot read #rows"); goto error_out; } if (do_swap) SWAP_INT32(&r); if (fread(&c, sizeof(c), 1, fp) != 1) { E_ERROR_SYSTEM("Cannot read #columns"); goto error_out; } if (do_swap) SWAP_INT32(&c); E_INFO("Rows: %d, Columns: %d\n", r, c); } if (n_feat != s->g->n_feat) { E_ERROR("Number of feature streams mismatch: %d != %d\n", n_feat, s->g->n_feat); goto error_out; } if (n_density != s->g->n_density) { E_ERROR("Number of densities mismatch: %d != %d\n", n_density, s->g->n_density); goto error_out; } if (n_sen != s->n_sen) { E_ERROR("Number of senones mismatch: %d != %d\n", n_sen, s->n_sen); goto error_out; } if (!((n_clust == 0) || (n_clust == 15) || (n_clust == 16))) { E_ERROR("Cluster count must be 0, 15, or 16\n"); goto error_out; } if (n_clust == 15) ++n_clust; if (!((n_bits == 8) || (n_bits == 4))) { E_ERROR("Cluster count must be 4 or 8\n"); goto error_out; } if (do_mmap) { E_INFO("Using memory-mapped I/O for senones\n"); } offset = ftell(fp); /* Allocate memory for pdfs (or memory map them) */ if (do_mmap) { s->sendump_mmap = mmio_file_read(file); /* Get cluster codebook if any. */ if (n_clust) { s->mixw_cb = ((uint8 *) mmio_file_ptr(s->sendump_mmap)) + offset; offset += n_clust; } } else { /* Get cluster codebook if any. */ if (n_clust) { s->mixw_cb = ckd_calloc(1, n_clust); if (fread(s->mixw_cb, 1, n_clust, fp) != (size_t) n_clust) { E_ERROR("Failed to read %d bytes from sendump\n", n_clust); goto error_out; } } } /* Set up pointers, or read, or whatever */ if (s->sendump_mmap) { s->mixw = ckd_calloc_2d(n_feat, n_density, sizeof(*s->mixw)); for (n = 0; n < n_feat; n++) { int step = c; if (n_bits == 4) step = (step + 1) / 2; for (i = 0; i < r; i++) { s->mixw[n][i] = ((uint8 *) mmio_file_ptr(s->sendump_mmap)) + offset; offset += step; } } } else { s->mixw = ckd_calloc_3d(n_feat, n_density, n_sen, sizeof(***s->mixw)); /* Read pdf values and ids */ for (n = 0; n < n_feat; n++) { int step = c; if (n_bits == 4) step = (step + 1) / 2; for (i = 0; i < r; i++) { if (fread(s->mixw[n][i], sizeof(***s->mixw), step, fp) != (size_t) step) { E_ERROR("Failed to read %d bytes from sendump\n", step); goto error_out; } } } } fclose(fp); return 0; error_out: fclose(fp); return -1; } static int32 read_mixw(ptm_mgau_t * s, char const *file_name, double SmoothMin) { char **argname, **argval; char eofchk; FILE *fp; int32 byteswap, chksum_present; uint32 chksum; float32 *pdf; int32 i, f, c, n; int32 n_sen; int32 n_feat; int32 n_comp; int32 n_err; E_INFO("Reading mixture weights file '%s'\n", file_name); if ((fp = fopen(file_name, "rb")) == NULL) E_FATAL_SYSTEM("Failed to open mixture file '%s' for reading", file_name); /* Read header, including argument-value info and 32-bit byteorder magic */ if (bio_readhdr(fp, &argname, &argval, &byteswap) < 0) E_FATAL("Failed to read header from '%s'\n", file_name); /* Parse argument-value list */ chksum_present = 0; for (i = 0; argname[i]; i++) { if (strcmp(argname[i], "version") == 0) { if (strcmp(argval[i], MGAU_MIXW_VERSION) != 0) E_WARN("Version mismatch(%s): %s, expecting %s\n", file_name, argval[i], MGAU_MIXW_VERSION); } else if (strcmp(argname[i], "chksum0") == 0) { chksum_present = 1; /* Ignore the associated value */ } } bio_hdrarg_free(argname, argval); argname = argval = NULL; chksum = 0; /* Read #senones, #features, #codewords, arraysize */ if ((bio_fread(&n_sen, sizeof(int32), 1, fp, byteswap, &chksum) != 1) || (bio_fread(&n_feat, sizeof(int32), 1, fp, byteswap, &chksum) != 1) || (bio_fread(&n_comp, sizeof(int32), 1, fp, byteswap, &chksum) != 1) || (bio_fread(&n, sizeof(int32), 1, fp, byteswap, &chksum) != 1)) { E_FATAL("bio_fread(%s) (arraysize) failed\n", file_name); } if (n_feat != s->g->n_feat) E_FATAL("#Features streams(%d) != %d\n", n_feat, s->g->n_feat); if (n != n_sen * n_feat * n_comp) { E_FATAL ("%s: #float32s(%d) doesn't match header dimensions: %d x %d x %d\n", file_name, i, n_sen, n_feat, n_comp); } /* n_sen = number of mixture weights per codeword, which is * fixed at the number of senones since we have only one codebook. */ s->n_sen = n_sen; /* Quantized mixture weight arrays. */ s->mixw = ckd_calloc_3d(s->g->n_feat, s->g->n_density, n_sen, sizeof(***s->mixw)); /* Temporary structure to read in floats before conversion to (int32) logs3 */ pdf = (float32 *) ckd_calloc(n_comp, sizeof(float32)); /* Read senone probs data, normalize, floor, convert to logs3, truncate to 8 bits */ n_err = 0; for (i = 0; i < n_sen; i++) { for (f = 0; f < n_feat; f++) { if (bio_fread((void *) pdf, sizeof(float32), n_comp, fp, byteswap, &chksum) != n_comp) { E_FATAL("bio_fread(%s) (arraydata) failed\n", file_name); } /* Normalize and floor */ if (vector_sum_norm(pdf, n_comp) <= 0.0) n_err++; vector_floor(pdf, n_comp, SmoothMin); vector_sum_norm(pdf, n_comp); /* Convert to LOG, quantize, and transpose */ for (c = 0; c < n_comp; c++) { int32 qscr; qscr = -logmath_log(s->lmath_8b, pdf[c]); if ((qscr > MAX_NEG_MIXW) || (qscr < 0)) qscr = MAX_NEG_MIXW; s->mixw[f][c][i] = qscr; } } } if (n_err > 0) E_WARN("Weight normalization failed for %d mixture weights components\n", n_err); ckd_free(pdf); if (chksum_present) bio_verify_chksum(fp, byteswap, chksum); if (fread(&eofchk, 1, 1, fp) == 1) E_FATAL("More data than expected in %s\n", file_name); fclose(fp); E_INFO("Read %d x %d x %d mixture weights\n", n_sen, n_feat, n_comp); return n_sen; } ps_mgau_t * ptm_mgau_init(acmod_t *acmod, bin_mdef_t *mdef) { ptm_mgau_t *s; ps_mgau_t *ps; char const *sendump_path; int i; s = ckd_calloc(1, sizeof(*s)); s->config = acmod->config; s->lmath = logmath_retain(acmod->lmath); /* Log-add table. */ s->lmath_8b = logmath_init(logmath_get_base(acmod->lmath), SENSCR_SHIFT, TRUE); if (s->lmath_8b == NULL) goto error_out; /* Ensure that it is only 8 bits wide so that fast_logmath_add() works. */ if (logmath_get_width(s->lmath_8b) != 1) { E_ERROR("Log base %f is too small to represent add table in 8 bits\n", logmath_get_base(s->lmath_8b)); goto error_out; } /* Read means and variances. */ if ((s->g = gauden_init(cmd_ln_str_r(s->config, "-mean"), cmd_ln_str_r(s->config, "-var"), cmd_ln_float32_r(s->config, "-varfloor"), s->lmath)) == NULL) goto error_out; /* We only support 256 codebooks or less (like 640k or 2GB, this * should be enough for anyone) */ if (s->g->n_mgau > 256) { E_INFO("Number of codebooks exceeds 256: %d\n", s->g->n_mgau); goto error_out; } if (s->g->n_mgau != bin_mdef_n_ciphone(mdef)) { 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)); goto error_out; } /* Verify n_feat and veclen, against acmod. */ if (s->g->n_feat != feat_dimension1(acmod->fcb)) { E_ERROR("Number of streams does not match: %d != %d\n", s->g->n_feat, feat_dimension1(acmod->fcb)); goto error_out; } for (i = 0; i < s->g->n_feat; ++i) { if (s->g->featlen[i] != feat_dimension2(acmod->fcb, i)) { E_ERROR("Dimension of stream %d does not match: %d != %d\n", s->g->featlen[i], feat_dimension2(acmod->fcb, i)); goto error_out; } } /* Read mixture weights. */ if ((sendump_path = cmd_ln_str_r(s->config, "-sendump"))) { if (read_sendump(s, acmod->mdef, sendump_path) < 0) { goto error_out; } } else { if (read_mixw(s, cmd_ln_str_r(s->config, "-mixw"), cmd_ln_float32_r(s->config, "-mixwfloor")) < 0) { goto error_out; } } s->ds_ratio = cmd_ln_int32_r(s->config, "-ds"); s->max_topn = cmd_ln_int32_r(s->config, "-topn"); E_INFO("Maximum top-N: %d\n", s->max_topn); /* Assume mapping of senones to their base phones, though this * will become more flexible in the future. */ s->sen2cb = ckd_calloc(s->n_sen, sizeof(*s->sen2cb)); for (i = 0; i < s->n_sen; ++i) s->sen2cb[i] = bin_mdef_sen2cimap(acmod->mdef, i); /* Allocate fast-match history buffers. We need enough for the * phoneme lookahead window, plus the current frame, plus one for * good measure? (FIXME: I don't remember why) */ s->n_fast_hist = cmd_ln_int32_r(s->config, "-pl_window") + 2; s->hist = ckd_calloc(s->n_fast_hist, sizeof(*s->hist)); /* s->f will be a rotating pointer into s->hist. */ s->f = s->hist; for (i = 0; i < s->n_fast_hist; ++i) { int j, k, m; /* Top-N codewords for every codebook and feature. */ s->hist[i].topn = ckd_calloc_3d(s->g->n_mgau, s->g->n_feat, s->max_topn, sizeof(ptm_topn_t)); /* Initialize them to sane (yet arbitrary) defaults. */ for (j = 0; j < s->g->n_mgau; ++j) { for (k = 0; k < s->g->n_feat; ++k) { for (m = 0; m < s->max_topn; ++m) { s->hist[i].topn[j][k][m].cw = m; s->hist[i].topn[j][k][m].score = WORST_DIST; } } } /* Active codebook mapping (just codebook, not features, at least not yet) */ s->hist[i].mgau_active = bitvec_alloc(s->g->n_mgau); /* Start with them all on, prune them later. */ bitvec_set_all(s->hist[i].mgau_active, s->g->n_mgau); } ps = (ps_mgau_t *)s; ps->vt = &ptm_mgau_funcs; return ps; error_out: ptm_mgau_free(ps_mgau_base(s)); return NULL; } int ptm_mgau_mllr_transform(ps_mgau_t *ps, ps_mllr_t *mllr) { ptm_mgau_t *s = (ptm_mgau_t *)ps; return gauden_mllr_transform(s->g, mllr, s->config); } void ptm_mgau_free(ps_mgau_t *ps) { int i; ptm_mgau_t *s = (ptm_mgau_t *)ps; logmath_free(s->lmath); logmath_free(s->lmath_8b); if (s->sendump_mmap) { ckd_free_2d(s->mixw); mmio_file_unmap(s->sendump_mmap); } else { ckd_free_3d(s->mixw); } ckd_free(s->sen2cb); for (i = 0; i < s->n_fast_hist; i++) { ckd_free_3d(s->hist[i].topn); bitvec_free(s->hist[i].mgau_active); } ckd_free(s->hist); gauden_free(s->g); ckd_free(s); }