ptm_mgau.c
/* -*- 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;
}
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;
}
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;
}
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;
}
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);
}
gauden_t::n_density
int32 n_density
Number gaussian densities in each codebook-feature stream.
Definition: ms_gauden.h:90
ptm_fast_eval_s::topn
ptm_topn_t *** topn
Top-N for each codebook (mgau x feature x topn)
Definition: ptm_mgau.h:64
gauden_free
void gauden_free(gauden_t *g)
Release memory allocated by gauden_init.
Definition: ms_gauden.c:399
gauden_t::det
mfcc_t *** det
log(determinant) for each variance vector; actually, log(sqrt(2*pi*det))
Definition: ms_gauden.h:85
ptm_mgau_s::sen2cb
uint8 * sen2cb
Senone to codebook mapping.
Definition: ptm_mgau.h:73
acmod_s::lmath
logmath_t * lmath
Log-math computation.
Definition: acmod.h:151
ptm_mgau_s::n_fast_hist
int n_fast_hist
Number of past frames tracked.
Definition: ptm_mgau.h:82
ptm_mgau_s::g
gauden_t * g
Set of Gaussians.
Definition: ptm_mgau.h:71
gauden_mllr_transform
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:550
ptm_fast_eval_s
Definition: ptm_mgau.h:63
gauden_init
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:361
ptm_mgau_frame_eval
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
ptm_mgau.h
Fast phonetically-tied mixture evaluation.
bin_mdef_s
Definition: bin_mdef.h:117
ptm_mgau_s
Definition: ptm_mgau.h:68
acmod_s::config
cmd_ln_t * config
Configuration.
Definition: acmod.h:150
WORST_SCORE
#define WORST_SCORE
Large "bad" score.
Definition: hmm.h:84
gauden_t::featlen
int32 * featlen
feature length for each feature
Definition: ms_gauden.h:91
GMMSUB
#define GMMSUB(a, b)
Subtract GMM component b (assumed to be positive) and saturate.
Definition: tied_mgau_common.h:62
gauden_t::n_mgau
int32 n_mgau
Number codebooks.
Definition: ms_gauden.h:88
ps_mllr_s
Feature space linear transform structure.
Definition: acmod.h:82
SENSCR_SHIFT
#define SENSCR_SHIFT
Shift count for senone scores.
Definition: hmm.h:73
gauden_t::mean
mfcc_t **** mean
mean[codebook][feature][codeword] vector
Definition: ms_gauden.h:83
acmod_s::fcb
feat_t * fcb
Dynamic feature computation.
Definition: acmod.h:156
ptm_mgau_s::config
cmd_ln_t * config
Configuration parameters.
Definition: ptm_mgau.h:70
ptm_mgau_s::mixw
uint8 *** mixw
Mixture weight distributions by feature, codeword, senone.
Definition: ptm_mgau.h:74
ptm_mgau_s::hist
ptm_fast_eval_t * hist
Fast evaluation info for past frames.
Definition: ptm_mgau.h:80
gauden_t::n_feat
int32 n_feat
Number feature streams in each codebook.
Definition: ms_gauden.h:89
ptm_mgau_s::f
ptm_fast_eval_t * f
Fast eval info for current frame.
Definition: ptm_mgau.h:81
ptm_topn_s::cw
int32 cw
Codeword index.
Definition: ptm_mgau.h:59
ptm_topn_s::score
int32 score
Score.
Definition: ptm_mgau.h:60
ps_mgau_s::vt
ps_mgaufuncs_t * vt
vtable of mgau functions.
Definition: acmod.h:114
fast_logmath_add
LOGMATH_INLINE int fast_logmath_add(logmath_t *lmath, int mlx, int mly)
Quickly log-add two negated log probabilities.
Definition: tied_mgau_common.h:103
acmod_s::mdef
bin_mdef_t * mdef
Model definition.
Definition: acmod.h:159
ptm_fast_eval_s::mgau_active
bitvec_t * mgau_active
Set of active codebooks.
Definition: ptm_mgau.h:65
MAX_NEG_ASCR
#define MAX_NEG_ASCR
Maximum negated acoustic score value.
Definition: tied_mgau_common.h:83
ptm_mgau_s::n_sen
int32 n_sen
Number of senones.
Definition: ptm_mgau.h:72
ps_mgaufuncs_s
Definition: acmod.h:98
MAX_NEG_MIXW
#define MAX_NEG_MIXW
Maximum negated mixture weight value.
Definition: tied_mgau_common.h:82
acmod_s
Acoustic model structure.
Definition: acmod.h:148
gauden_t::var
mfcc_t **** var
like mean; diagonal covariance vector only
Definition: ms_gauden.h:84
ps_mgau_s
Definition: acmod.h:113
ptm_topn_s
Definition: ptm_mgau.h:58
tied_mgau_common.h
Common code shared between SC and PTM (tied-state) models.