/*
* Find Viterbi alignment.
*/
static void align_utt (char *sent, /* In: Reference transcript */
float32 **mfc, /* In: MFC cepstra for input utterance */
int32 nfr, /* In: #frames of input */
char *ctlspec, /* In: Utt specifiction from control file */
char *uttid) /* In: Utterance id, for logging and other use */
{
static float32 **feat = NULL;
static int32 w;
static int32 topn;
static gauden_dist_t ***dist;
static int32 *senscr;
static s3senid_t *sen_active;
static int8 *mgau_active;
static char *s2stsegdir;
static char *stsegdir;
static char *phsegdir;
static char *wdsegdir;
int32 i, s, sid, gid, n_sen_active, best;
char *arg;
align_stseg_t *stseg;
align_phseg_t *phseg;
align_wdseg_t *wdseg;
if (! feat) {
/* One-time allocation of necessary intermediate variables */
/* Allocate space for a feature vector */
feat = (float32 **) ckd_calloc (n_feat, sizeof(float32 *));
for (i = 0; i < n_feat; i++)
feat[i] = (float32 *) ckd_calloc (featlen[i], sizeof(float32));
/* Allocate space for top-N codeword density values in a codebook */
w = feat_window_size (); /* #MFC vectors needed on either side of current
frame to compute one feature vector */
topn = *((int32 *) cmd_ln_access("-topn"));
if (topn > g->n_density) {
E_ERROR("-topn argument (%d) > #density codewords (%d); set to latter\n",
topn, g->n_density);
topn = g->n_density;
}
dist = (gauden_dist_t ***) ckd_calloc_3d (g->n_mgau, n_feat, topn,
sizeof(gauden_dist_t));
/* Space for one frame of senone scores, and per frame active flags */
senscr = (int32 *) ckd_calloc (sen->n_sen, sizeof(int32));
sen_active = (s3senid_t *) ckd_calloc (sen->n_sen, sizeof(s3senid_t));
mgau_active = (int8 *) ckd_calloc (g->n_mgau, sizeof(int8));
/* Note various output directories */
s2stsegdir = NULL;
stsegdir = NULL;
phsegdir = NULL;
wdsegdir = NULL;
if ((arg = (char *) cmd_ln_access ("-s2stsegdir")) != NULL)
s2stsegdir = (char *) ckd_salloc (arg);
if ((arg = (char *) cmd_ln_access ("-stsegdir")) != NULL)
stsegdir = (char *) ckd_salloc (arg);
if ((arg = (char *) cmd_ln_access ("-phsegdir")) != NULL)
phsegdir = (char *) ckd_salloc (arg);
if ((arg = (char *) cmd_ln_access ("-wdsegdir")) != NULL)
wdsegdir = (char *) ckd_salloc (arg);
}
/* HACK HACKA HACK BHIKSHA
if (nfr <= (w<<1)) {
E_ERROR("Utterance %s < %d frames (%d); ignored\n", uttid, (w<<1)+1, nfr);
return;
}
END HACK HACKA HACK */
cyctimer_reset_all ();
counter_reset_all ();
timing_reset (tm_utt);
timing_start (tm_utt);
cyctimer_resume (tmr_utt);
/* AGC and CMN */
arg = (char *) cmd_ln_access ("-cmn");
if (strcmp (arg, "current") == 0)
norm_mean (mfc-4, nfr+8, cepsize); /* -4 HACKA HACK */
arg = (char *) cmd_ln_access ("-agc");
if (strcmp (arg, "max") == 0)
agc_max (mfc, nfr);
if (align_build_sent_hmm (sent) != 0) {
align_destroy_sent_hmm ();
cyctimer_pause (tmr_utt);
E_ERROR("No sentence HMM; no alignment for %s\n", uttid);
return;
}
align_start_utt (uttid);
/*
* A feature vector for frame f depends on input MFC vectors [f-w..f+w]. Hence
* the feature vector corresponding to the first w and last w input frames is
* undefined. We define them by simply replicating the first and last true
* feature vectors (presumably silence regions).
*/
for (i = 0; i < nfr; i++) {
cyctimer_resume (tmr_utt);
/* Compute feature vector for current frame from input speech cepstra */
/* HACK HACKA HACK BHIKSHA
if (i < w)
feat_cep2feat (mfc+w, feat);
else if (i >= nfr-w)
feat_cep2feat (mfc+(nfr-w-1), feat);
else
END HACK HACKA HACK */
feat_cep2feat (mfc+i, feat);
/*
* Evaluate gaussian density codebooks and senone scores for input codeword.
* Evaluate only active codebooks and senones.
*/
/* Obtain active senone flags */
cyctimer_resume (tmr_senone);
align_sen_active (sen_active, sen->n_sen);
/* Flag all CI senones to active if interpolating */
if (interp) {
for (s = 0; s < mdef->n_ci_sen; s++)
sen_active[s] = 1;
}
/* Turn active flags into list (for faster access) */
n_sen_active = 0;
for (s = 0; s < mdef->n_sen; s++) {
if (sen_active[s])
sen_active[n_sen_active++] = s;
}
cyctimer_pause (tmr_senone);
/* Flag all active mixture-gaussian codebooks */
cyctimer_resume (tmr_gauden);
for (gid = 0; gid < g->n_mgau; gid++)
mgau_active[gid] = 0;
for (s = 0; s < n_sen_active; s++) {
sid = sen_active[s];
mgau_active[sen->mgau[sid]] = 1;
}
/* Compute topn gaussian density values (for active codebooks) */
for (gid = 0; gid < g->n_mgau; gid++)
if (mgau_active[gid])
gauden_dist (g, gid, topn, feat, dist[gid]);
cyctimer_pause (tmr_gauden);
/* Evaluate active senones */
cyctimer_resume (tmr_senone);
best = (int32) 0x80000000;
for (s = 0; s < n_sen_active; s++) {
sid = sen_active[s];
senscr[sid] = senone_eval (sen, sid, dist[sen->mgau[sid]], topn);
if (best < senscr[sid])
best = senscr[sid];
}
if (interp) {
for (s = 0; s < n_sen_active; s++) {
if ((sid = sen_active[s]) >= mdef->n_ci_sen)
interp_cd_ci (interp, senscr, sid, mdef->cd2cisen[sid]);
}
}
/* Normalize senone scores (interpolation above can only lower best score) */
for (s = 0; s < n_sen_active; s++) {
sid = sen_active[s];
senscr[sid] -= best;
}
senscale[i] = best;
cyctimer_pause (tmr_senone);
/* Step alignment one frame forward */
cyctimer_resume (tmr_align);
align_frame (senscr);
cyctimer_pause (tmr_align);
cyctimer_pause (tmr_utt);
}
timing_stop (tm_utt);
printf ("\n");
/* Wind up alignment for this utterance */
if (align_end_utt (&stseg, &phseg, &wdseg) < 0)
E_ERROR("Final state not reached; no alignment for %s\n\n", uttid);
else {
if (s2stsegdir)
write_s2stseg (s2stsegdir, stseg, uttid, ctlspec);
if (stsegdir)
write_stseg (stsegdir, stseg, uttid, ctlspec);
if (phsegdir)
write_phseg (phsegdir, phseg, uttid, ctlspec);
if (wdsegdir)
write_wdseg (wdsegdir, wdseg, uttid, ctlspec);
if (outsentfp)
write_outsent (outsentfp, wdseg, uttid);
}
align_destroy_sent_hmm ();
cyctimer_print_all_norm (stdout, nfr*0.01, tmr_utt);
counter_print_all (stdout);
printf("EXECTIME: %5d frames, %7.2f sec CPU, %6.2f xRT; %7.2f sec elapsed, %6.2f xRT\n",
nfr,
tm_utt->t_cpu, tm_utt->t_cpu * 100.0 / nfr,
tm_utt->t_elapsed, tm_utt->t_elapsed * 100.0 / nfr);
tot_nfr += nfr;
}
/*
* Find Viterbi alignment.
*/
static void
align_utt(char *sent, /* In: Reference transcript */
int32 nfr, /* In: #frames of input */
char *ctlspec, /* In: Utt specifiction from control file */
char *uttid)
{ /* In: Utterance id, for logging and other use */
int32 i;
align_stseg_t *stseg;
align_phseg_t *phseg;
align_wdseg_t *wdseg;
int32 w;
w = feat_window_size(kbcore_fcb(kbc)); /* #MFC vectors needed on either side of current
frame to compute one feature vector */
if (nfr <= (w << 1)) {
E_ERROR("Utterance %s < %d frames (%d); ignored\n", uttid,
(w << 1) + 1, nfr);
return;
}
ptmr_reset_all(timers);
ptmr_reset(&tm_utt);
ptmr_start(&tm_utt);
ptmr_reset(&tm_ovrhd);
ptmr_start(&tm_ovrhd);
ptmr_start(timers + tmr_utt);
if (align_build_sent_hmm(sent, cmd_ln_int32_r(kbc->config, "-insert_sil")) != 0) {
align_destroy_sent_hmm();
ptmr_stop(timers + tmr_utt);
E_ERROR("No sentence HMM; no alignment for %s\n", uttid);
return;
}
align_start_utt(uttid);
for (i = 0; i < nfr; i++) {
ptmr_start(timers + tmr_utt);
/* Obtain active senone flags */
ptmr_start(timers + tmr_gauden);
ptmr_start(timers + tmr_senone);
align_sen_active(ascr->sen_active, ascr->n_sen);
/* Bah, there ought to be a function for this. */
if (kbc->ms_mgau) {
ms_cont_mgau_frame_eval(ascr,
kbc->ms_mgau,
kbc->mdef, feat[i], i);
}
else if (kbc->s2_mgau) {
s2_semi_mgau_frame_eval(kbc->s2_mgau,
ascr, fastgmm, feat[i],
i);
}
else if (kbc->mgau) {
approx_cont_mgau_ci_eval(kbcore_svq(kbc),
kbcore_gs(kbc),
kbcore_mgau(kbc),
fastgmm,
kbc->mdef,
feat[i][0],
ascr->cache_ci_senscr[0],
&(ascr->cache_best_list[0]), i,
kbcore_logmath(kbc));
approx_cont_mgau_frame_eval(kbcore_mdef(kbc),
kbcore_svq(kbc),
kbcore_gs(kbc),
kbcore_mgau(kbc),
fastgmm, ascr,
feat[i][0], i,
ascr->
cache_ci_senscr[0],
&tm_ovrhd,
kbcore_logmath(kbc));
}
ptmr_stop(timers + tmr_gauden);
ptmr_stop(timers + tmr_senone);
/* Step alignment one frame forward */
ptmr_start(timers + tmr_align);
align_frame(ascr->senscr);
ptmr_stop(timers + tmr_align);
ptmr_stop(timers + tmr_utt);
}
ptmr_stop(&tm_utt);
ptmr_stop(&tm_ovrhd);
printf("\n");
/* Wind up alignment for this utterance */
if (align_end_utt(&stseg, &phseg, &wdseg) < 0)
E_ERROR("Final state not reached; no alignment for %s\n\n", uttid);
else {
if (s2stsegdir)
write_s2stseg(s2stsegdir, stseg, uttid, ctlspec, cmd_ln_boolean_r(kbc->config, "-s2cdsen"));
if (stsegdir)
write_stseg(stsegdir, stseg, uttid, ctlspec);
if (phsegdir)
write_phseg(phsegdir, phseg, uttid, ctlspec);
if (phlabdir)
write_phlab(phlabdir, phseg, uttid, ctlspec, cmd_ln_int32_r(kbc->config, "-frate"));
if (wdsegdir)
write_wdseg(wdsegdir, wdseg, uttid, ctlspec);
if (outsentfp)
write_outsent(outsentfp, wdseg, uttid);
if (outctlfp)
write_outctl(outctlfp, ctlspec);
}
align_destroy_sent_hmm();
ptmr_print_all(stdout, timers, nfr * 0.1);
printf
("EXECTIME: %5d frames, %7.2f sec CPU, %6.2f xRT; %7.2f sec elapsed, %6.2f xRT\n",
nfr, tm_utt.t_cpu, tm_utt.t_cpu * 100.0 / nfr, tm_utt.t_elapsed,
tm_utt.t_elapsed * 100.0 / nfr);
tot_nfr += nfr;
}
int32
viterbi_update(float64 *log_forw_prob,
vector_t **feature,
uint32 n_obs,
state_t *state_seq,
uint32 n_state,
model_inventory_t *inv,
float64 a_beam,
float32 spthresh,
s3phseg_t *phseg,
int32 mixw_reest,
int32 tmat_reest,
int32 mean_reest,
int32 var_reest,
int32 pass2var,
int32 var_is_full,
FILE *pdumpfh,
feat_t *fcb)
{
float64 *scale = NULL;
float64 **dscale = NULL;
float64 **active_alpha;
uint32 **active_astate;
uint32 **bp;
uint32 *n_active_astate;
gauden_t *g; /* Gaussian density parameters and
reestimation sums */
float32 ***mixw; /* all mixing weights */
float64 ***now_den = NULL; /* Short for den[t] */
uint32 ***now_den_idx = NULL;/* Short for den_idx[t] */
uint32 *active_cb;
uint32 n_active_cb;
float32 **tacc; /* Transition matrix reestimation sum accumulators
for the utterance. */
float32 ***wacc; /* mixing weight reestimation sum accumulators
for the utterance. */
float32 ***denacc = NULL; /* mean/var reestimation accumulators for time t */
size_t denacc_size; /* Total size of data references in denacc. Allows
for quick clears between time frames */
uint32 n_lcl_cb;
uint32 *cb_inv;
uint32 i, j, q;
int32 t;
uint32 n_feat;
uint32 n_density;
uint32 n_top;
int ret;
timing_t *fwd_timer = NULL;
timing_t *rstu_timer = NULL;
timing_t *gau_timer = NULL;
timing_t *rsts_timer = NULL;
timing_t *rstf_timer = NULL;
float64 log_fp; /* accumulator for the log of the probability
* of observing the input given the model */
uint32 max_n_next = 0;
uint32 n_cb;
static float64 *p_op = NULL;
static float64 *p_ci_op = NULL;
static float64 **d_term = NULL;
static float64 **d_term_ci = NULL;
/* caller must ensure that there is some non-zero amount
of work to be done here */
assert(n_obs > 0);
assert(n_state > 0);
/* Get the forward estimation CPU timer */
fwd_timer = timing_get("fwd");
/* Get the per utterance reestimation CPU timer */
rstu_timer = timing_get("rstu");
/* Get the Gaussian density evaluation CPU timer */
gau_timer = timing_get("gau");
/* Get the per state reestimation CPU timer */
rsts_timer = timing_get("rsts");
/* Get the per frame reestimation CPU timer */
rstf_timer = timing_get("rstf");
g = inv->gauden;
n_feat = gauden_n_feat(g);
n_density = gauden_n_density(g);
n_top = gauden_n_top(g);
n_cb = gauden_n_mgau(g);
if (p_op == NULL) {
p_op = ckd_calloc(n_feat, sizeof(float64));
p_ci_op = ckd_calloc(n_feat, sizeof(float64));
}
if (d_term == NULL) {
d_term = (float64 **)ckd_calloc_2d(n_feat, n_top, sizeof(float64));
d_term_ci = (float64 **)ckd_calloc_2d(n_feat, n_top, sizeof(float64));
}
scale = (float64 *)ckd_calloc(n_obs, sizeof(float64));
dscale = (float64 **)ckd_calloc(n_obs, sizeof(float64 *));
n_active_astate = (uint32 *)ckd_calloc(n_obs, sizeof(uint32));
active_alpha = (float64 **)ckd_calloc(n_obs, sizeof(float64 *));
active_astate = (uint32 **)ckd_calloc(n_obs, sizeof(uint32 *));
active_cb = ckd_calloc(2*n_state, sizeof(uint32));
bp = (uint32 **)ckd_calloc(n_obs, sizeof(uint32 *));
/* Run forward algorithm, which has embedded Viterbi. */
if (fwd_timer)
timing_start(fwd_timer);
ret = forward(active_alpha, active_astate, n_active_astate, bp,
scale, dscale,
feature, n_obs, state_seq, n_state,
inv, a_beam, phseg, 0);
/* Dump a phoneme segmentation if requested */
if (cmd_ln_str("-outphsegdir")) {
const char *phsegdir;
char *segfn, *uttid;
phsegdir = cmd_ln_str("-outphsegdir");
uttid = (cmd_ln_int32("-outputfullpath")
? corpus_utt_full_name() : corpus_utt());
segfn = ckd_calloc(strlen(phsegdir) + 1
+ strlen(uttid)
+ strlen(".phseg") + 1, 1);
strcpy(segfn, phsegdir);
strcat(segfn, "/");
strcat(segfn, uttid);
strcat(segfn, ".phseg");
write_phseg(segfn, inv, state_seq, active_astate, n_active_astate,
n_state, n_obs, active_alpha, scale, bp);
ckd_free(segfn);
}
if (fwd_timer)
timing_stop(fwd_timer);
if (ret != S3_SUCCESS) {
/* Some problem with the utterance, release per utterance storage and
* forget about adding the utterance accumulators to the global accumulators */
goto all_done;
}
mixw = inv->mixw;
if (mixw_reest) {
/* Need to reallocate mixing accumulators for utt */
if (inv->l_mixw_acc) {
ckd_free_3d((void ***)inv->l_mixw_acc);
inv->l_mixw_acc = NULL;
}
inv->l_mixw_acc = (float32 ***)ckd_calloc_3d(inv->n_mixw_inverse,
n_feat,
n_density,
sizeof(float32));
}
wacc = inv->l_mixw_acc;
n_lcl_cb = inv->n_cb_inverse;
cb_inv = inv->cb_inverse;
/* Allocate local accumulators for mean, variance reestimation
sums if necessary */
gauden_alloc_l_acc(g, n_lcl_cb,
mean_reest, var_reest,
var_is_full);
if (tmat_reest) {
if (inv->l_tmat_acc) {
ckd_free_2d((void **)inv->l_tmat_acc);
inv->l_tmat_acc = NULL;
}
for (i = 0; i < n_state; i++) {
if (state_seq[i].n_next > max_n_next)
max_n_next = state_seq[i].n_next;
}
inv->l_tmat_acc = (float32 **)ckd_calloc_2d(n_state,
max_n_next,
sizeof(float32));
}
/* transition matrix reestimation sum accumulators
for the utterance */
tacc = inv->l_tmat_acc;
n_active_cb = 0;
now_den = (float64 ***)ckd_calloc_3d(n_lcl_cb,
n_feat,
n_top,
sizeof(float64));
now_den_idx = (uint32 ***)ckd_calloc_3d(n_lcl_cb,
n_feat,
n_top,
sizeof(uint32));
if (mean_reest || var_reest) {
/* allocate space for the per frame density counts */
denacc = (float32 ***)ckd_calloc_3d(n_lcl_cb,
n_feat,
n_density,
sizeof(float32));
/* # of bytes required to store all weighted vectors */
denacc_size = n_lcl_cb * n_feat * n_density * sizeof(float32);
}
else {
denacc = NULL;
denacc_size = 0;
}
/* Okay now run through the backtrace and accumulate counts. */
/* Find the non-emitting ending state */
for (q = 0; q < n_active_astate[n_obs-1]; ++q) {
if (active_astate[n_obs-1][q] == n_state-1)
break;
}
if (q == n_active_astate[n_obs-1]) {
E_ERROR("Failed to align audio to trancript: final state of the search is not reached\n");
ret = S3_ERROR;
goto all_done;
}
for (t = n_obs-1; t >= 0; --t) {
uint32 l_cb;
uint32 l_ci_cb;
float64 op, p_reest_term;
uint32 prev;
j = active_astate[t][q];
/* Follow any non-emitting states at time t first. */
while (state_seq[j].mixw == TYING_NON_EMITTING) {
prev = active_astate[t][bp[t][q]];
#if VITERBI_DEBUG
printf("Following non-emitting state at time %d, %u => %u\n",
t, j, prev);
#endif
/* Backtrace and accumulate transition counts. */
if (tmat_reest) {
assert(tacc != NULL);
tacc[prev][j - prev] += 1.0;
}
q = bp[t][q];
j = prev;
}
/* Now accumulate statistics for the real state. */
l_cb = state_seq[j].l_cb;
l_ci_cb = state_seq[j].l_ci_cb;
n_active_cb = 0;
if (gau_timer)
timing_start(gau_timer);
gauden_compute_log(now_den[l_cb],
now_den_idx[l_cb],
feature[t],
g,
state_seq[j].cb,
NULL);
active_cb[n_active_cb++] = l_cb;
if (l_cb != l_ci_cb) {
gauden_compute_log(now_den[l_ci_cb],
now_den_idx[l_ci_cb],
feature[t],
g,
state_seq[j].ci_cb,
NULL);
active_cb[n_active_cb++] = l_ci_cb;
}
gauden_scale_densities_bwd(now_den, now_den_idx,
&dscale[t],
active_cb, n_active_cb, g);
assert(state_seq[j].mixw != TYING_NON_EMITTING);
/* Now calculate mixture densities. */
/* This is the normalizer sum_m c_{jm} p(o_t|\lambda_{jm}) */
op = gauden_mixture(now_den[l_cb], now_den_idx[l_cb],
mixw[state_seq[j].mixw], g);
if (gau_timer)
timing_stop(gau_timer);
if (rsts_timer)
timing_start(rsts_timer);
/* Make up this bogus value to be consistent with backward.c */
p_reest_term = 1.0 / op;
/* Compute the output probability excluding the contribution
* of each feature stream. i.e. p_op[0] is the output
* probability excluding feature stream 0 */
partial_op(p_op,
op,
now_den[l_cb],
now_den_idx[l_cb],
mixw[state_seq[j].mixw],
n_feat,
n_top);
/* compute the probability of each (of possibly topn) density */
den_terms(d_term,
p_reest_term,
p_op,
now_den[l_cb],
now_den_idx[l_cb],
mixw[state_seq[j].mixw],
n_feat,
n_top);
if (l_cb != l_ci_cb) {
/* For each feature stream f, compute:
* sum_k(mixw[f][k] den[f][k])
* and store the results in p_ci_op */
partial_ci_op(p_ci_op,
now_den[l_ci_cb],
now_den_idx[l_ci_cb],
mixw[state_seq[j].ci_mixw],
n_feat,
n_top);
/* For each feature stream and density compute the terms:
* w[f][k] den[f][k] / sum_k(w[f][k] den[f][k]) * post_j
* and store results in d_term_ci */
den_terms_ci(d_term_ci,
1.0, /* post_j = 1.0 */
p_ci_op,
now_den[l_ci_cb],
now_den_idx[l_ci_cb],
mixw[state_seq[j].ci_mixw],
n_feat,
n_top);
}
/* accumulate the probability for each density in the mixing
* weight reestimation accumulators */
if (mixw_reest) {
accum_den_terms(wacc[state_seq[j].l_mixw], d_term,
now_den_idx[l_cb], n_feat, n_top);
/* check if mixw and ci_mixw are different to avoid
* doubling the EM counts in a CI run. */
if (state_seq[j].mixw != state_seq[j].ci_mixw) {
if (n_cb < inv->n_mixw) {
/* semi-continuous, tied mixture, and discrete case */
accum_den_terms(wacc[state_seq[j].l_ci_mixw], d_term,
now_den_idx[l_cb], n_feat, n_top);
}
else {
/* continuous case */
accum_den_terms(wacc[state_seq[j].l_ci_mixw], d_term_ci,
now_den_idx[l_ci_cb], n_feat, n_top);
}
}
}
/* accumulate the probability for each density in the
* density reestimation accumulators */
if (mean_reest || var_reest) {
accum_den_terms(denacc[l_cb], d_term,
now_den_idx[l_cb], n_feat, n_top);
if (l_cb != l_ci_cb) {
accum_den_terms(denacc[l_ci_cb], d_term_ci,
now_den_idx[l_ci_cb], n_feat, n_top);
}
}
if (rsts_timer)
timing_stop(rsts_timer);
/* Note that there is only one state/frame so this is kind of
redundant */
if (rstf_timer)
timing_start(rstf_timer);
if (mean_reest || var_reest) {
/* Update the mean and variance reestimation accumulators */
if (pdumpfh)
fprintf(pdumpfh, "time %d:\n", t);
accum_gauden(denacc,
cb_inv,
n_lcl_cb,
feature[t],
now_den_idx,
g,
mean_reest,
var_reest,
pass2var,
inv->l_mixw_acc,
var_is_full,
pdumpfh,
fcb);
memset(&denacc[0][0][0], 0, denacc_size);
}
if (rstf_timer)
timing_stop(rstf_timer);
if (t > 0) {
prev = active_astate[t-1][bp[t][q]];
#if VITERBI_DEBUG
printf("Backtrace at time %d, %u => %u\n",
t, j, prev);
#endif
/* Backtrace and accumulate transition counts. */
if (tmat_reest) {
assert(tacc != NULL);
tacc[prev][j-prev] += 1.0;
}
q = bp[t][q];
j = prev;
}
}
/* If no error was found, add the resulting utterance reestimation
* accumulators to the global reestimation accumulators */
if (rstu_timer)
timing_start(rstu_timer);
accum_global(inv, state_seq, n_state,
mixw_reest, tmat_reest, mean_reest, var_reest,
var_is_full);
if (rstu_timer)
timing_stop(rstu_timer);
/* Find the final state */
for (i = 0; i < n_active_astate[n_obs-1]; ++i) {
if (active_astate[n_obs-1][i] == n_state-1)
break;
}
/* Calculate log[ p( O | \lambda ) ] */
assert(active_alpha[n_obs-1][i] > 0);
log_fp = log(active_alpha[n_obs-1][i]);
for (t = 0; t < n_obs; t++) {
assert(scale[t] > 0);
log_fp -= log(scale[t]);
for (j = 0; j < inv->gauden->n_feat; j++) {
log_fp += dscale[t][j];
}
}
*log_forw_prob = log_fp;
all_done:
ckd_free((void *)scale);
for (i = 0; i < n_obs; i++) {
if (dscale[i])
ckd_free((void *)dscale[i]);
}
ckd_free((void **)dscale);
ckd_free(n_active_astate);
for (i = 0; i < n_obs; i++) {
ckd_free((void *)active_alpha[i]);
ckd_free((void *)active_astate[i]);
ckd_free((void *)bp[i]);
}
ckd_free((void *)active_alpha);
ckd_free((void *)active_astate);
ckd_free((void *)active_cb);
if (denacc)
ckd_free_3d((void ***)denacc);
if (now_den)
ckd_free_3d((void ***)now_den);
if (now_den_idx)
ckd_free_3d((void ***)now_den_idx);
if (ret != S3_SUCCESS)
E_ERROR("%s ignored\n", corpus_utt_brief_name());
return ret;
}
int32
baum_welch_update(float64 *log_forw_prob,
vector_t **feature,
uint32 n_obs,
state_t *state,
uint32 n_state,
model_inventory_t *inv,
float64 a_beam,
float64 b_beam,
float32 spthresh,
s3phseg_t *phseg,
int32 mixw_reest,
int32 tmat_reest,
int32 mean_reest,
int32 var_reest,
int32 pass2var,
int32 var_is_full,
FILE *pdumpfh,
bw_timers_t *timers,
feat_t *fcb)
{
float64 *scale = NULL;
float64 **dscale = NULL;
float64 **active_alpha;
uint32 **active_astate;
uint32 **bp;
uint32 *n_active_astate;
float64 log_fp; /* accumulator for the log of the probability
* of observing the input given the model */
uint32 t; /* time */
int ret;
uint32 i,j;
/* caller must ensure that there is some non-zero amount
of work to be done here */
assert(n_obs > 0);
assert(n_state > 0);
scale = (float64 *)ckd_calloc(n_obs, sizeof(float64));
dscale = (float64 **)ckd_calloc(n_obs, sizeof(float64 *));
n_active_astate = (uint32 *)ckd_calloc(n_obs, sizeof(uint32));
active_alpha = (float64 **)ckd_calloc(n_obs, sizeof(float64 *));
active_astate = (uint32 **)ckd_calloc(n_obs, sizeof(uint32 *));
bp = (uint32 **)ckd_calloc(n_obs, sizeof(uint32 *));
/* Compute the scaled alpha variable and scale factors
* for all states and time subject to the pruning constraints */
if (timers)
ptmr_start(&timers->fwd_timer);
/*
* Debug?
* E_INFO("Before Forward search\n");
*/
ret = forward(active_alpha, active_astate, n_active_astate, bp,
scale, dscale,
feature, n_obs, state, n_state,
inv, a_beam, phseg, timers, 0);
#if BW_DEBUG
for (i=0 ; i < n_obs; i++) {
E_INFO("Number of active states %d at time %d\n",n_active_astate[i],i);
E_INFO("Scale of time %d is %e \n",i,scale[i]);
for(j=0 ; j < n_active_astate[i]; j++) {
E_INFO("Active state: %d Active alpha: %e\n",active_astate[i][j], active_alpha[i][j]);
}
}
i=0;
j=0;
#endif
/* Dump a phoneme segmentation if requested */
if (cmd_ln_str("-outphsegdir")) {
const char *phsegdir;
char *segfn, *uttid;
phsegdir = cmd_ln_str("-outphsegdir");
uttid = (cmd_ln_int32("-outputfullpath")
? corpus_utt_full_name() : corpus_utt());
segfn = ckd_calloc(strlen(phsegdir) + 1
+ strlen(uttid)
+ strlen(".phseg") + 1, 1);
strcpy(segfn, phsegdir);
strcat(segfn, "/");
strcat(segfn, uttid);
strcat(segfn, ".phseg");
write_phseg(segfn, inv, state, active_astate, n_active_astate,
n_state, n_obs, active_alpha, scale, bp);
ckd_free(segfn);
}
if (timers)
ptmr_stop(&timers->fwd_timer);
if (ret != S3_SUCCESS) {
/* Some problem with the utterance, release per utterance storage and
* forget about adding the utterance accumulators to the global accumulators */
goto error;
}
/* Compute the scaled beta variable and update the reestimation
* sums */
if (timers)
ptmr_start(&timers->bwd_timer);
#if BW_DEBUG
E_INFO("Before Backward search\n");
#endif
ret = backward_update(active_alpha, active_astate, n_active_astate, scale, dscale,
feature, n_obs,
state, n_state,
inv, b_beam, spthresh,
mixw_reest, tmat_reest, mean_reest, var_reest, pass2var,
var_is_full, pdumpfh, timers, fcb);
if (timers)
ptmr_stop(&timers->bwd_timer);
if (ret != S3_SUCCESS) {
/* Some problem with the utterance, release per utterance storage and
* forget about adding the utterance accumulators to the global accumulators */
goto error;
}
#if BW_DEBUG
E_INFO("Before Global Accumulation\n");
#endif
/* If no error was found in the forward or backward procedures,
* add the resulting utterance reestimation accumulators to the
* global reestimation accumulators */
if (timers)
ptmr_start(&timers->rstu_timer);
accum_global(inv, state, n_state,
mixw_reest, tmat_reest, mean_reest, var_reest,
var_is_full);
if (timers)
ptmr_stop(&timers->rstu_timer);
for (i = 0; i < n_active_astate[n_obs-1] && active_astate[n_obs-1][i] != (n_state-1); i++);
assert(i < n_active_astate[n_obs-1]);
/* Calculate log[ p( O | \lambda ) ] */
assert(active_alpha[n_obs-1][i] > 0);
log_fp = log(active_alpha[n_obs-1][i]);
for (t = 0; t < n_obs; t++) {
assert(scale[t] > 0);
log_fp -= log(scale[t]);
for (j = 0; j < inv->gauden->n_feat; j++) {
log_fp += dscale[t][j];
}
}
*log_forw_prob = log_fp;
ckd_free((void *)scale);
ckd_free(n_active_astate);
for (i = 0; i < n_obs; i++) {
ckd_free((void *)active_alpha[i]);
ckd_free((void *)active_astate[i]);
ckd_free((void *)dscale[i]);
ckd_free((void *)bp[i]);
}
ckd_free((void *)active_alpha);
ckd_free((void *)active_astate);
ckd_free((void **)dscale);
ckd_free(bp);
return S3_SUCCESS;
error:
ckd_free((void *)scale);
for (i = 0; i < n_obs; i++) {
if (dscale[i])
ckd_free((void *)dscale[i]);
}
ckd_free((void **)dscale);
ckd_free(n_active_astate);
for (i = 0; i < n_obs; i++) {
ckd_free((void *)active_alpha[i]);
ckd_free((void *)active_astate[i]);
ckd_free((void *)bp[i]);
}
ckd_free((void *)active_alpha);
ckd_free((void *)active_astate);
ckd_free(bp);
E_ERROR("%s ignored\n", corpus_utt_brief_name());
return S3_ERROR;
}
