/**
* @brief Compute a set of Gaussians with no pruning
*
* The calculated scores will be stored to OP_calced_score, with its
* corresponding mixture id to OP_calced_id.
* The number of calculated mixtures is also stored in OP_calced_num.
*
* This can be called from calc_tied_mix() or calc_mix().
*
* @param wrk [i/o] HMM computation work area
* @param g [in] set of Gaussian densities to compute the output probability.
* @param num [in] length of above
* @param last_id [in] ID list of N-best mixture in previous input frame,
* or NULL if not exist
* @param lnum [in] length of last_id
*/
void
gprune_none(HMMWork *wrk, HTK_HMM_Dens **g, int num, int *last_id, int lnum)
{
int i;
HTK_HMM_Dens *dens;
LOGPROB *prob = wrk->OP_calced_score;
int *id = wrk->OP_calced_id;
#ifdef ENABLE_MSD
int valid_dim;
int calced_num;
#endif
#ifdef ENABLE_MSD
valid_dim = 0;
for(i=0; i<wrk->OP_veclen; i++) {
if (wrk->OP_vec[i] != LZERO) valid_dim++;
}
calced_num = 0;
for(i=0; i<num; i++) {
dens = *(g++);
if (dens->meanlen != valid_dim) continue;
if (dens->meanlen == 0) {
*(prob++) = 0.0;
} else {
*(prob++) = compute_g_base(wrk, dens);
}
*(id++) = i;
calced_num++;
}
if (calced_num == 0) {
jlog("Error: MSD: input data dim = %d / %d, but no Gaussian defined for it\n", valid_dim, wrk->OP_veclen);
jlog("Error: MSD: Gaussian dimensions in this mixture:");
for(i=0;i<num;i++) {
jlog(" %d", g[i]->meanlen);
}
jlog("\n");
}
wrk->OP_calced_num = calced_num;
#else
for(i=0; i<num; i++) {
dens = *(g++);
*(prob++) = compute_g_base(wrk, dens);
*(id++) = i;
}
wrk->OP_calced_num = num;
#endif
}
/**
* @brief Compute a set of Gaussians with safe pruning.
*
* If the N-best mixtures in the previous frame is specified in @a last_id,
* They are first computed to set the initial threshold.
* After that, the rest of the Gaussians will be computed with the thresholds
* to drop unpromising Gaussians from computation at early stage
* of likelihood computation. If the computation of a Gaussian reached to
* the end, the threshold will be updated to always hold the likelihood of
* current N-best score.
*
* The calculated scores will be stored to OP_calced_score, with its
* corresponding mixture id to OP_calced_id. These are done by calling
* cache_push().
* The number of calculated mixtures is also stored in OP_calced_num.
*
* This can be called from calc_tied_mix() or calc_mix().
*
* @param wrk [i/o] HMM computation work area
* @param g [in] set of Gaussian densities to compute the output probability
* @param gnum [in] length of above
* @param last_id [in] ID list of N-best mixture in previous input frame,
* or NULL if not exist
* @param lnum [in] length of last_id
*/
void
gprune_safe(HMMWork *wrk, HTK_HMM_Dens **g, int gnum, int *last_id, int lnum)
{
int i, j, num = 0;
LOGPROB score, thres;
if (last_id != NULL) { /* compute them first to form threshold */
/* 1. calculate first $OP_gprune_num and set initial threshold */
for (j=0; j<lnum; j++) {
i = last_id[j];
score = compute_g_base(wrk, g[i]);
num = cache_push(wrk, i, score, num);
wrk->mixcalced[i] = TRUE; /* mark them as calculated */
}
thres = wrk->OP_calced_score[num-1];
/* 2. calculate the rest with pruning*/
for (i = 0; i < gnum; i++) {
/* skip calced ones in 1. */
if (wrk->mixcalced[i]) {
wrk->mixcalced[i] = FALSE;
continue;
}
/* compute with safe pruning */
score = compute_g_safe(wrk, g[i], thres);
if (score <= thres) continue;
num = cache_push(wrk, i, score, num);
thres = wrk->OP_calced_score[num-1];
}
} else { /* in case the last_id not available */
/* not tied-mixture, or at the first 0 frame */
thres = LOG_ZERO;
for (i = 0; i < gnum; i++) {
if (num < wrk->OP_gprune_num) {
score = compute_g_base(wrk, g[i]);
} else {
score = compute_g_safe(wrk, g[i], thres);
if (score <= thres) continue;
}
num = cache_push(wrk, i, score, num);
thres = wrk->OP_calced_score[num-1];
}
}
wrk->OP_calced_num = num;
}
/**
* @brief Compute a set of Gaussians with heuristic pruning.
*
* If the N-best mixtures in the previous frame is specified in @a last_id,
* They are first computed to get the maximum value for each dimension.
* After that, the rest of the Gaussians will be computed using the maximum
* values as heuristics of uncomputed dimensions to drop unpromising
* Gaussians from computation at early stage
* of likelihood computation. If the @a last_id is not specified (typically
* at the first frame of the input), a safe pruning as same as one in
* gprune_safe.c will be applied.
*
* The calculated scores will be stored to OP_calced_score, with its
* corresponding mixture id to OP_calced_id. These are done by calling
* cache_push().
* The number of calculated mixtures is also stored in OP_calced_num.
*
* This can be called from calc_tied_mix() or calc_mix().
*
* @param wrk [i/o] HMM computation work area
* @param g [in] set of Gaussian densities to compute the output probability
* @param gnum [in] length of above
* @param last_id [in] ID list of N-best mixture in previous input frame,
* or NULL if not exist
* @param lnum [in] length of last_id
*/
void
gprune_heu(HMMWork *wrk, HTK_HMM_Dens **g, int gnum, int *last_id, int lnum)
{
int i, j, num = 0;
LOGPROB score, thres;
if (last_id != NULL) { /* compute them first to form thresholds */
/* 1. clear backmax */
init_backmax(wrk);
/* 2. calculate first $OP_gprune_num with setting max for each dimension */
for (j=0; j<lnum; j++) {
i = last_id[j];
score = compute_g_heu_updating(wrk, g[i]);
num = cache_push(wrk, i, score, num);
wrk->mixcalced[i] = TRUE; /* mark them as calculated */
}
/* 3. set backmax for each dimension */
make_backmax(wrk);
/* 4. calculate the rest with pruning*/
thres = wrk->OP_calced_score[num-1];
for (i = 0; i < gnum; i++) {
/* skip calced ones in 1. */
if (wrk->mixcalced[i]) {
wrk->mixcalced[i] = FALSE;
continue;
}
/* compute with safe pruning */
score = compute_g_heu_pruning(wrk, g[i], thres);
if (score > LOG_ZERO) {
num = cache_push(wrk, i, score, num);
thres = wrk->OP_calced_score[num-1];
}
}
} else { /* in case the last_id not available */
/* at the first 0 frame */
/* calculate with safe pruning */
thres = LOG_ZERO;
for (i = 0; i < gnum; i++) {
if (num < wrk->OP_gprune_num) {
score = compute_g_base(wrk, g[i]);
} else {
score = compute_g_safe(wrk, g[i], thres);
if (score <= thres) continue;
}
num = cache_push(wrk, i, score, num);
thres = wrk->OP_calced_score[num-1];
}
}
wrk->OP_calced_num = num;
}
/**
* Main function to compute all the GMS %HMM states in a frame
* with the input vectore specified by OP_vec. This function assumes
* that this will be called for sequencial frame, since it utilizes the
* result of previous frame for faster pruning.
*
* @param wrk [i/o] HMM computation work area
*
*/
void
compute_gs_scores(HMMWork *wrk)
{
int i;
for (i=0;i<wrk->gsset_num;i++) {
#ifdef GS_MAX_PROB
#ifdef LAST_BEST
/* compute only the maximum with pruning (last best first) */
wrk->t_fs[i] = compute_g_max(wrk, wrk->gsset[i].state, wrk->gms_last_max_id_list[i]);
#else
wrk->t_fs[i] = compute_g_max(wrk, wrk->gsset[i].state);
#endif /* LAST_BEST */
#else
/* compute all mixture */
wrk->t_fs[i] = compute_g_base(wrk, wrk->gsset[i].state);
#endif
/*printf("%d:%s:%f\n",i,gsset[i].book->name,t_fs[i]);*/
}
}
/**
* @brief Compute a set of Gaussians with beam pruning.
*
* If the N-best mixtures in the previous frame is specified in @a last_id,
* They are first computed to set the thresholds for each dimension.
* After that, the rest of the Gaussians will be computed with those dimension
* thresholds to drop unpromising Gaussians from computation at early stage
* of likelihood computation. If the @a last_id is not specified (typically
* at the first frame of the input), a safe pruning as same as one in
* gprune_safe.c will be applied.
*
* The calculated scores will be stored to OP_calced_score, with its
* corresponding mixture id to OP_calced_id. These are done by calling
* cache_push().
* The number of calculated mixtures is also stored in OP_calced_num.
*
* This can be called from calc_tied_mix() or calc_mix().
*
* @param wrk [i/o] HMM computation work area
* @param g [in] set of Gaussian densities to compute the output probability
* @param gnum [in] length of above
* @param last_id [in] ID list of N-best mixture in previous input frame,
* or NULL if not exist
* @param lnum [in] length of last_id
*/
void
gprune_beam(HMMWork *wrk, HTK_HMM_Dens **g, int gnum, int *last_id, int lnum)
{
int i, j, num = 0;
LOGPROB score, thres;
if (last_id != NULL) { /* compute them first to form thresholds */
/* 1. clear dimthres */
clear_dimthres(wrk);
/* 2. calculate first $OP_gprune_num and set initial thresholds */
for (j=0; j<lnum; j++) {
i = last_id[j];
#ifdef TEST2
if (!g[i]) {
score = LOG_ZERO;
} else {
score = compute_g_beam_updating(wrk, g[i]);
}
num = cache_push(wrk, i, score, num);
#else
score = compute_g_beam_updating(wrk, g[i]);
num = cache_push(wrk, i, score, num);
#endif
wrk->mixcalced[i] = TRUE; /* mark them as calculated */
}
/* 3. set pruning thresholds for each dimension */
set_dimthres(wrk);
/* 4. calculate the rest with pruning*/
for (i = 0; i < gnum; i++) {
/* skip calced ones in 1. */
if (wrk->mixcalced[i]) {
wrk->mixcalced[i] = FALSE;
continue;
}
#ifdef TEST2
/* compute with safe pruning */
if (!g[i]) continue;
score = compute_g_beam_pruning(wrk, g[i]);
if (score > LOG_ZERO) {
num = cache_push(wrk, i, score, num);
}
#else
/* compute with safe pruning */
score = compute_g_beam_pruning(wrk, g[i]);
if (score > LOG_ZERO) {
num = cache_push(wrk, i, score, num);
}
#endif
}
} else { /* in case the last_id not available */
/* at the first 0 frame */
/* calculate with safe pruning */
thres = LOG_ZERO;
for (i = 0; i < gnum; i++) {
if (num < wrk->OP_gprune_num) {
score = compute_g_base(wrk, g[i]);
} else {
score = compute_g_safe(wrk, g[i], thres);
if (score <= thres) continue;
}
num = cache_push(wrk, i, score, num);
thres = wrk->OP_calced_score[num-1];
}
}
wrk->OP_calced_num = num;
}
