libsent/src/phmm/gprune_heu.c
混合ガウス分布計算: Gaussian pruning (heuristic algorithm) [詳細]
#include <sent/stddefs.h>#include <sent/htk_hmm.h>#include <sent/htk_param.h>#include <sent/hmm.h>#include <sent/gprune.h>#include "globalvars.h"
関数 | |
| static void | init_backmax () |
| static void | make_backmax () |
| static LOGPROB | compute_g_heu_updating (HTK_HMM_Dens *binfo) |
| Calculate probability with maximum value update. | |
| static LOGPROB | compute_g_heu_pruning (HTK_HMM_Dens *binfo, LOGPROB thres) |
| Calculate probability with pruning. | |
| boolean | gprune_heu_init () |
| void | gprune_heu_free () |
| void | gprune_heu (HTK_HMM_Dens **g, int gnum, int *last_id) |
| Compute a set of Gaussians with heuristic pruning. | |
変数 | |
| static LOGPROB * | backmax |
| Backward sum of max for each dimension (inversed). | |
| static int | backmax_num |
| Length of above. | |
| static boolean * | mixcalced |
| Mark which Gaussian has been computed. | |
説明
混合ガウス分布計算: Gaussian pruning (heuristic algorithm)
- 日付:
- Thu Feb 17 05:44:52 2005
gprune_heu()は混合ガウス分布集合の計算ルーチンの一つです． heuristic pruning を使って上位のガウス分布の出力確率のみを高速に求めます． Tied-mixture HMM 使用時に Julius でGPRUNE_DEFAULT_HEURISTIC が 定義されているか，あるいはJuliusのオプション "-gprune heuristic" を 指定することでこの関数が使用されます．
heuristic pruning はあまり使われていない手法で，高速化の効果は 他の手法の中間です．
gprune_heu() は outprob_init() によってその関数へのポインタが compute_gaussset にセットされることで使用されます．このポインタが calc_tied_mix() または calc_mix() から呼び出されます．
- Revision
- 1.6
gprune_heu.c で定義されています。
関数
| static void init_backmax | ( | ) | [static] |
| static void make_backmax | ( | ) | [static] |
Build backmax information for each frame, by summing up current maximum values of each dimensions.
gprune_heu.c の 136 行で定義されています。
参照元 gprune_heu().
| static LOGPROB compute_g_heu_updating | ( | HTK_HMM_Dens * | binfo | ) | [static] |
Calculate probability with maximum value update.
Calculate probability of a Gaussian toward OP_vec, while storing the maximum values of each dimension to backmax. for future pruning. The pruning itself is not performed here. This function will be used to compute the first N Gaussians.
- 引数:
-
binfo [in] Gaussian density
- 戻り値:
- the output log probability.
gprune_heu.c の 162 行で定義されています。
参照元 gprune_heu().
| static LOGPROB compute_g_heu_pruning | ( | HTK_HMM_Dens * | binfo, | |
| LOGPROB | thres | |||
| ) | [static] |
Calculate probability with pruning.
Calculate probability of a Gaussian toward OP_vec, performing pruning using threshold and the backmax information that has been set by compute_g_heu_updating() and make_backmax().
- 引数:
-
binfo [in] Gaussian density thres [in] threshold
- 戻り値:
- the output log probability.
gprune_heu.c の 200 行で定義されています。
参照元 gprune_heu().
| boolean gprune_heu_init | ( | ) |
Initialize and setup work area for Gaussian pruning by heuristic algorithm.
- 戻り値:
- TRUE on success, FALSE on failure.
gprune_heu.c の 235 行で定義されています。
参照元 outprob_init().
| void gprune_heu_free | ( | ) |
| void gprune_heu | ( | HTK_HMM_Dens ** | g, | |
| int | gnum, | |||
| int * | last_id | |||
| ) |
Compute a set of Gaussians with heuristic pruning.
If the N-best mixtures in the previous frame is specified in 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 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().
- 引数:
-
g [in] set of Gaussian densities to compute the output probability gnum [in] length of above last_id [in] ID list of N-best mixture in previous input frame, or NULL if not exist
gprune_heu.c の 288 行で定義されています。
参照元 outprob_init().
