s2_semi_mgau.c
/* -*- c-basic-offset: 4; indent-tabs-mode: nil -*- */
/* ====================================================================
* Copyright (c) 1999-2004 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,
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/* 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 "s2_semi_mgau.h"
#include "tied_mgau_common.h"
static ps_mgaufuncs_t s2_semi_mgau_funcs = {
"s2_semi",
s2_semi_mgau_frame_eval, /* frame_eval */
s2_semi_mgau_mllr_transform, /* transform */
s2_semi_mgau_free /* free */
};
struct vqFeature_s {
int32 score; /* score or distance */
int32 codeword; /* codeword (vector index) */
};
static void
eval_topn(s2_semi_mgau_t *s, int32 feat, mfcc_t *z)
{
int i, ceplen;
vqFeature_t *topn;
topn = s->f[feat];
ceplen = s->g->featlen[feat];
for (i = 0; i < s->max_topn; i++) {
mfcc_t *mean, diff, sqdiff, compl; /* diff, diff^2, component likelihood */
vqFeature_t vtmp;
mfcc_t *var, d;
mfcc_t *obs;
int32 cw, j;
cw = topn[i].codeword;
mean = s->g->mean[0][feat][0] + cw * ceplen;
var = s->g->var[0][feat][0] + cw * ceplen;
d = s->g->det[0][feat][cw];
obs = z;
for (j = 0; j < ceplen; j++) {
diff = *obs++ - *mean++;
sqdiff = MFCCMUL(diff, diff);
compl = MFCCMUL(sqdiff, *var);
d = GMMSUB(d, compl);
++var;
}
topn[i].score = (int32)d;
if (i == 0)
continue;
vtmp = topn[i];
for (j = i - 1; j >= 0 && (int32)d > topn[j].score; j--) {
topn[j + 1] = topn[j];
}
topn[j + 1] = vtmp;
}
}
static void
eval_cb(s2_semi_mgau_t *s, int32 feat, mfcc_t *z)
{
vqFeature_t *worst, *best, *topn;
mfcc_t *mean;
mfcc_t *var, *det, *detP, *detE;
int32 i, ceplen;
best = topn = s->f[feat];
worst = topn + (s->max_topn - 1);
mean = s->g->mean[0][feat][0];
var = s->g->var[0][feat][0];
det = s->g->det[0][feat];
detE = det + s->g->n_density;
ceplen = s->g->featlen[feat];
for (detP = det; detP < detE; ++detP) {
mfcc_t diff, sqdiff, compl; /* diff, diff^2, component likelihood */
mfcc_t d;
mfcc_t *obs;
vqFeature_t *cur;
int32 cw, j;
d = *detP;
obs = z;
cw = (int)(detP - det);
for (j = 0; (j < ceplen) && (d >= worst->score); ++j) {
diff = *obs++ - *mean++;
sqdiff = MFCCMUL(diff, diff);
compl = MFCCMUL(sqdiff, *var);
d = GMMSUB(d, compl);
++var;
}
if (j < ceplen) {
/* terminated early, so not in topn */
mean += (ceplen - j);
var += (ceplen - j);
continue;
}
if ((int32)d < worst->score)
continue;
for (i = 0; i < s->max_topn; i++) {
/* already there, so don't need to insert */
if (topn[i].codeword == cw)
break;
}
if (i < s->max_topn)
continue; /* already there. Don't insert */
/* remaining code inserts codeword and dist in correct spot */
for (cur = worst - 1; cur >= best && (int32)d >= cur->score; --cur)
memcpy(cur + 1, cur, sizeof(vqFeature_t));
++cur;
cur->codeword = cw;
cur->score = (int32)d;
}
}
static void
mgau_dist(s2_semi_mgau_t * s, int32 frame, int32 feat, mfcc_t * z)
{
eval_topn(s, feat, z);
/* If this frame is skipped, do nothing else. */
if (frame % s->ds_ratio)
return;
/* Evaluate the rest of the codebook (or subset thereof). */
eval_cb(s, feat, z);
}
static int
mgau_norm(s2_semi_mgau_t *s, int feat)
{
int32 norm;
int j;
/* Compute quantized normalizing constant. */
norm = s->f[feat][0].score >> SENSCR_SHIFT;
/* Normalize the scores, negate them, and clamp their dynamic range. */
for (j = 0; j < s->max_topn; ++j) {
s->f[feat][j].score = -((s->f[feat][j].score >> SENSCR_SHIFT) - norm);
if (s->f[feat][j].score > MAX_NEG_ASCR)
s->f[feat][j].score = MAX_NEG_ASCR;
if (s->topn_beam[feat] && s->f[feat][j].score > s->topn_beam[feat])
break;
}
return j;
}
static int32
get_scores_8b_feat_6(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3, *pid_cw4, *pid_cw5;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
pid_cw4 = s->mixw[i][s->f[i][4].codeword];
pid_cw5 = s->mixw[i][s->f[i][5].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw1[sen] + s->f[i][1].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw2[sen] + s->f[i][2].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw3[sen] + s->f[i][3].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw4[sen] + s->f[i][4].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw5[sen] + s->f[i][5].score);
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_5(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3, *pid_cw4;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
pid_cw4 = s->mixw[i][s->f[i][4].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw1[sen] + s->f[i][1].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw2[sen] + s->f[i][2].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw3[sen] + s->f[i][3].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw4[sen] + s->f[i][4].score);
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_4(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw1[sen] + s->f[i][1].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw2[sen] + s->f[i][2].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw3[sen] + s->f[i][3].score);
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_3(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw1[sen] + s->f[i][1].score);
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw2[sen] + s->f[i][2].score);
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_2(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw1[sen] + s->f[i][1].score);
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_1(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0;
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
int32 tmp = pid_cw0[sen] + s->f[i][0].score;
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat_any(s2_semi_mgau_t * s, int i, int topn,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, k, l;
for (l = j = 0; j < n_senone_active; j++) {
int sen = senone_active[j] + l;
uint8 *pid_cw;
int32 tmp;
pid_cw = s->mixw[i][s->f[i][0].codeword];
tmp = pid_cw[sen] + s->f[i][0].score;
for (k = 1; k < topn; ++k) {
pid_cw = s->mixw[i][s->f[i][k].codeword];
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw[sen] + s->f[i][k].score);
}
senone_scores[sen] += tmp;
l = sen;
}
return 0;
}
static int32
get_scores_8b_feat(s2_semi_mgau_t * s, int i, int topn,
int16 *senone_scores, uint8 *senone_active, int32 n_senone_active)
{
switch (topn) {
case 6:
return get_scores_8b_feat_6(s, i, senone_scores,
senone_active, n_senone_active);
case 5:
return get_scores_8b_feat_5(s, i, senone_scores,
senone_active, n_senone_active);
case 4:
return get_scores_8b_feat_4(s, i, senone_scores,
senone_active, n_senone_active);
case 3:
return get_scores_8b_feat_3(s, i, senone_scores,
senone_active, n_senone_active);
case 2:
return get_scores_8b_feat_2(s, i, senone_scores,
senone_active, n_senone_active);
case 1:
return get_scores_8b_feat_1(s, i, senone_scores,
senone_active, n_senone_active);
default:
return get_scores_8b_feat_any(s, i, topn, senone_scores,
senone_active, n_senone_active);
}
}
static int32
get_scores_8b_feat_all(s2_semi_mgau_t * s, int i, int topn, int16 *senone_scores)
{
int32 j, k;
for (j = 0; j < s->n_sen; j++) {
uint8 *pid_cw;
int32 tmp;
pid_cw = s->mixw[i][s->f[i][0].codeword];
tmp = pid_cw[j] + s->f[i][0].score;
for (k = 1; k < topn; ++k) {
pid_cw = s->mixw[i][s->f[i][k].codeword];
tmp = fast_logmath_add(s->lmath_8b, tmp,
pid_cw[j] + s->f[i][k].score);
}
senone_scores[j] += tmp;
}
return 0;
}
static int32
get_scores_4b_feat_6(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3, *pid_cw4, *pid_cw5;
uint8 w_den[6][16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[0][j] = s->mixw_cb[j] + s->f[i][0].score;
w_den[1][j] = s->mixw_cb[j] + s->f[i][1].score;
w_den[2][j] = s->mixw_cb[j] + s->f[i][2].score;
w_den[3][j] = s->mixw_cb[j] + s->f[i][3].score;
w_den[4][j] = s->mixw_cb[j] + s->f[i][4].score;
w_den[5][j] = s->mixw_cb[j] + s->f[i][5].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
pid_cw4 = s->mixw[i][s->f[i][4].codeword];
pid_cw5 = s->mixw[i][s->f[i][5].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
cw = pid_cw4[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[4][cw]);
cw = pid_cw5[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[5][cw]);
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
cw = pid_cw4[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[4][cw]);
cw = pid_cw5[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[5][cw]);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_5(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3, *pid_cw4;
uint8 w_den[5][16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[0][j] = s->mixw_cb[j] + s->f[i][0].score;
w_den[1][j] = s->mixw_cb[j] + s->f[i][1].score;
w_den[2][j] = s->mixw_cb[j] + s->f[i][2].score;
w_den[3][j] = s->mixw_cb[j] + s->f[i][3].score;
w_den[4][j] = s->mixw_cb[j] + s->f[i][4].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
pid_cw4 = s->mixw[i][s->f[i][4].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
cw = pid_cw4[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[4][cw]);
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
cw = pid_cw4[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[4][cw]);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_4(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2, *pid_cw3;
uint8 w_den[4][16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[0][j] = s->mixw_cb[j] + s->f[i][0].score;
w_den[1][j] = s->mixw_cb[j] + s->f[i][1].score;
w_den[2][j] = s->mixw_cb[j] + s->f[i][2].score;
w_den[3][j] = s->mixw_cb[j] + s->f[i][3].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
pid_cw3 = s->mixw[i][s->f[i][3].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
cw = pid_cw3[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[3][cw]);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_3(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1, *pid_cw2;
uint8 w_den[3][16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[0][j] = s->mixw_cb[j] + s->f[i][0].score;
w_den[1][j] = s->mixw_cb[j] + s->f[i][1].score;
w_den[2][j] = s->mixw_cb[j] + s->f[i][2].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
pid_cw2 = s->mixw[i][s->f[i][2].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
cw = pid_cw2[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[2][cw]);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_2(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0, *pid_cw1;
uint8 w_den[2][16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[0][j] = s->mixw_cb[j] + s->f[i][0].score;
w_den[1][j] = s->mixw_cb[j] + s->f[i][1].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
pid_cw1 = s->mixw[i][s->f[i][1].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] >> 4;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[0][cw];
cw = pid_cw1[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp, w_den[1][cw]);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_1(s2_semi_mgau_t * s, int i,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, l;
uint8 *pid_cw0;
uint8 w_den[16];
/* Precompute scaled densities. */
for (j = 0; j < 16; ++j) {
w_den[j] = s->mixw_cb[j] + s->f[i][0].score;
}
pid_cw0 = s->mixw[i][s->f[i][0].codeword];
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
if (n & 1) {
cw = pid_cw0[n/2] >> 4;
tmp = w_den[cw];
}
else {
cw = pid_cw0[n/2] & 0x0f;
tmp = w_den[cw];
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat_any(s2_semi_mgau_t * s, int i, int topn,
int16 *senone_scores, uint8 *senone_active,
int32 n_senone_active)
{
int32 j, k, l;
for (l = j = 0; j < n_senone_active; j++) {
int n = senone_active[j] + l;
int tmp, cw;
uint8 *pid_cw;
pid_cw = s->mixw[i][s->f[i][0].codeword];
if (n & 1)
cw = pid_cw[n/2] >> 4;
else
cw = pid_cw[n/2] & 0x0f;
tmp = s->mixw_cb[cw] + s->f[i][0].score;
for (k = 1; k < topn; ++k) {
pid_cw = s->mixw[i][s->f[i][k].codeword];
if (n & 1)
cw = pid_cw[n/2] >> 4;
else
cw = pid_cw[n/2] & 0x0f;
tmp = fast_logmath_add(s->lmath_8b, tmp,
s->mixw_cb[cw] + s->f[i][k].score);
}
senone_scores[n] += tmp;
l = n;
}
return 0;
}
static int32
get_scores_4b_feat(s2_semi_mgau_t * s, int i, int topn,
int16 *senone_scores, uint8 *senone_active, int32 n_senone_active)
{
switch (topn) {
case 6:
return get_scores_4b_feat_6(s, i, senone_scores,
senone_active, n_senone_active);
case 5:
return get_scores_4b_feat_5(s, i, senone_scores,
senone_active, n_senone_active);
case 4:
return get_scores_4b_feat_4(s, i, senone_scores,
senone_active, n_senone_active);
case 3:
return get_scores_4b_feat_3(s, i, senone_scores,
senone_active, n_senone_active);
case 2:
return get_scores_4b_feat_2(s, i, senone_scores,
senone_active, n_senone_active);
case 1:
return get_scores_4b_feat_1(s, i, senone_scores,
senone_active, n_senone_active);
default:
return get_scores_4b_feat_any(s, i, topn, senone_scores,
senone_active, n_senone_active);
}
}
static int32
get_scores_4b_feat_all(s2_semi_mgau_t * s, int i, int topn, int16 *senone_scores)
{
int j, last_sen;
j = 0;
/* Number of senones is always even, but don't overrun if it isn't. */
last_sen = s->n_sen & ~1;
while (j < last_sen) {
uint8 *pid_cw;
int32 tmp0, tmp1;
int k;
pid_cw = s->mixw[i][s->f[i][0].codeword];
tmp0 = s->mixw_cb[pid_cw[j/2] & 0x0f] + s->f[i][0].score;
tmp1 = s->mixw_cb[pid_cw[j/2] >> 4] + s->f[i][0].score;
for (k = 1; k < topn; ++k) {
int32 w_den0, w_den1;
pid_cw = s->mixw[i][s->f[i][k].codeword];
w_den0 = s->mixw_cb[pid_cw[j/2] & 0x0f] + s->f[i][k].score;
w_den1 = s->mixw_cb[pid_cw[j/2] >> 4] + s->f[i][k].score;
tmp0 = fast_logmath_add(s->lmath_8b, tmp0, w_den0);
tmp1 = fast_logmath_add(s->lmath_8b, tmp1, w_den1);
}
senone_scores[j++] += tmp0;
senone_scores[j++] += tmp1;
}
return 0;
}
/*
* Compute senone scores for the active senones.
*/
int32
s2_semi_mgau_frame_eval(ps_mgau_t *ps,
int16 *senone_scores,
uint8 *senone_active,
int32 n_senone_active,
mfcc_t ** featbuf, int32 frame,
int32 compallsen)
{
s2_semi_mgau_t *s = (s2_semi_mgau_t *)ps;
int i, topn_idx;
int n_feat = s->g->n_feat;
memset(senone_scores, 0, s->n_sen * sizeof(*senone_scores));
/* 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. */
topn_idx = frame % s->n_topn_hist;
s->f = s->topn_hist[topn_idx];
for (i = 0; i < n_feat; ++i) {
/* For past frames this will already be computed. */
if (frame >= ps_mgau_base(ps)->frame_idx) {
vqFeature_t **lastf;
if (topn_idx == 0)
lastf = s->topn_hist[s->n_topn_hist-1];
else
lastf = s->topn_hist[topn_idx-1];
memcpy(s->f[i], lastf[i], sizeof(vqFeature_t) * s->max_topn);
mgau_dist(s, frame, i, featbuf[i]);
s->topn_hist_n[topn_idx][i] = mgau_norm(s, i);
}
if (s->mixw_cb) {
if (compallsen)
get_scores_4b_feat_all(s, i, s->topn_hist_n[topn_idx][i], senone_scores);
else
get_scores_4b_feat(s, i, s->topn_hist_n[topn_idx][i], senone_scores,
senone_active, n_senone_active);
}
else {
if (compallsen)
get_scores_8b_feat_all(s, i, s->topn_hist_n[topn_idx][i], senone_scores);
else
get_scores_8b_feat(s, i, s->topn_hist_n[topn_idx][i], senone_scores,
senone_active, n_senone_active);
}
}
return 0;
}
static int32
read_sendump(s2_semi_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(s2_semi_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 weights 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 file '%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(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;
}
static int
split_topn(char const *str, uint8 *out, int nfeat)
{
char *topn_list = ckd_salloc(str);
char *c, *cc;
int i, maxn;
c = topn_list;
i = 0;
maxn = 0;
while (i < nfeat && (cc = strchr(c, ',')) != NULL) {
*cc = '\0';
out[i] = atoi(c);
if (out[i] > maxn) maxn = out[i];
c = cc + 1;
++i;
}
if (i < nfeat && *c != '\0') {
out[i] = atoi(c);
if (out[i] > maxn) maxn = out[i];
++i;
}
while (i < nfeat)
out[i++] = maxn;
ckd_free(topn_list);
return maxn;
}
ps_mgau_t *
s2_semi_mgau_init(acmod_t *acmod)
{
s2_semi_mgau_t *s;
ps_mgau_t *ps;
char const *sendump_path;
int i;
int n_feat;
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) {
E_ERROR("Failed to read means and variances\n");
goto error_out;
}
/* Currently only a single codebook is supported. */
if (s->g->n_mgau != 1)
goto error_out;
n_feat = s->g->n_feat;
/* Verify n_feat and veclen, against acmod. */
if (n_feat != feat_dimension1(acmod->fcb)) {
E_ERROR("Number of streams does not match: %d != %d\n",
n_feat, feat_dimension1(acmod->fcb));
goto error_out;
}
for (i = 0; i < 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",
i, 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");
/* Determine top-N for each feature */
s->topn_beam = ckd_calloc(n_feat, sizeof(*s->topn_beam));
s->max_topn = cmd_ln_int32_r(s->config, "-topn");
split_topn(cmd_ln_str_r(s->config, "-topn_beam"), s->topn_beam, n_feat);
E_INFO("Maximum top-N: %d ", s->max_topn);
E_INFOCONT("Top-N beams:");
for (i = 0; i < n_feat; ++i) {
E_INFOCONT(" %d", s->topn_beam[i]);
}
E_INFOCONT("\n");
/* Top-N scores from recent frames */
s->n_topn_hist = cmd_ln_int32_r(s->config, "-pl_window") + 2;
s->topn_hist = (vqFeature_t ***)
ckd_calloc_3d(s->n_topn_hist, n_feat, s->max_topn,
sizeof(***s->topn_hist));
s->topn_hist_n = ckd_calloc_2d(s->n_topn_hist, n_feat,
sizeof(**s->topn_hist_n));
for (i = 0; i < s->n_topn_hist; ++i) {
int j;
for (j = 0; j < n_feat; ++j) {
int k;
for (k = 0; k < s->max_topn; ++k) {
s->topn_hist[i][j][k].score = WORST_DIST;
s->topn_hist[i][j][k].codeword = k;
}
}
}
ps = (ps_mgau_t *)s;
ps->vt = &s2_semi_mgau_funcs;
return ps;
error_out:
s2_semi_mgau_free(ps_mgau_base(s));
return NULL;
}
int
s2_semi_mgau_mllr_transform(ps_mgau_t *ps,
ps_mllr_t *mllr)
{
s2_semi_mgau_t *s = (s2_semi_mgau_t *)ps;
return gauden_mllr_transform(s->g, mllr, s->config);
}
void
s2_semi_mgau_free(ps_mgau_t *ps)
{
s2_semi_mgau_t *s = (s2_semi_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);
if (s->mixw_cb)
ckd_free(s->mixw_cb);
}
gauden_free(s->g);
ckd_free(s->topn_beam);
ckd_free_2d(s->topn_hist_n);
ckd_free_3d((void **)s->topn_hist);
ckd_free(s);
}
SENSCR_SHIFT
#define SENSCR_SHIFT
Shift count for senone scores.
Definition: hmm.h:73
gauden_free
void gauden_free(gauden_t *g)
Release memory allocated by gauden_init.
Definition: ms_gauden.c:358
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:509
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:311
acmod_s
Acoustic model structure.
Definition: acmod.h:148
acmod_s::mdef
bin_mdef_t * mdef
Model definition.
Definition: acmod.h:159
acmod_s::config
cmd_ln_t * config
Configuration.
Definition: acmod.h:150
acmod_s::fcb
feat_t * fcb
Dynamic feature computation.
Definition: acmod.h:156
acmod_s::lmath
logmath_t * lmath
Log-math computation.
Definition: acmod.h:151
bin_mdef_s
Definition: bin_mdef.h:117
gauden_t::var
mfcc_t **** var
like mean; diagonal covariance vector only
Definition: ms_gauden.h:84
gauden_t::det
mfcc_t *** det
log(determinant) for each variance vector; actually, log(sqrt(2*pi*det))
Definition: ms_gauden.h:85
gauden_t::n_feat
int32 n_feat
Number feature streams in each codebook.
Definition: ms_gauden.h:89
gauden_t::mean
mfcc_t **** mean
mean[codebook][feature][codeword] vector
Definition: ms_gauden.h:83
gauden_t::n_density
int32 n_density
Number gaussian densities in each codebook-feature stream.
Definition: ms_gauden.h:90
gauden_t::featlen
int32 * featlen
feature length for each feature
Definition: ms_gauden.h:91
gauden_t::n_mgau
int32 n_mgau
Number codebooks.
Definition: ms_gauden.h:88
ps_mgau_s
Definition: acmod.h:113
ps_mgau_s::vt
ps_mgaufuncs_t * vt
vtable of mgau functions.
Definition: acmod.h:114
ps_mgaufuncs_s
Definition: acmod.h:98
ps_mllr_s
Feature space linear transform structure.
Definition: acmod.h:82
s2_semi_mgau_s
Definition: s2_semi_mgau.h:59
s2_semi_mgau_s::n_topn_hist
int n_topn_hist
Number of past frames tracked.
Definition: s2_semi_mgau.h:77
s2_semi_mgau_s::topn_hist
vqFeature_t *** topn_hist
Top-N scores and codewords for past frames.
Definition: s2_semi_mgau.h:74
s2_semi_mgau_s::topn_hist_n
uint8 ** topn_hist_n
Variable top-N for past frames.
Definition: s2_semi_mgau.h:75
s2_semi_mgau_s::f
vqFeature_t ** f
Topn-N for currently scoring frame.
Definition: s2_semi_mgau.h:76
vqFeature_s
Definition: s2_semi_mgau.c:70
tied_mgau_common.h
Common code shared between SC and PTM (tied-state) models.
GMMSUB
#define GMMSUB(a, b)
Subtract GMM component b (assumed to be positive) and saturate.
Definition: tied_mgau_common.h:62
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
MAX_NEG_ASCR
#define MAX_NEG_ASCR
Maximum negated acoustic score value.
Definition: tied_mgau_common.h:83
MAX_NEG_MIXW
#define MAX_NEG_MIXW
Maximum negated mixture weight value.
Definition: tied_mgau_common.h:82