/* Determine global mean and covariance of data in sequence s */
void CalcMeanCov(Sequence seq[], int s)
{
mean[s] = CreateVector(&dStack,swidth[s]);
SequenceMean(seq[s],mean[s]);
if (trace&T_MEAN) {
printf("Stream %d",s);
ShowVector(" global mean:\n",mean[s],20);
}
switch(ck){
case INVDIAGC:
case DIAGC:
cov[s].var = CreateVector(&dStack,swidth[s]);
SequenceCov(seq[s],ck,cov[s],mean[s]);
if(trace&T_MEAN) ShowVector("Global variance",cov[s].var,20);
break;
case FULLC:
cov[s].inv = CreateTriMat(&dStack,swidth[s]);
SequenceCov(seq[s],ck,cov[s],mean[s]);
if(trace&T_MEAN) ShowTriMat("Global covariance",cov[s].inv,20,20);
break;
case NULLC:
default:
cov[s].var = NULL;
if(trace&T_MEAN) printf("Using Euclidean distance\n");
break;
}
}
/* CalcCovs: calculate covariance of speech data */
void CalcCovs(void)
{
int x,y,s,V;
float meanx,meany,varxy,n;
Matrix fullMat;
if (totalCount<2)
HError(2021,"CalcCovs: Only %d speech frames accumulated",totalCount);
if (trace&T_TOP)
printf("%ld speech frames accumulated\n", totalCount);
n = (float)totalCount; /* to prevent rounding to integer below */
for (s=1; s<=hset.swidth[0]; s++){ /* For each stream */
V = hset.swidth[s];
for (x=1; x<=V; x++) /* For each coefficient ... */
accs[s].meanSum[x] /= n; /* ... calculate mean */
for (x=1;x<=V;x++) {
meanx = accs[s].meanSum[x]; /* ... and [co]variance */
if (fullcNeeded[s]) {
for (y=1; y<=x; y++) {
meany = accs[s].meanSum[y];
varxy = accs[s].squareSum.inv[x][y]/n - meanx*meany;
accs[s].squareSum.inv[x][y] =
(x != y || varxy > minVar) ? varxy : minVar;
}
}
else {
varxy = accs[s].squareSum.var[x]/n - meanx*meanx;
accs[s].fixed.var[x] = (varxy > minVar) ? varxy :minVar;
}
}
if (fullcNeeded[s]) { /* invert covariance matrix */
fullMat=CreateMatrix(&gstack,V,V);
ZeroMatrix(fullMat);
CovInvert(accs[s].squareSum.inv,fullMat);
Mat2Tri(fullMat,accs[s].fixed.inv);
FreeMatrix(&gstack,fullMat);
}
if (trace&T_COVS) {
printf("Stream %d\n",s);
if (meanUpdate)
ShowVector(" Mean Vector ", accs[s].meanSum,12);
if (fullcNeeded[s]) {
ShowTriMat(" Covariance Matrix ",accs[s].squareSum.inv,12,12);
} else
ShowVector(" Variance Vector ", accs[s].fixed.var,12);
}
}
}
/* PrintTree: Print each node as an entry */
static void PrintTree(VQNode n, CovKind ck)
{
if (n != NULL) {
printf("vqidx=%d ids=[%d %d %d]\n",
n->vqidx,n->nid,n->lid,n->rid);
ShowVector("Mean",n->mean,10);
switch(ck){
case NULLC:
break;
case INVDIAGC:
ShowVector("IVar",(Vector)n->cov.var,10);
break;
case FULLC:
ShowTriMat("ICov",(TriMat)n->cov.inv,10,10);
break;
}
printf("\n");
PrintTree(n->left,ck);
PrintTree(n->right,ck);
}
}
/* UpdateCounts: using frames in seg i and alignment in states/mixes */
void UpdateCounts(int segNum, int segLen, IntVec states,IntVec *mixes)
{
int M=0,i,j,k,s,m,state,last;
StreamElem *ste;
MixPDF *mp = NULL;
WtAcc *wa;
MuAcc *ma;
VaAcc *va;
TrAcc *ta;
Vector v;
Observation obs;
TMixRec *tmRec = NULL;
float x,y;
last = 1; /* last before 1st emitting state must be 1 */
ta = (TrAcc *)GetHook(hmmLink->transP);
for (i=1; i<=segLen; i++){
state = states[i];
if (trace&T_CNT)
printf(" Seg %d -> state %d\n",i,state);
if (uFlags&(UPMEANS|UPVARS|UPMIXES)){
obs = GetSegObs(segStore, segNum, i);
if (hset.hsKind == TIEDHS)
PrecomputeTMix(&hset, &obs, 50.0, 0);
ste = hmmLink->svec[state].info->pdf+1;
for (s=1; s<=nStreams; s++,ste++){
if (hset.hsKind==DISCRETEHS){
m = obs.vq[s]; v = NULL;
} else {
v = obs.fv[s]; m = mixes[s][i];
}
switch(hset.hsKind){
case TIEDHS:
tmRec = &(hset.tmRecs[s]);
M = tmRec->nMix;
break;
case PLAINHS:
case SHAREDHS:
case DISCRETEHS:
M = ste->nMix;
break;
}
if (m<1 || m > M)
HError(2170,"UpdateCounts: mix/vq idx out of range[%d]",m);
if (trace&T_CNT)
printf(" stream %d -> mix %d[%d]\n",s,m,M);
/* update mixture weight */
if (M>1 && (uFlags&UPMIXES)) {
wa = (WtAcc *)ste->hook;
wa->occ += 1.0; wa->c[m] += 1.0;
if (trace&T_CNT)
printf(" mix wt -> %.1f\n",wa->c[m]);
}
if (hset.hsKind==DISCRETEHS) continue;
/* update state/mixture component */
switch(hset.hsKind){
case PLAINHS:
case SHAREDHS:
mp = ste->spdf.cpdf[m].mpdf;
break;
case TIEDHS:
mp = tmRec->mixes[m];
break;
}
ma = (MuAcc *)GetHook(mp->mean);
va = (VaAcc *)GetHook(mp->cov.var);
ma->occ += 1.0; va->occ += 1.0;
for (j=1; j<=hset.swidth[s]; j++) {
x = v[j] - mp->mean[j];
ma->mu[j] += x;
if (uFlags&UPVARS)
switch(mp->ckind){
case DIAGC:
va->cov.var[j] += x*x;
break;
case FULLC:
for (k=1; k<=j; k++){
y = v[k]-mp->mean[k];
va->cov.inv[j][k] += x*y;
}
break;
default:
HError(2124,"UpdateCounts: bad cov kind %d\n",
mp->ckind);
}
}
if (trace&T_CNT) {
ShowVector(" mean ->",ma->mu,6);
if (uFlags&UPVARS) {
if (mp->ckind==DIAGC)
ShowVector(" var ->",va->cov.var,6);
else
ShowTriMat(" cov ->",va->cov.inv,6,6);
}
fflush(stdout);
}
}
}
/* update transition probs */
if (uFlags&UPTRANS){
ta->occ[last] += 1.0;
ta->tran[last][state] += 1.0;
last = state;
if (i==segLen){ /* remember final state */
ta->occ[state] += 1.0;
ta->tran[state][nStates] += 1.0;
}
if (trace&T_CNT) {
ShowMatrix(" tran ->",ta->tran,6,6);
fflush(stdout);
}
}
}
}
