HError(999,"Can only update linear transforms OR model parameters!");
xfInfo.useOutXForm = TRUE;
/* This initialises things - temporary hack - THINK!! */
CreateAdaptXForm(hset, "tmp");
}
/* initialise and pass information to the forward backward library */
InitialiseForBack(fbInfo, x, hset, uFlags, pruneInit, pruneInc,
pruneLim, minFrwdP);
if (parMode != 0) {
ConvLogWt(hset);
}
/* 2-model reestimation */
if (al_hmmUsed){
if (trace&T_TOP)
printf("2-model re-estimation enabled\n");
/* load alignment HMM set */
CreateHMMSet(&al_hset,&hmmStack,TRUE);
xfInfo.al_hset = &al_hset;
if (xfInfo.alXFormExt == NULL) xfInfo.alXFormExt = xfInfo.inXFormExt;
/* load multiple MMFs */
if (strlen(al_hmmMMF) > 0 ) {
char *p,*q;
Boolean eos;
p=q=al_hmmMMF;
for(;;) {
eos = (*p=='\0');
if ( ( isspace((int) *p) || *p == '\0' ) && (q!=p) ) {
/* UpdateModels: update all models and save them in newDir if set,
new files have newExt if set */
void UpdateModels(void)
{
int n;
HLink hmm;
HMMScanState hss;
if (trace&T_INT){
printf("Starting Model Update\n"); fflush(stdout);
}
if (hsKind==TIEDHS){
if (uFlags & UPVARS) /* TIEDHS therefore only done once per HMMSet */
UpdateTMVars();
if (uFlags & UPMEANS)
UpdateTMMeans();
if (uFlags & (UPMEANS|UPVARS))
FixAllGConsts(&hset);
}
NewHMMScan(&hset,&hss);
do {
hmm = hss.hmm;
n = (int)hmm->hook;
if (n<minEgs && !(trace&T_OPT))
HError(-2428,"%s copied: only %d egs\n",HMMPhysName(&hset,hmm),n);
if (n>=minEgs) {
if (uFlags & UPTRANS)
UpdateTrans(hmm);
if (maxMixes>1 && uFlags & UPMIXES)
UpdateWeights(hmm);
}
if (trace&T_OPT) {
if (n<minEgs)
printf("Model %s copied: only %d examples\n",
HMMPhysName(&hset,hmm),n);
else
printf("Model %s updated with %d examples\n",
HMMPhysName(&hset,hmm),n);
fflush(stdout);
}
} while (GoNextHMM(&hss));
EndHMMScan(&hss);
if (trace&T_TOP){
printf("Saving hmm's to dir %s\n",(newDir==NULL)?"Current":newDir);
fflush(stdout);
}
if(SaveHMMSet(&hset,newDir,newExt,NULL,saveBinary)<SUCCESS)
HError(2411,"UpdateModels: SaveHMMSet failed");
ResetHeaps(); /* Clean Up */
if (trace&T_TOP)
printf("Reestimation complete - average log prob per frame = %e\n",
totalPr/(double)totalT);
}