if (NextArg()==FLOATARG || NextArg()==INTARG)
{
pruneInc = GetChkedFlt(0.0,1.0E20,s);
pruneLim = GetChkedFlt(0.0,1.0E20,s);
}
else
{
pruneInc = 0.0;
pruneLim = pruneInit ;
}
break;
case 'u':
SetuFlags(); break;
case 'v':
minVar = GetChkedFlt(0.0,10.0,s); break;
case 'w':
mixWeightFloor = MINMIX * GetChkedFlt(0.0,10000.0,s);
break;
/* DoOnlineAdaptation: Perform unsupervised online adaptation
using the recognition hypothesis as the transcription */
int DoOnlineAdaptation(Lattice *lat, ParmBuf pbuf, int nFrames)
{
Transcription *modelTrans, *trans;
BufferInfo pbinfo;
Lattice *alignLat, *wordNet;
Network *alignNet;
int i;
GetBufferInfo(pbuf,&pbinfo);
trans=TranscriptionFromLattice(&netHeap,lat,1);
wordNet=LatticeFromLabels(GetLabelList(trans,1),bndId,
&vocab,&netHeap);
alignNet=ExpandWordNet(&netHeap,wordNet,&vocab,&hset);
StartRecognition(alignvri,alignNet,0.0,0.0,0.0);
/* do forced alignment */
for (i = 0; i < nFrames; i++) {
ReadAsTable(pbuf, i, &obs);
ProcessObservation(alignvri,&obs,-1,xfInfo.inXForm);
}
alignLat=CompleteRecognition(alignvri,
pbinfo.tgtSampRate/10000000.0,
&netHeap);
if (alignvri->noTokenSurvived) {
Dispose(&netHeap, trans);
/* Return value 0 to indicate zero frames process failed */
return 0;
}
modelTrans=TranscriptionFromLattice(&netHeap,alignLat,1);
/* format the transcription so that it contains just the models */
FormatTranscription(modelTrans,pbinfo.tgtSampRate,FALSE,TRUE,
FALSE,FALSE,TRUE,FALSE,TRUE,TRUE, FALSE);
/* Now do the frame/state alignment accumulating MLLR statistics */
/* set the various values in the utterance storage */
utt->tr = modelTrans;
utt->pbuf = pbuf;
utt->Q = CountLabs(utt->tr->head);
utt->T = nFrames;
utt->ot = obs;
/* do frame state alignment and accumulate statistics */
fbInfo->inXForm = xfInfo.inXForm;
fbInfo->al_inXForm = xfInfo.inXForm;
fbInfo->paXForm = xfInfo.paXForm;
if (!FBFile(fbInfo, utt, NULL))
nFrames = 0;
Dispose(&netHeap, trans);
if (trace&T_TOP) {
printf("Accumulated statistics...\n");
fflush(stdout);
}
return nFrames;
}
