void cTumkwsjSink::fillKresult(Kresult *k, WORD_ID *seq, int n, WORD_INFO *winfo, LOGPROB *cmscore, int numOfFrames, SentenceAlign *alignment)
{
int i;
int kwcount = 0;
if (seq != NULL) {
for (i=0;i<n;i++) {
if (strcmp("garbage",winfo->woutput[seq[i]])!=0 && strcmp("<s>",winfo->woutput[seq[i]])!=0 && strcmp("</s>",winfo->woutput[seq[i]])!=0) {
//keywords:
k->keyword[kwcount]=winfo->woutput[seq[i]];
if (alignment == NULL) {
k->kwStartTime[kwcount]= 0.0;
} else {
k->kwStartTime[kwcount]= (period * (double)(alignment->begin_frame[i])); // ?? n != ??
}
k->kwConf[kwcount]=cmscore[i];
kwcount++;
if (kwcount >= MAXNUMKW) {
SMILE_IWRN(2,"keywords were discarded, more than MAXNUMKW=%i (tumkwsjSink.hpp!) keywords detected!",MAXNUMKW);
i=n; break;
}
}
}
}
k->numOfKw=kwcount;
k->turnDuration=numOfFrames;
}
int cLibsvmLiveSink::myFinaliseInstance()
{
int ap=0;
int ret = cDataSink::myFinaliseInstance();
if (ret==0) return 0;
// TODO: binary model files...
// load model
SMILE_MSG(2,"loading LibSVM model for instance '%s' ...",getInstName());
if((model=svm_load_model(modelfile))==0) {
COMP_ERR("can't open libSVM model file '%s'",modelfile);
}
nClasses = svm_get_nr_class(model);
svmType = svm_get_svm_type(model);
if(predictProbability) {
if ((svmType==NU_SVR) || (svmType==EPSILON_SVR)) {
nClasses = 0;
SMILE_MSG(2,"LibSVM prob. model (regression) for test data: target value = predicted value + z,\nz: Laplace distribution e^(-|z|/sigma)/(2sigma),sigma=%g",svm_get_svr_probability(model));
} else {
labels=(int *) malloc(nClasses*sizeof(int));
svm_get_labels(model,labels);
SMILE_MSG(3,"LibSVM %i labels in model '%s':",nClasses,modelfile);
int j;
for(j=0;j<nClasses;j++)
SMILE_MSG(3," Label[%i] : '%d'",j,labels[j]);
}
}
//?? move this in front of above if() block ?
if ((predictProbability)&&(nClasses>0))
probEstimates = (double *) malloc(nClasses*sizeof(double));
// load scale
if((scale=svm_load_scale(scalefile))==0) {
COMP_ERR("can't open libSVM scale file '%s'",scalefile);
}
// load selection
loadSelection(fselection);
//TODO: check compatibility of getLevelN() (possibly after selection), number of features in model, and scale
if (nClasses>0) {
// load class mapping
loadClasses(classes);
} else {
if (classes != NULL) SMILE_IWRN(2,"not loading given class mapping file for regression SVR model (there are no classes...)!");
}
return ret;
}
// get smileTime from _msg, convert to semaine time by getting current time from smile and semaine and observing the difference
long long cSemaineEmmaSender::smileTimeToSemaineTime( double smileTime )
{
smileTime *= 1000.0;
if (meta != NULL) {
long long smit = (long long)round(getSmileTime()*1000.0);
return (long long)round(smileTime) + (meta->getTime() - smit);
} else {
SMILE_IWRN(3,"warning, no meta component found, times sent are SMILE times and NOT semaine times!");
return (long long)round(smileTime);
}
return 0;
}
int cFullinputMean::myTick(long long t)
{
long i;
if (isEOI()) {
if (means == NULL) {
SMILE_IWRN(1,"sequence too short, cannot compute mean value!");
long N = reader->getLevelN();
means = new cVector( N, DMEM_FLOAT );
for (i=0; i<N; i++) {
means->dataF[i] = 0;
}
nMeans = 1;
}
if (flag==0) {
reader->setCurR(0); flag = 1;
FLOAT_DMEM nM = (FLOAT_DMEM)nMeans;
if (nM <= 0.0) nM = 1.0;
for (i=0; i<means->N; i++) {
means->dataF[i] /= nM;
}
}
cVector *vec = reader->getNextFrame();
if (vec!= NULL) {
/*if ((htkcompatible)&&(idx0>0)) {
for (i=0; i<means->N; i++) {
if ((i==0)||(i%idx0!=0)) {
vec->dataF[i] -= means->dataF[i];
}
}
} else {*/
for (i=0; i<means->N; i++) {
vec->dataF[i] -= means->dataF[i];
//printf("means[%i] = %f\n",i,means->dataF[i]);
}
//}
writer->setNextFrame(vec);
return 1;
}
} else {
// compute means, do not write data
cVector *vec = reader->getNextFrame();
if (vec != NULL) {
if (vec->type != DMEM_FLOAT) { COMP_ERR("only float data-type is supported by cFullinputMean!"); }
if (means == NULL) {
means = new cVector( vec->N, vec->type );
for (i=0; i<vec->N; i++) {
means->dataF[i] = vec->dataF[i];
}
nMeans = 1;
} else {
for (i=0; i<vec->N; i++) {
means->dataF[i] += vec->dataF[i];
}
nMeans++;
}
return 1;
}
}
return 0;
}
// this is called from julius decoder thread...
int cTumkwsjSink::getFv(float *vec, int n)
{
int ret=0;
smileMutexLock(dataFlgMtx);
if (terminated) {
smileMutexUnlock(dataFlgMtx);
recog->process_want_terminate = TRUE;
return -1;
}
// we should wait for main thread to provide data, then set a flag that data was read..
SMILE_IDBG(4,"yes... julius requests features from us (n=%i)!",n);
int end=0;
do {
lockMessageMemory();
turnStartSmileTimeCur = turnStartSmileTime;
// handle pre/post silence and turn detector interface
if (turnStart) {
// process old turnEnd message first...
if ((turnEnd)&&(vIdxEnd < vIdxStart)) {
turnEnd = 0; isTurn = 0; ret=-3; end=1;
turnStartSmileTimeCur = turnStartSmileTimeLast;
SMILE_IDBG(2,"processed turn end message!");
}
turnStart = 0;
curVidx = vIdxStart-preSil;
isTurn = 1;
SMILE_IDBG(2,"received turn start message!");
}
if (turnEnd) {
SMILE_IDBG(4,"received turn end message!");
if (curVidx >= vIdxEnd+postSil) {
turnEnd = 0; isTurn = 0; ret=-3; end=1; SMILE_IDBG(2,"processed turn end message!");
turnStartSmileTimeCur = turnStartSmileTimeLast;
}
// if no frames have been written...
if (curVidx == vIdxStart) {
SMILE_IWRN(2,"turn (vIdx %i - vIdx %i) has 0 frames (curVidx = %i)!",vIdxStart,vIdxEnd,curVidx);
turnEnd=0; isTurn=0;
}
}
unlockMessageMemory();
if (!isTurn) {
smileCondWaitWMtx( tickCond, dataFlgMtx ); // wait one smile tick for things to change
}
if (terminated) {
smileMutexUnlock(dataFlgMtx);
recog->process_want_terminate = TRUE;
return -1;
}
} while ((!isTurn)&&(!end));
//printf("turn getFv\n");
if (isTurn) {
int result=0;
curVec = NULL;
while (curVec == NULL) {
curVec = reader->getFrame(curVidx, -1, 0, &result);
// TODO: check if curVidx is behind ringbuffer storage space!!
if (result & DMRES_OORleft) {
long tmp = reader->getMinR()+10;
if (tmp > curVidx) {
SMILE_IWRN(2,"ASR processing tried to get feature data behind beginning of ringbuffer, which is no more available! Skipping a few frames to catch up... (%i) : %i -> %i",tmp-curVidx, curVidx, tmp);
curVidx = tmp;
}
}
if (curVec == NULL) {
smileCondWaitWMtx( tickCond, dataFlgMtx );
if (terminated) {
smileMutexUnlock(dataFlgMtx);
recog->process_want_terminate = TRUE;
return -1;
}
}
}
curVidx++;
}
//printf("turn: %f n=%i\n",curVec->dataF[curVec->N-1],curVec->N);
smileMutexUnlock(dataFlgMtx);
int i;
if (curVec != NULL) {
for (i=0; i<MIN( curVec->N, n ); i++) {
vec[i] = (float)(curVec->dataF[i]);
}
} else {
for (i=0; i<n; i++) {
vec[i] = 0.0;
}
}
// TODO: input segmentation (via smile ComponentMessages...??)
return ret;
}
