, including all inherited members.
| adapt_adapt() | PhoneModel | |
| adapt_adaptVar() | PhoneModel | |
| adapt_addAcumulatorData(int state, int contextKey, Vector *observation, double probability=1.0) | PhoneModel | |
| adapt_clear() | PhoneModel | |
| adapt_setAcTrain(int useLabel=-1, int useSegmentation=-1, FeaturePool *usePool=NULL) | TrainPhoneModel | |
| adapt_setAcumulators(int useLabel, int useSegmentation, FeaturePool *usePool) | PhoneModel | |
| adapt_setHelperMatrices() | PhoneModel | |
| adapt_setInitialNode(Adapt_AM_TreeNode *node) | PhoneModel | |
| adapt_setNode() | PhoneModel | |
| adapt_setVarTrans() | PhoneModel | |
| adapt_unAdapt() | PhoneModel | |
| addAccumulators(FILE *file) | PhoneModel | |
| addChain(TokenType **tokenNew, float likelihood, TokenType *token, int stateNr, int curTime, DecoderSettings *settings, float *bestL, bool checkCollission) | PhoneModel | [static] |
| addChain_lmla(TokenType **tokenNew, float likelihood, TokenType *token, int index, DecoderSettings *settings, float *bestL) | PhoneModel | [protected, static] |
| addChain_ordered(TokenType **tokenNew, float likelihood, TokenType *token, int stateNr, int curTime, DecoderSettings *settings, float *bestL) | PhoneModel | [static] |
| addCountedGaussians(TrainPhoneModel *source, int nmbr) | TrainPhoneModel | |
| addGaussian(Vector *v) | TrainPhoneModel | |
| appendSAT(FILE *outFile) | TrainPhoneModel | |
| baumWelch(int trainWhat, PhoneModel *doSat=NULL) | TrainPhoneModel | [protected] |
| channelInfoBlock | TrainPhoneModel | [protected] |
| copyGaussians(MixGaussian *destMixGaussian, int maxNmbr) | PhoneModel | |
| copyPhonePath(PLRType *pP) | PhoneModel | [static] |
| count(Vector *observation) | TrainPhoneModel | |
| decision_Matrix | TrainPhoneModel | [protected] |
| decision_numberOfModels | TrainPhoneModel | [protected] |
| decision_numberOfRules | TrainPhoneModel | [protected] |
| dim() const | PhoneModel | [inline] |
| dimensions | PhoneModel | [protected] |
| doNotuseBordersForTraining(bool useBordersNot) | TrainPhoneModel | |
| fillDistanceArray(int *distA) | TrainPhoneModel | |
| finishSAT() | TrainPhoneModel | |
| getClusterP(Vector *observation) | TrainPhoneModel | |
| getCoSim(TrainPhoneModel *t1, TrainPhoneModel *t2) | TrainPhoneModel | |
| getDominantGaussian() | TrainPhoneModel | |
| getKLDistance(TrainPhoneModel *t2) | TrainPhoneModel | |
| getLogPDFProbability(int contextKey, Vector *v) | PhoneModel | |
| getLookaheadLogP(double *vectorList, int timeStamp, bool doSecondHalf) | PhoneModel | [virtual] |
| getNormDistance() | TrainPhoneModel | |
| getNumberOfGaussians() | PhoneModel | |
| getOutput(int contextKey, TokenType **token, int tLength, TokenType **outToken, DecoderSettings *settings, float *bestL) | PhoneModel | [virtual] |
| getPDFProbability(int contextKey, Vector *v, int stateNr, int time) | PhoneModel | |
| getSilP(int useLabel, int useSegmentation, FeaturePool *usePool) | TrainPhoneModel | [protected] |
| getSilSumHist(Vector **histogram) | PhoneModel | |
| getStateNr(int contextKey, int state) | PhoneModel | |
| getStatistics(void) | PhoneModel | |
| getTrainSilP(int useLabel=-1, int useSegmentation=-1, FeaturePool *usePool=NULL) | TrainPhoneModel | |
| getTransition(int contextKey, bool toSelf, int stateNr) | PhoneModel | |
| guestTrainingLabel | TrainPhoneModel | [protected] |
| initialisePhonePath(PLRType *t) | PhoneModel | [static] |
| initialiseToken(TokenType **token) | PhoneModel | [static] |
| isSil | PhoneModel | [protected] |
| isSilModel() const | PhoneModel | [inline] |
| mapAdaptMeans() | PhoneModel | |
| maxNrOfGaussians() | TrainPhoneModel | |
| mixtureSetData | PhoneModel | |
| moveModelGaussians(TrainPhoneModel *model, double factor) | TrainPhoneModel | |
| normalize() | TrainPhoneModel | |
| PhoneModel(int dim=ASR_DEFAULT_VECTORSIZE) | PhoneModel | |
| PhoneModel(FILE *inFile, int dim=ASR_DEFAULT_VECTORSIZE, bool onlyUseFastP=false) | PhoneModel | |
| PhoneModel(MixGaussian *mix, double toNext) | PhoneModel | |
| printInfo(Vector *v) | PhoneModel | |
| printModel(FILE *fileMean, FILE *fileVariance, FILE *fileWeight) | PhoneModel | |
| processVector(int contextKey, Vector *v, int t, int index, TokenType **token, int tLength, TokenType *inToken, DecoderSettings *settings, float *bestL) | PhoneModel | [virtual] |
| readModel(FILE *inFile) | TrainPhoneModel | |
| replaceTokenLM(TokenType *nt, TokenType *token, float like, float *bestL) | PhoneModel | [protected, static] |
| resetPhoneAdmin() | PhoneModel | |
| setDecisionMatrix(int numberOfModels, int numberOfRules, int *dMatrix) | TrainPhoneModel | |
| setMaxGaussians(int maxGaussians) | TrainPhoneModel | |
| setSilTrans(double tr) | PhoneModel | |
| setTrainingData(FeaturePool *fp, int segmentationID, int labelID, int guestID=-1, int tSilP=100, int tSilMax=-1) | TrainPhoneModel | |
| silRinglastPos | PhoneModel | [protected] |
| startCount() | TrainPhoneModel | |
| stateMix_1 | PhoneModel | [protected] |
| stateMix_2 | PhoneModel | [protected] |
| stateMix_3 | PhoneModel | [protected] |
| statistics | PhoneModel | [protected] |
| stopCount() | TrainPhoneModel | |
| timeStamp | PhoneModel | [protected] |
| totalLength | TrainPhoneModel | [protected] |
| touchPDF(int contextKey, int t, MixGaussian **updateThese, double **resultHere) | PhoneModel | [virtual] |
| train(int maxGaussians, bool isSil, bool neverPrune=false, Vector **trainDiscr=NULL, Vector *trainDiscrMask=NULL, PhoneModel *doSAT=NULL, bool doFastTraining=false) | TrainPhoneModel | |
| trainingLabel | TrainPhoneModel | [protected] |
| trainingPool | TrainPhoneModel | [protected] |
| trainingSegment | TrainPhoneModel | [protected] |
| trainMMI(FILE *fileEnum, FILE *fileDenom) | TrainPhoneModel | |
| TrainPhoneModel(const char *n, int contextLeft, int contextRight, bool isSil, int dim, FeaturePoolInfo *infoBlock=NULL) | TrainPhoneModel | |
| TrainPhoneModel(MixGaussian *gmm, double trans, const char *name) | TrainPhoneModel | |
| TrainPhoneModel(TrainPhoneModel *model1, TrainPhoneModel *model2, int maxGaussians=-1) | TrainPhoneModel | |
| TrainPhoneModel(TrainPhoneModel *model1, TrainPhoneModel *model2, double rate) | TrainPhoneModel | |
| TrainPhoneModel(TrainPhoneModel *orgModel, int shiftLeftRight=0) | TrainPhoneModel | |
| TrainPhoneModel(FILE *inFile, int dim, FeaturePoolInfo *infoBlock=NULL) | TrainPhoneModel | |
| trainSilMax | TrainPhoneModel | [protected] |
| trainSilP | TrainPhoneModel | [protected] |
| trainWithoutBorders | TrainPhoneModel | [protected] |
| viterbi(int trainWhat) | TrainPhoneModel | [protected] |
| weightRinglastPos | PhoneModel | [protected] |
| writeAccumulators(FILE *file, FILE *fileF=NULL, FILE *fileST=NULL, bool doBinary=false) | PhoneModel | |
| writeModel(FILE *outFile) | PhoneModel | |
| writeSAT(FILE *outFile) | TrainPhoneModel | |
| ~PhoneModel() | PhoneModel | |
| ~TrainPhoneModel() | TrainPhoneModel | |