// Training of client Speakers
// Input: Xlist Format: ID_Client Seg1 Seg2 ..
// Output: ALIZE_MixtureServer (binaire) + GMM / Client (binary)
int TrainTarget(Config& config)
{
String inputClientListFileName = config.getParam("targetIdList");
String inputWorldFilename = config.getParam("inputWorldFilename");
String outputSERVERFilename = "";
if (config.existsParam("mixtureServer")) outputSERVERFilename =config.getParam("mixtureServer");
bool initByClient=false; // In this case, the init model is read from the file
if (config.existsParam("initByClient")) initByClient=config.getParam("initByClient").toBool();
bool saveEmptyModel=false;
if (config.existsParam("saveEmptyModel")) saveEmptyModel=config.getParam("saveEmptyModel").toBool();
// label for selected frames - Only the frames associated with this label, in the label files, will be used
bool fixedLabelSelectedFrame=true;
String labelSelectedFrames;
if (config.existsParam("useIdForSelectedFrame")) // the ID of each speaker is used as labelSelectedFrame ?
fixedLabelSelectedFrame=(config.getParam("useIdForSelectedFrame").toBool()==false);
if (fixedLabelSelectedFrame) // the label is decided by the command line and is unique for the run
labelSelectedFrames=config.getParam("labelSelectedFrames");
bool modelData=false;
if (config.existsParam("useModelData")) modelData=config.getParam("useModelData").toBool();
String initModelS=inputWorldFilename;
if (modelData) if (config.existsParam("initModel")) initModelS=config.getParam("initModel"); // Use a specific model for Em init
bool outputAdaptParam=false;
if (config.existsParam("superVector")) outputAdaptParam=true;
bool NAP=false;
Matrix <double> ChannelMatrix;
if (config.existsParam("NAP")) {
if (verbose) cout<< "Removing channel effect with NAP from " << config.getParam("NAP") << " of size: [";
NAP=true; // enable NAP
ChannelMatrix.load(config.getParam("NAP"),config); //get Channel Matrix from args and load in a Matrix object
if (verbose) cout << ChannelMatrix.rows() << "," <<ChannelMatrix.cols() << "]" << endl;
}
bool saveCompleteServer=false;
try{
XList inputClientList(inputClientListFileName,config); // read the Id + filenames for each client
XLine * linep;
inputClientList.getLine(0);
MixtureServer ms(config);
StatServer ss(config, ms);
if (verbose) cout << "TrainTarget - Load world model [" << inputWorldFilename<<"]"<<endl;
MixtureGD& world = ms.loadMixtureGD(inputWorldFilename);
MixtureGD& initModel =ms.loadMixtureGD(initModelS);
if (verbose) cout <<"Use["<<initModelS<<"] for initializing EM"<<endl;
// *********** Target loop *****************
while ((linep=inputClientList.getLine()) != NULL){ // linep gives the XLine with the Id of a given client and the list of files
String *id=linep->getElement(); // Get the Client ID (id)
XLine featureFileListp=linep->getElements(); // Get the list of feature file for the client (end of the line)
if (verbose) cout << "Train model ["<<*id<<"]"<<endl;
if (!fixedLabelSelectedFrame){ // the ID is used as label for selecting the frame
labelSelectedFrames=*id;
if (verbose) cout <<*id<<" is used for label selected frames"<<endl;
}
FeatureServer fs(config,featureFileListp); // Reading the features (from several files)
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(featureFileListp,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files...
MixtureGD & adaptedMixture = ms.duplicateMixture(world,DUPL_DISTRIB); // Creating final as a copy of the world model
MixtureGD & clientMixture= ms.duplicateMixture(world,DUPL_DISTRIB);
if (initByClient){ // During trainig data statistic estimation by EM,
clientMixture= ms.loadMixtureGD(*id); // the client model is used for initalization
adaptedMixture=clientMixture;
}
long codeSelectedFrame=labelServer.getLabelIndexByString(labelSelectedFrames); // Get the index of the cluster with in interest audio segments
if (codeSelectedFrame==-1){ // No data for this model !!!!!!!!!!!!!!
cout << " WARNING - NO DATA FOR TRAINING ["<<*id<<"]";
if (saveEmptyModel){
cout <<" World model is returned"<<endl; // In this case, the client model is the world model
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
adaptedMixture.save(*id, config); // Save the client model
}
}
else{
SegCluster& selectedSegments=segmentsServer.getCluster(codeSelectedFrame); // Gives the cluster of the selected/used segments
if (!initByClient) ms.setMixtureId(clientMixture,*id); // Set the client model Id
if (modelData) modelBasedadaptModel(config,ss,ms,fs,selectedSegments,world,clientMixture,initModel); // EM algo with MAP criterion
else adaptModel(config,ss,ms,fs,selectedSegments,world,clientMixture); // EM algo with MAP criterion
if (NAP) {
if (verbose) cout << "NAP on SVs" << endl;
computeNap(clientMixture,ChannelMatrix);
}
if (outputAdaptParam) {
RealVector<double> v;
getSuperVector(v,world,clientMixture,config);
String out=config.getParam("saveVectorFilesPath")+*id+config.getParam("vectorFilesExtension");
Matrix <double> vv=(Matrix<double>)v;
vv.save(out,config);
}
if (!outputAdaptParam) {
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
clientMixture.save(*id, config); // Save the client model
}
if (!saveCompleteServer){
long tid=ms.getMixtureIndex(*id); // TO BE SUPPRESSED BY
ms.deleteMixtures(tid,tid); // ADDING a delete on a mixture pointor
ms.deleteUnusedDistribs();
}
}
} // end of the the target loop
// Save the complete mixture server
// TODO
} // fin try
catch (Exception& e)
{
cout << e.toString().c_str() << endl;
}
return 0;
}
// Training of client Speakers
// The same than TrainTarget but train simultaneoulsy 1 model for each cluster (set of segments with the same label)
// found in the input files labels.
// One option in order to save the n models as a modification of the world model - save disk space
int TrainTargetByLabel(Config& config)
{
String inputClientListFileName = config.getParam("targetIdList");
String inputWorldFilename = config.getParam("inputWorldFilename");
String outputSERVERFilename = config.getParam("mixtureServer");
// label for selected frames - Only the frames associated with this label, in the label files, will be used
//bool fixedLabelSelectedFrame;
bool initByClient=false;
bool aprioriWorld=true;
if (config.existsParam("initByClient")) initByClient=true;
if (config.existsParam("aprioriClient")){
aprioriWorld=false;
initByClient=true;
}
bool saveCompleteServer=false;
bool outputAdaptParam=false;
if (config.existsParam("outputAdaptParam")) outputAdaptParam=config.getParam("outputAdaptParam").toBool();
try{
XList inputClientList(inputClientListFileName,config); // read the Id + filenames for each client
XLine *linep;
inputClientList.getLine(0);
MixtureServer ms(config);
StatServer ss(config, ms);
if (verbose) cout << "TrainTarget - by label opption - Load world model [" << inputWorldFilename<<"]"<<endl;
MixtureGD& world = ms.loadMixtureGD(inputWorldFilename);
// *********** Target loop *****************
while ((linep=inputClientList.getLine()) != NULL){ // linep gives the XLine with the Id of a given client and the list of files
String clientId=(*linep->getElement()); // Get the Client ID (clientId)
XLine featureFileListp=linep->getElements(); // Get the list of feature file for the client (end of the line)
FeatureServer fs(config,featureFileListp); // Reading the features (from several files)
if (verbose) cout << "Train label models for client ["<<clientId<<"]"<<endl;
MixtureGD &clientGModel=ms.createMixtureGD();
if (initByClient) {
if (verbose) cout << "Load client model [" << clientId <<"]"<<endl;
clientGModel = ms.loadMixtureGD(clientId); //not necessary to load client model
}
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(featureFileListp,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files...
for (unsigned long codeSelectedFrame=0;codeSelectedFrame<segmentsServer.getClusterCount();codeSelectedFrame++){ // For each cluster
String clientIdByLabel=clientId+"_"+labelServer.getLabel(codeSelectedFrame).getString(); // Build the model name for the client and the label
if (verbose) cout << "Train labeldependent model ["<<clientIdByLabel<<"]"<<endl;
SegCluster& selectedSegments=segmentsServer.getCluster(codeSelectedFrame); // Gives the cluster of the selected/used segments
MixtureGD & clientMixture = ms.duplicateMixture(world,DUPL_DISTRIB); // Creating clientMixture as a copy of the world model
ms.setMixtureId(clientMixture,clientIdByLabel); // Set the client model Id
if (initByClient) // During trainig data statistic estimation by EM,
clientMixture=clientGModel; // the global client model is used for initalization
if (aprioriWorld) // EM algo with MAP criterion
adaptModel(config,ss,ms,fs,selectedSegments,world,clientMixture); // A priori info is the world model
else adaptModel(config,ss,ms,fs,selectedSegments,clientGModel,clientMixture);// A priori info is the client model-by default initByClient is also set
if (!outputAdaptParam) {
if (verbose) cout << "Save client model ["<<clientIdByLabel<<"]" << endl;
clientMixture.save(clientIdByLabel, config); // Save the client model
}
if (!saveCompleteServer){
long tid=ms.getMixtureIndex(clientIdByLabel); // TO BE SUPPRESSED BY
ms.deleteMixtures(tid,tid); // ADDING a delete on a mixture pointor
ms.deleteUnusedDistribs();
}
}
if (!saveCompleteServer){
long tid=ms.getMixtureIndex(clientId); // TO BE SUPPRESSED BY
ms.deleteMixtures(tid,tid); // ADDING a delete on a mixture pointor
ms.deleteUnusedDistribs();
} // end of the the label loop fr a speaker
} // end of the the target loop
// Save the complete mixture server
// TODO
} // fin try
catch (Exception& e)
{
cout << e.toString().c_str() << endl;
}
return 0;
}
//-----------------------------------------------------------------------------------------------------------------------------------------------------------
int TrainTargetLFA(Config& config)
{
String inputClientListFileName = config.getParam("targetIdList");
String inputWorldFilename = config.getParam("inputWorldFilename");
String outputSERVERFilename = "";
if (config.existsParam("mixtureServer")) outputSERVERFilename =config.getParam("mixtureServer");
bool initByClient=false; // In this case, the init model is read from the file
if (config.existsParam("initByClient")) initByClient=config.getParam("initByClient").toBool();
bool saveEmptyModel=false;
if (config.existsParam("saveEmptyModel")) saveEmptyModel=config.getParam("saveEmptyModel").toBool();
// label for selected frames - Only the frames associated with this label, in the label files, will be used
bool fixedLabelSelectedFrame=true;
String labelSelectedFrames;
if (config.existsParam("useIdForSelectedFrame")) // the ID of each speaker is used as labelSelectedFrame ?
fixedLabelSelectedFrame=(config.getParam("useIdForSelectedFrame").toBool()==false);
if (fixedLabelSelectedFrame) // the label is decided by the command line and is unique for the run
labelSelectedFrames=config.getParam("labelSelectedFrames");
bool modelData=false;
if (config.existsParam("useModelData")) modelData=config.getParam("useModelData").toBool();
String initModelS=inputWorldFilename;
if (modelData) if (config.existsParam("initModel")) initModelS=config.getParam("initModel"); // Use a specific model for Em init
bool outputAdaptParam=false;
if (config.existsParam("superVectors")) outputAdaptParam=true;
try{
XList inputClientList(inputClientListFileName,config); // read the Id + filenames for each client
XLine * linep;
inputClientList.getLine(0);
MixtureServer ms(config);
StatServer ss(config, ms);
if (verbose) cout << "(TrainTarget) Latent Factor Analysis - Load world model [" << inputWorldFilename<<"]"<<endl;
MixtureGD& world = ms.loadMixtureGD(inputWorldFilename);
if (verbose) cout <<"(TrainTarget) Use["<<initModelS<<"] for initializing EM"<<endl;
//LOAD JFA MAtrices
unsigned long svsize=world.getDistribCount()*world.getVectSize();
Matrix<double> U, V;
DoubleVector D(svsize,svsize);
//Initialise EC matrix
if(config.existsParam("eigenChannelMatrix")){
String uName = config.getParam("matrixFilesPath") + config.getParam("eigenChannelMatrix") + config.getParam("loadMatrixFilesExtension");
U.load (uName, config);
if (verboseLevel >=1) cout << "(TrainTargetLFA) Init EC matrix from "<< config.getParam("eigenChannelMatrix") <<" from EigenChannel Matrix: "<<", rank: ["<<U.rows() << "] sv size: [" << U.cols() <<"]"<<endl;
}
else{
U.setDimensions(1,svsize);
U.setAllValues(0.0);
if (verboseLevel >1) cout << "(TrainTargetLFA) Init EC matrix to 0"<<endl;
}
V.setDimensions(1,svsize);
V.setAllValues(0.0);
if (verboseLevel >=1) cout << "(TrainTargetLFA) Init EV matrix to 0"<<endl;
//Initialise the D matrix for MAP adaptation
for(unsigned long i=0; i<world.getDistribCount(); i++){
for(unsigned long j = 0; j<world.getVectSize(); j++){
D[i*world.getVectSize()+j] = sqrt(1.0/(world.getDistrib(i).getCovInv(j)*config.getParam("regulationFactor").toDouble()));
}
}
// *********** Target loop *****************
while ((linep=inputClientList.getLine()) != NULL){ // linep gives the XLine with the Id of a given client and the list of files
String *id=linep->getElement(); // Get the Client ID (id)
XLine featureFileListp=linep->getElements(); // Get the list of feature file for the client (end of the line)
if (verbose) cout << "(TrainTargetLFA) Train model ["<<*id<<"]"<<endl;
XList ndx; ndx.addLine() = featureFileListp;
JFAAcc jfaAcc(ndx,config,"TrainTarget");
//Charger les matrices V, U et D a partir des objets matrice existant.
jfaAcc.loadEV(V, config); jfaAcc.loadEC(U, config); jfaAcc.loadD(D);
//Initialise VU matrix
jfaAcc.initVU();
FeatureServer fs(config,featureFileListp); // Reading the features (from several files)
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(featureFileListp,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files...
MixtureGD & adaptedMixture = ms.duplicateMixture(world,DUPL_DISTRIB); // Creating final as a copy of the world model
MixtureGD & clientMixture= ms.duplicateMixture(world,DUPL_DISTRIB);
long codeSelectedFrame=labelServer.getLabelIndexByString(labelSelectedFrames); // Get the index of the cluster with in interest audio segments
if (codeSelectedFrame==-1){ // No data for this model !!!!!!!!!!!!!!
cout << " WARNING - NO DATA FOR TRAINING ["<<*id<<"]";
if (saveEmptyModel){
cout <<" World model is returned"<<endl; // In this case, the client model is the world model
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
adaptedMixture.save(*id, config); // Save the client model
}
}
else{
SegCluster& selectedSegments=segmentsServer.getCluster(codeSelectedFrame); // Gives the cluster of the selected/used segments
//Compute the JFA statistics
jfaAcc.computeAndAccumulateJFAStat(selectedSegments,fs,config);
//Estimate X and Y in one time for each speaker
jfaAcc.storeAccs();
jfaAcc.estimateVUEVUT(config);
jfaAcc.estimateAndInverseL_VU(config);
jfaAcc.substractMplusDZ(config);
jfaAcc.estimateYX();
//Reinitialise the accumulators
jfaAcc.resetTmpAcc();
jfaAcc.restoreAccs();
//Split X and Y estimates
jfaAcc.splitYX();
//Substract speaker and channel statistics M + VUYX
jfaAcc.substractMplusVUYX();
//Estimate Z for each speaker
double tau = config.getParam("regulationFactor").toLong();
jfaAcc.estimateZMAP(tau);
//Reinitialise the accumulators
jfaAcc.resetTmpAcc();
jfaAcc.restoreAccs();
bool varAdapt = false;
if((config.existsParam("varAdapt")) && ( config.getParam("varAdapt").toBool() )){
varAdapt = true;
}
DoubleVector clientModel(jfaAcc.getSvSize(), jfaAcc.getSvSize());
clientModel.setSize(jfaAcc.getSvSize());
jfaAcc.getMplusVYplusDZ(clientModel, 0);
//Create the ClientMixture
svToModel(clientModel, clientMixture);
clientMixture.save(*id, config);
long tid=ms.getMixtureIndex(*id);
ms.deleteMixtures(tid,tid);
ms.deleteUnusedDistribs();
}
}
} // fin try
catch (Exception& e) {cout << e.toString().c_str() << endl;}
return 0;
}
//-----------------------------------------------------------------------------------------------------------------------------------------------------------
int TrainTargetJFA(Config& config)
{
String inputClientListFileName = config.getParam("targetIdList");
String inputWorldFilename = config.getParam("inputWorldFilename");
String outputSERVERFilename = "";
if (config.existsParam("mixtureServer")) outputSERVERFilename =config.getParam("mixtureServer");
bool initByClient=false; // In this case, the init model is read from the file
if (config.existsParam("initByClient")) initByClient=config.getParam("initByClient").toBool();
bool saveEmptyModel=false;
if (config.existsParam("saveEmptyModel")) saveEmptyModel=config.getParam("saveEmptyModel").toBool();
// label for selected frames - Only the frames associated with this label, in the label files, will be used
bool fixedLabelSelectedFrame=true;
String labelSelectedFrames;
if (config.existsParam("useIdForSelectedFrame")) // the ID of each speaker is used as labelSelectedFrame ?
fixedLabelSelectedFrame=(config.getParam("useIdForSelectedFrame").toBool()==false);
if (fixedLabelSelectedFrame) // the label is decided by the command line and is unique for the run
labelSelectedFrames=config.getParam("labelSelectedFrames");
bool modelData=false;
if (config.existsParam("useModelData")) modelData=config.getParam("useModelData").toBool();
String initModelS=inputWorldFilename;
if (modelData) if (config.existsParam("initModel")) initModelS=config.getParam("initModel"); // Use a specific model for Em init
bool outputAdaptParam=false;
if (config.existsParam("superVectors")) outputAdaptParam=true;
try{
XList inputClientList(inputClientListFileName,config); // read the Id + filenames for each client
XLine * linep;
inputClientList.getLine(0);
MixtureServer ms(config);
StatServer ss(config, ms);
if (verbose) cout << "(TrainTarget) Joint Factor Analysis - Load world model [" << inputWorldFilename<<"]"<<endl;
MixtureGD& world = ms.loadMixtureGD(inputWorldFilename);
if (verbose) cout <<"(TrainTarget) Use["<<initModelS<<"] for initializing EM"<<endl;
//LOAD JFA MAtrices
Matrix<double> U, V;
DoubleVector D;
//Initialise EC matrix
if(config.existsParam("eigenChannelMatrix")){
String uName = config.getParam("matrixFilesPath") + config.getParam("eigenChannelMatrix") + config.getParam("loadMatrixFilesExtension");
U.load (uName, config);
if (verboseLevel >=1) cout << "(TrainTargetJFA) Init EC matrix from "<< config.getParam("eigenChannelMatrix") <<" from EigenChannel Matrix: "<<", rank: ["<<U.rows() << "] sv size: [" << U.cols() <<"]"<<endl;
}
else{
unsigned long sS = world.getVectSize() * world.getDistribCount();
U.setDimensions(1,sS);
U.setAllValues(0.0);
if (verboseLevel >=1) cout << "(TrainTargetJFA) Init EC matrix to 0"<<endl;
}
//Initialise EV matrix
if(config.existsParam("eigenVoiceMatrix")){
String vName = config.getParam("matrixFilesPath") + config.getParam("eigenVoiceMatrix") + config.getParam("loadMatrixFilesExtension");
V.load (vName, config);
if (verboseLevel >=1) cout << "(TrainTargetJFA) Init EV matrix from "<< config.getParam("eigenVoiceMatrix") <<" from EigenVoice Matrix: "<<", rank: ["<<V.rows() << "] sv size: [" << V.cols() <<"]"<<endl;
}
else{
unsigned long sS = world.getVectSize() * world.getDistribCount();
V.setDimensions(1,sS);
V.setAllValues(0.0);
if (verboseLevel >=1) cout << "(TrainTargetJFA) Init EV matrix to 0"<<endl;
}
//Initialise D matrix
if(config.existsParam("DMatrix")){
String dName = config.getParam("matrixFilesPath") + config.getParam("DMatrix") + config.getParam("loadMatrixFilesExtension");
Matrix<double> tmpD(dName, config);
if( (tmpD.rows() != 1) || ( tmpD.cols() != world.getVectSize()*world.getDistribCount() ) ){
throw Exception("Incorrect dimension of D Matrix",__FILE__,__LINE__);
}
else{
D.setSize(world.getVectSize()*world.getDistribCount());
D.setAllValues(0.0);
for(unsigned long i=0; i<world.getVectSize()*world.getDistribCount(); i++){
D[i] = tmpD(0,i);
}
if (verboseLevel >=1) cout << "(TrainTargetJFA) Init D matrix from "<<config.getParam("DMatrix")<<endl;
}
}
else{
unsigned long sS = world.getVectSize() * world.getDistribCount();
D.setSize(sS);
D.setAllValues(0.0);
if (verboseLevel >1) cout << "(TrainTargetJFA) Init D matrix to 0"<<endl;
}
// *********** Target loop *****************
while ((linep=inputClientList.getLine()) != NULL){ // linep gives the XLine with the Id of a given client and the list of files
String *id=linep->getElement(); // Get the Client ID (id)
XLine featureFileListp=linep->getElements(); // Get the list of feature file for the client (end of the line)
if (verbose) cout << "(TrainTarget) Train model ["<<*id<<"]"<<endl;
XList ndx; ndx.addLine() = featureFileListp;
JFAAcc jfaAcc(ndx,config,"TrainTarget");
//Load V, U and D from existing matrices.
jfaAcc.loadEV(V, config); jfaAcc.loadEC(U, config); jfaAcc.loadD(D);
//Initialize VU matrix
jfaAcc.initVU();
FeatureServer fs(config,featureFileListp); // Reading the features (from several files)
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(featureFileListp,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files...
MixtureGD & adaptedMixture = ms.duplicateMixture(world,DUPL_DISTRIB); // Creating final as a copy of the world model
MixtureGD & clientMixture= ms.duplicateMixture(world,DUPL_DISTRIB);
long codeSelectedFrame=labelServer.getLabelIndexByString(labelSelectedFrames); // Get the index of the cluster with in interest audio segments
if (codeSelectedFrame==-1){ // No data for this model !!!!!!!!!!!!!!
cout << " WARNING - NO DATA FOR TRAINING ["<<*id<<"]";
if (saveEmptyModel){
cout <<" World model is returned"<<endl; // In this case, the client model is the world model
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
adaptedMixture.save(*id, config); // Save the client model
}
}
else{
SegCluster& selectedSegments=segmentsServer.getCluster(codeSelectedFrame); // Gives the cluster of the selected/used segments
//Compute the JFA statistics
jfaAcc.computeAndAccumulateJFAStat(selectedSegments,fs,config);
//Estimate X and Y in one time for each speaker
jfaAcc.storeAccs();
jfaAcc.estimateVUEVUT(config);
jfaAcc.estimateAndInverseL_VU(config);
jfaAcc.substractMplusDZ(config);
jfaAcc.estimateYX();
//Reinitialise the accumulators
jfaAcc.resetTmpAcc();
jfaAcc.restoreAccs();
//Split X and Y estimates
jfaAcc.splitYX();
//Substract speaker and channel statistics M + VUYX
jfaAcc.substractMplusVUYX();
//Estimate Z for each speaker
jfaAcc.estimateZ();
//Reinitialise the accumulators
jfaAcc.resetTmpAcc();
jfaAcc.restoreAccs();
bool varAdapt = false;
if((config.existsParam("varAdapt")) && ( config.getParam("varAdapt").toBool() )){
varAdapt = true;
}
DoubleVector clientSV(jfaAcc.getSvSize(), jfaAcc.getSvSize());
clientSV.setSize(jfaAcc.getSvSize());
DoubleVector clientModel(jfaAcc.getSvSize(), jfaAcc.getSvSize());
clientModel.setSize(jfaAcc.getSvSize());
bool saveMixture = true;
if((config.existsParam("saveMixture")) && !( config.getParam("saveMixture").toBool() )) saveMixture = false;
bool saveSuperVector = true;
if((config.existsParam("saveSuperVector")) && !( config.getParam("saveSuperVector").toBool() )) saveSuperVector = false;
bool saveX = false;
bool saveY = false;
bool saveZ = false;
if(config.existsParam("saveX")) saveX = config.getParam("saveX").toBool();
if(config.existsParam("saveY")) saveY = config.getParam("saveY").toBool();
if(config.existsParam("saveZ")) saveZ = config.getParam("saveZ").toBool();
String xExtension = ".x"; String yExtension = ".y"; String zExtension = ".z";
if(config.existsParam("xExtension")) xExtension = config.getParam("xExtension");
if(config.existsParam("yExtension")) yExtension = config.getParam("yExtension");
if(config.existsParam("zExtension")) zExtension = config.getParam("zExtension");
jfaAcc.getVYplusDZ(clientSV, 0);
jfaAcc.getMplusVYplusDZ(clientModel, 0);
//WARNING !!!!! only the SuperVector model is divided by the UBM Co-Variance.
for(unsigned long i=0; i<jfaAcc.getSvSize(); i++){
clientSV[i] *= jfaAcc.getUbmInvVar()[i];
}
//Create the ClientMixture to save if required
if(saveMixture){
svToModel(clientModel, clientMixture);
clientMixture.save(*id, config);
}
String svPath,svExt,svFile;
if(saveSuperVector){
String svPath =config.getParam("saveVectorFilesPath");
String svExt =config.getParam("vectorFilesExtension");
String svFile =svPath+*id+svExt;
((Matrix<double>)clientSV).save(svFile,config);
}
// String svPath=config.getParam("saveVectorFilesPath");
if(saveX){
String xFile=svPath+*id+xExtension;
jfaAcc.saveX(xFile,config);
}
if(saveY){
String yFile=svPath+*id+yExtension;
jfaAcc.saveY(yFile,config);
}
if(saveZ){
String zFile=svPath+*id+zExtension;
jfaAcc.saveZ(zFile,config);
}
long tid=ms.getMixtureIndex(*id);
ms.deleteMixtures(tid,tid);
ms.deleteUnusedDistribs();
}
}
} // fin try
catch (Exception& e) {cout << e.toString().c_str() << endl;}
return 0;
}
//-----------------------------------------------------------------------------------------------------------------------------------------------------------
int TrainTargetFA(Config& config)
{
String inputClientListFileName = config.getParam("targetIdList");
String inputWorldFilename = config.getParam("inputWorldFilename");
String outputSERVERFilename = "";
if (config.existsParam("mixtureServer")) outputSERVERFilename =config.getParam("mixtureServer");
bool initByClient=false; // In this case, the init model is read from the file
if (config.existsParam("initByClient")) initByClient=config.getParam("initByClient").toBool();
bool saveEmptyModel=false;
if (config.existsParam("saveEmptyModel")) saveEmptyModel=config.getParam("saveEmptyModel").toBool();
// label for selected frames - Only the frames associated with this label, in the label files, will be used
bool fixedLabelSelectedFrame=true;
String labelSelectedFrames;
if (config.existsParam("useIdForSelectedFrame")) // the ID of each speaker is used as labelSelectedFrame ?
fixedLabelSelectedFrame=(config.getParam("useIdForSelectedFrame").toBool()==false);
if (fixedLabelSelectedFrame) // the label is decided by the command line and is unique for the run
labelSelectedFrames=config.getParam("labelSelectedFrames");
bool modelData=false;
if (config.existsParam("useModelData")) modelData=config.getParam("useModelData").toBool();
String initModelS=inputWorldFilename;
if (modelData) if (config.existsParam("initModel")) initModelS=config.getParam("initModel"); // Use a specific model for Em init
bool outputAdaptParam=false;
if (config.existsParam("superVectors")) outputAdaptParam=true;
Matrix <double> ChannelMatrix;
if (verbose) cout<< "EigenMAP and Eigenchannel with [" << config.getParam("initChannelMatrix") << "] of size: [";
ChannelMatrix.load(config.getParam("initChannelMatrix"),config); //get Channel Matrix from args and load in a Matrix object
if (verbose) cout << ChannelMatrix.rows() << "," <<ChannelMatrix.cols() << "]" << endl;
bool varAdapt=false;
if (config.existsParam("FAVarAdapt")) varAdapt=true;
bool saveCompleteServer=false;
try{
XList inputClientList(inputClientListFileName,config); // read the Id + filenames for each client
XLine * linep;
inputClientList.getLine(0);
MixtureServer ms(config);
StatServer ss(config, ms);
if (verbose) cout << "(TrainTarget) Factor Analysis - Load world model [" << inputWorldFilename<<"]"<<endl;
MixtureGD& world = ms.loadMixtureGD(inputWorldFilename);
if (verbose) cout <<"(TrainTarget) Use["<<initModelS<<"] for initializing EM"<<endl;
// *********** Target loop *****************
while ((linep=inputClientList.getLine()) != NULL){ // linep gives the XLine with the Id of a given client and the list of files
String *id=linep->getElement(); // Get the Client ID (id)
XLine featureFileListp=linep->getElements(); // Get the list of feature file for the client (end of the line)
if (verbose) cout << "(TrainTarget) Train model ["<<*id<<"]"<<endl;
FeatureServer fs(config,featureFileListp); // Reading the features (from several files)
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(featureFileListp,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files...
MixtureGD & adaptedMixture = ms.duplicateMixture(world,DUPL_DISTRIB); // Creating final as a copy of the world model
MixtureGD & clientMixture= ms.duplicateMixture(world,DUPL_DISTRIB);
long codeSelectedFrame=labelServer.getLabelIndexByString(labelSelectedFrames); // Get the index of the cluster with in interest audio segments
if (codeSelectedFrame==-1){ // No data for this model !!!!!!!!!!!!!!
cout << " WARNING - NO DATA FOR TRAINING ["<<*id<<"]";
if (saveEmptyModel){
cout <<" World model is returned"<<endl; // In this case, the client model is the world model
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
adaptedMixture.save(*id, config); // Save the client model
}
}
else{
SegCluster& selectedSegments=segmentsServer.getCluster(codeSelectedFrame); // Gives the cluster of the selected/used segments
/// **** Factor Analysis Stuff
XList faNdx;
faNdx.addLine()=featureFileListp;
FactorAnalysisStat FA(faNdx,fs,config); // give all features to FA stats
//FA.computeAndAccumulateGeneralFAStats(selectedSegments,fs,config);
for(int i=0;i<config.getParam("nbTrainIt").toLong();i++){
if (verbose) cout << "------ Iteration ["<<i<<"] ------"<<endl;
FA.computeAndAccumulateGeneralFAStats(selectedSegments,fs,config);
/*if (!varAdapt) FA.getTrueSpeakerModel(clientMixture,linep->getElement(1));
else FA.getFactorAnalysisModel(clientMixture,linep->getElement(1));
if (verbose) cout << "LLK for model["<<*id<<"] at it["<<i-1<<"]="<<FA.getLLK(selectedSegments,clientMixture,fs,config) << endl; */
FA.estimateAndInverseL(config);
FA.substractSpeakerStats();
FA.getXEstimate();
FA.substractChannelStats();
FA.getYEstimate();
}
MixtureGD & sessionMixture= ms.duplicateMixture(world,DUPL_DISTRIB);
bool saveSessionModel=false;
if (config.existsParam("saveSessionModel")) saveSessionModel=true;
if (saveSessionModel) FA.getSessionModel(sessionMixture,linep->getElement(1));
if (!varAdapt) FA.getTrueSpeakerModel(clientMixture,linep->getElement(1)); // basically compute M_s_h=M+Dy_s and get a model
else FA.getFactorAnalysisModel(clientMixture,linep->getElement(1)); // get FA variance adapted model
if (verbose) cout << "Final LLK for model["<<*id<<"]="<<FA.getLLK(selectedSegments,clientMixture,fs,config) << endl;
/// **** End of FA
if (!outputAdaptParam) {
if (verbose) cout << "Save client model ["<<*id<<"]" << endl;
clientMixture.save(*id, config); // Save the client model
if (saveSessionModel) {
String sessionfile=*id+".session";
if (verbose) cout << "Save session model ["<<sessionfile<<"]" << endl;
sessionMixture.save(sessionfile,config);
}
}
if (!saveCompleteServer){
long tid=ms.getMixtureIndex(*id); // TO BE SUPPRESSED BY
ms.deleteMixtures(tid,tid); // ADDING a delete on a mixture pointor
ms.deleteUnusedDistribs();
}
}
}
} // fin try
catch (Exception& e) {cout << e.toString().c_str() << endl;}
return 0;
}
void launchTurnDetectionProcess(Config & config){
String outputFilesPath=config.getParam("outputFilesPath");
String inputListFileName = config.getParam("listFileToSegment"); //file including the list of files to segment
XLine classToAnalyse; //Array of labels to analyze
classToAnalyse.reset();
if(verbose){
cout << "*********** Current Configuration ***************" << endl;
for(unsigned long i=0; i<config.getParamCount(); i++){
cout << config.getParamName(i) << " => " << config.getParamContent(i) << endl;
}
cout << "*************************************************" << endl;
}
try{
XList listLabel;
XList listFileName;
try{
listFileName.load(inputListFileName,config);
}
catch(FileNotFoundException& e){
cout<<"There is no files to segment !"<<endl;
exit(-1);
}
listFileName.rewind();
XLine *filep;
while ((filep=listFileName.getLine()) != NULL){ // For each stream of audio data (in several files in the same line)
const XLine & listFile=filep->getElements(); // One or several files, as several part of the same stream
MixtureServer ms(config);
StatServer ss(config, ms);
SegServer Resultat;
FeatureServer fs(config,listFile); // Reading the features (one or more files)
SegServer segmentsServer; // Create the segment server for managing the segments/clusters
LabelServer labelServer; // Create the lable server, for indexing the segments/clusters
initializeClusters(listFile,segmentsServer,labelServer,config); // Reading the segmentation files for each feature input file
verifyClusterFile(segmentsServer,fs,config); // Verify if the segments ending before the end of the feature files
String fileInit=listFile.getElement(0);
config.setParam("fileSize", String::valueOf(fs.getFeatureCountOfASource(fileInit)));
if(config.existsParam("fileRefPath")){
// assumption: all the segments in the segment server come from the same source file !!!
displayAllSegmentsFromRef(config, fileInit, fs.getFeatureCountOfASource(fileInit));
}
for(unsigned long icluster=0;icluster<segmentsServer.getClusterCount();icluster++){ // for each cluster
SegCluster& cluster=segmentsServer.getCluster(icluster);
SegServer segOutputServer;
TurnDetection(config,cluster,segOutputServer,ss,fs,ms,labelServer);
displayAllSegments(config,segOutputServer);
for(unsigned long i=0;i<segOutputServer.getSegCount();i++){
Seg& segment=segOutputServer.getSeg(i);
Resultat.createSeg(segment.begin(),segment.length(),segment.labelCode(),segment.string(),segment.sourceName());
}
}//for icluster
saveSegmentation(config,Resultat,fs,outputFilesPath,1);
}// while
} // end try
catch (Exception& e){
cout << e.toString().c_str() << endl;
}
}//launchTurnDetectionProcess
void TurnDetection(Config& config, SegCluster& cluster,SegServer& segOutputServer,
StatServer& ss,FeatureServer &fs,MixtureServer&
ms,LabelServer& labelServer){
SegServer segTemp;
segOutputServer.removeAllClusters();
segOutputServer.removeAllSegs();
SegServer actualSeg;
String et_temp="speech";
Label l(et_temp);
SegCluster& clusterSeg=actualSeg.createCluster(labelServer.addLabel(l),et_temp," "); //Create the cluster L
String crit="DGLR";
if(config.existsParam("clusteringCrit"))
crit=config.getParam("clusteringCrit");
double threshold=0.0;
if(config.existsParam("clusteringCritThresh"))
threshold=config.getParam("clusteringCritThresh").toDouble();
unsigned long winSize=50;
if(config.existsParam("winSize")) winSize=config.getParam("winSize").toLong();
unsigned long winStep=5;
if(config.existsParam("winStep")) winStep=config.getParam("winStep").toLong();
double alpha=0.7;
if(config.existsParam("alpha")) alpha=config.getParam("alpha").toDouble();
unsigned long start1=0, end1=0;
unsigned long start2=0, end2=0;
unsigned long accu=0;
for(unsigned long iseg=0; iseg<cluster.getCount(); iseg++){
Seg& segment=(Seg&)cluster.get(iseg);
if(verbose)
cout << "Segment" << iseg << ": " << segment.begin() << " " << endSeg(&segment) << endl;
if(segment.length() <= 2*winSize){
clusterSeg.add(actualSeg.createSeg(segment.begin(),endSeg(&segment)-segment.begin()+1,0,segment.string(),segment.sourceName()));
if(debug) cout << "add: " << segment.begin() << " " << endSeg(&segment) << endl;
}
else{
ObjectRefVector res;
start1=segment.begin();
end1=start1+winSize-1;
start2=end1+1;
end2=start2+winSize-1;
accu = start1;
while(end2 < endSeg(&segment)){
if(verbose){
cout << "Computation between: " << start1 << " " << end1;
cout << " and " << start2 << " " << end2 << endl;
}
SegCluster& c1=segTemp.createCluster();
c1.add(segTemp.createSeg(start1,winSize,0,"null",segment.sourceName()));
SegCluster& c2=segTemp.createCluster();
c2.add(segTemp.createSeg(start2,winSize,0,"null",segment.sourceName()));
CritInfo *resCrit=new CritInfo(clusteringCriterionWithoutWorldInitOneGaus(config, c1, c2, ss, fs,crit),false,end1);
res.addObject((Object&)*resCrit);
start1+=winStep;
end1+=winStep;
start2+=winStep;
end2+=winStep;
}
/* smoothing */
/* for(unsigned long i=1; i<res.size()-1; i++){
CritInfo &resCrit=(CritInfo&)(res.getObject(i));
CritInfo &resCritP=(CritInfo&)(res.getObject(i-1));
CritInfo &resCritN=(CritInfo&)(res.getObject(i+1));
resCrit.setValue(0.25*resCritP.getValue()+0.25*resCritN.getValue()+0.5*resCrit.getValue());
}
*/
DoubleVector score_buffer;
score_buffer.setSize(2);
score_buffer[0 % 2]=((CritInfo&)(res.getObject(0))).getValue();
for(unsigned long i=1; i<res.size()-1; i++)
{
CritInfo &resCrit=(CritInfo&)(res.getObject(i));
CritInfo &resCritN=(CritInfo&)(res.getObject(i+1));//right window
score_buffer[i % 2]=resCrit.getValue();
resCrit.setValue(0.25*score_buffer[(i-1) % 2]+0.25*resCritN.getValue()+0.5*resCrit.getValue());
}
/* to look for maxima in the criterion value curve */
/* if difference on left and right of a point with neighboor points is over alpha*standard deviation => maxima is found ! */
double sum=0.0;
double sum2=0.0;
for(unsigned long i=0; i<res.size(); i++){
CritInfo &resCrit=(CritInfo&)res.getObject(i);
sum += resCrit.getValue();
sum2+=resCrit.getValue()*resCrit.getValue();
}
double mean=sum/(double)res.size();
double std=sqrt((sum2/(double)(res.size())-(mean*mean)));
if(verbose){
cout << "Mean and std: " << mean << " " << std << endl;
}
CritInfo &resCrit=(CritInfo&)res.getObject(0);
resCrit.setDec(false);
for(unsigned long i=1, j=0; i<res.size()-1; i++){
/* for each value */
/* search left min */
j=i-1;
double minL=((CritInfo&)res.getObject(i)).getValue();
bool ok=true;
while(ok && (j > 0)){
if(((CritInfo&)res.getObject(j)).getValue() < minL){
minL =((CritInfo&)res.getObject(j)).getValue();
j--;
}else{
ok = false;
}
}
if(myabs(((CritInfo&)res.getObject(i)).getValue()-minL) > alpha*std){
// search right min
j=i+1;
double minR=((CritInfo&)res.getObject(i)).getValue();
ok=true;
while(ok && (j < res.size())){
if(((CritInfo&)res.getObject(j)).getValue() < minR){
minR = ((CritInfo&)res.getObject(j)).getValue();
j++;
}else{
ok = false;
}
}
if(myabs(((CritInfo&)res.getObject(i)).getValue()-minR) > alpha*std){
((CritInfo&)res.getObject(i)).setDec(true);
}else{
((CritInfo&)res.getObject(i)).setDec(false);
}
}else{
((CritInfo&)res.getObject(i)).setDec(false);
}
/*double max=((CritInfo&)res.getObject(i)).getValue();
double minL=((CritInfo&)res.getObject(i-1)).getValue();
double minR=((CritInfo&)res.getObject(i+1)).getValue();
if((minL < max) && (minR < max) && (max > mean+std))
((CritInfo&)res.getObject(i)).setDec(true);
else
((CritInfo&)res.getObject(i)).setDec(false);
*/
}
start1 = segment.begin();
for(unsigned long i=0; i<res.size(); i++){
cout << ((CritInfo&)res.getObject(i)).getFrame() << " " << ((CritInfo&)res.getObject(i)).getValue() << " => " << ((CritInfo&)res.getObject(i)).getDec() << endl;
if(((CritInfo&)res.getObject(i)).getDec()){
clusterSeg.add(actualSeg.createSeg(start1,((CritInfo&)res.getObject(i)).getFrame()-start1+1,0,segment.string(),segment.sourceName()));
if(verbose) cout << "add: " << start1 << " " << ((CritInfo&)res.getObject(i)).getFrame() << endl;
start1=((CritInfo&)res.getObject(i)).getFrame()+1;
}
}
// last point
cout << "last point: " << start1 << " fin segment: " << endSeg(&segment) << endl;
if(start1 < endSeg(&segment)){
clusterSeg.add(actualSeg.createSeg(start1,endSeg(&segment)-start1+1,0,segment.string(),segment.sourceName()));
if(verbose) cout << "add: " << start1 << " " << endSeg(&segment) << endl;
}
}
}
displayAllClusters(config, actualSeg);
segOutputServer=actualSeg;
}
