Uses of Class
marytts.features.FeatureDefinition

Packages that use FeatureDefinition

Package	Description
marytts.cart
marytts.cart.impose
marytts.cart.io
marytts.features
marytts.htsengine
marytts.machinelearning	Machine learning classes for K-Means clustering, Gaussian Mixture Models, and manual data generation for testing purposes.
marytts.tools.dbselection
marytts.tools.voiceimport
marytts.tools.voiceimport.traintrees
marytts.tools.voiceimport.vocalizations
marytts.unitselection
marytts.unitselection.analysis
marytts.unitselection.data
marytts.unitselection.select
marytts.util	Various relatively generic utilities.
marytts.vocalizations
weka.classifiers.trees.j48

Uses of FeatureDefinition in marytts.cart

Fields in marytts.cart declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	DirectedGraph.featDef
protected FeatureDefinition	DecisionNode.featureDefinition

Methods in marytts.cart that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	DirectedGraph.getFeatureDefinition()
FeatureDefinition	DecisionNode.getFeatureDefinition()

Methods in marytts.cart with parameters of type FeatureDefinition

Modifier and Type	Method and Description
void	FeatureVectorCART.load(String fileName, FeatureDefinition featDefinition, String[] setFeatureSequence)
String	LeafNode.StringAndFloatLeafNode.mostProbableString(FeatureDefinition featureDefinition, int featureIndex) Return the most probable value in this leaf, translated into its string representation using the featureIndex'th feature of the given feature definition.

Constructors in marytts.cart with parameters of type FeatureDefinition

Constructor and Description
CART(FeatureDefinition featDef) Build a new empty cart with the given feature definition.
CART(Node rootNode, FeatureDefinition featDef) Build a new cart with the given node as the root node
CART(Node rootNode, FeatureDefinition featDef, Properties properties) Build a new cart with the given node as the root node
DecisionNode.BinaryByteDecisionNode(int featureIndex, byte value, FeatureDefinition featureDefinition)
DecisionNode.BinaryByteDecisionNode(int uniqueId, FeatureDefinition featureDefinition) Creates an empty BinaryByteDecisionNode, the feature and feature value of this node should be filled with setFeatureAndFeatureValue() function.
DecisionNode.BinaryByteDecisionNode(String feature, String value, FeatureDefinition featureDefinition) Create a new binary String DecisionNode.
DecisionNode.BinaryFloatDecisionNode(int featureIndex, float value, FeatureDefinition featureDefinition) Create a new binary String DecisionNode.
DecisionNode.BinaryFloatDecisionNode(String feature, float value, FeatureDefinition featureDefinition)
DecisionNode.BinaryShortDecisionNode(int featureIndex, short value, FeatureDefinition featureDefinition)
DecisionNode.BinaryShortDecisionNode(String feature, String value, FeatureDefinition featureDefinition) Create a new binary String DecisionNode.
DecisionNode.ByteDecisionNode(int featureIndex, int numDaughters, FeatureDefinition featureDefinition) Build a new byte decision node
DecisionNode.ByteDecisionNode(String feature, int numDaughters, FeatureDefinition featureDefinition) Build a new byte decision node
DecisionNode.ShortDecisionNode(int featureIndex, int numDaughters, FeatureDefinition featureDefinition) Build a new short decision node
DecisionNode.ShortDecisionNode(String feature, int numDaughters, FeatureDefinition featureDefinition) Build a new short decision node
DecisionNode(int numDaughters, FeatureDefinition featureDefinition) Construct a new DecisionNode
DecisionNode(int featureIndex, int numDaughters, FeatureDefinition featureDefinition) Construct a new DecisionNode
DecisionNode(String feature, int numDaughters, FeatureDefinition featureDefinition) Construct a new DecisionNode
DirectedGraph(FeatureDefinition featDef) Build a new empty graph with the given feature definition.
DirectedGraph(Node rootNode, FeatureDefinition featDef) Build a new graph with the given node as the root node
DirectedGraph(Node rootNode, FeatureDefinition featDef, Properties properties) Build a new graph with the given node as the root node
StringPredictionTree(BufferedReader reader, FeatureDefinition featDefinition) This constructs a new string prediction tree from a stream containing a tree in wagon format.
StringPredictionTree(Node aRootNode, FeatureDefinition aFeatDef, String[] aTargetDecoding)

Uses of FeatureDefinition in marytts.cart.impose

Methods in marytts.cart.impose that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	FeatureArrayIndexer.getFeatureDefinition()

Constructors in marytts.cart.impose with parameters of type FeatureDefinition

Constructor and Description
FeatureArrayIndexer(FeatureVector[] featureVectors, FeatureDefinition featureDefinition) Constructor which loads the feature vector array but does not launch an indexing operation.
FeatureArrayIndexer(FeatureVector[] featureVectors, FeatureDefinition featureDefinition, int[] setFeatureSequence) Constructor which takes an array of feature vectors and launches an indexing operation according to a feature sequence constraint.
FeatureArrayIndexer(FeatureVector[] featureVectors, FeatureDefinition featureDefinition, String[] setFeatureSequence) Constructor which takes an array of feature vectors and launches an indexing operation according to a feature sequence constraint.

Uses of FeatureDefinition in marytts.cart.io

Methods in marytts.cart.io with parameters of type FeatureDefinition

Modifier and Type	Method and Description
Node	WagonCARTReader.load(BufferedReader reader, FeatureDefinition featDefinition) This loads a cart from a wagon tree in textual format, from a reader.
CART[]	HTSCARTReader.load(int numStates, InputStream treeStream, InputStream pdfStream, HMMData.PdfFileFormat fileFormat, FeatureDefinition featDefinition, PhoneTranslator phTranslator) Load the cart from the given file
Node	WagonCARTReader.load(String fileName, FeatureDefinition featDefinition, String[] dummy) Load the cart from the given file

Uses of FeatureDefinition in marytts.features

Fields in marytts.features declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	TargetFeatureComputer.featureDefinition

Methods in marytts.features that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	TargetFeatureComputer.getFeatureDefinition() Provide the feature definition that can be used to interpret the feature processors generated by this TargetFeatureComputer.
FeatureDefinition	FeatureDefinition.subset(String[] featureNamesToDrop) Create a new FeatureDefinition that contains a subset of the features in this.

Methods in marytts.features with parameters of type FeatureDefinition

Modifier and Type	Method and Description
boolean	FeatureDefinition.contains(FeatureDefinition other) Determine whether this FeatureDefinition is a superset of, or equal to, another FeatureDefinition.
boolean	FeatureDefinition.featureEquals(FeatureDefinition other) Determine whether two feature definitions are equal, with respect to number, names, and possible values of the three kinds of features (byte-valued, short-valued, continuous).
String	FeatureDefinition.featureEqualsAnalyse(FeatureDefinition other) An extension of the previous method.
String	FeatureVector.getFeatureAsString(int index, FeatureDefinition feaDef) A wrapper to getFeature(), to get the result as an String value, e.g., for subsequent System.out output.

Uses of FeatureDefinition in marytts.htsengine

Methods in marytts.htsengine that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	HMMData.getFeatureDefinition()

Methods in marytts.htsengine with parameters of type FeatureDefinition

Modifier and Type	Method and Description
String	PhoneTranslator.features2context(FeatureDefinition def, FeatureVector featureVector, Vector<String> featureList) Convert the feature vector into a context model name to be used by HTS/HTK.
String	PhoneTranslator.features2LongContext(FeatureDefinition def, FeatureVector featureVector, Vector<String> featureList) Convert the feature vector into a context model name to be used by HTS/HTK.
HTSModel	CartTreeSet.generateHTSModel(HMMData htsData, FeatureDefinition feaDef, FeatureVector fv, double oldErr) creates a HTSModel (pre-HMM optimization vector data for all parameter streams of a given phoneme) given a feature vector compare with original code in the main loop of marytts.modules.HTSEngine#processTargetList()
void	GVModelSet.loadGVModelSet(HMMData htsData, FeatureDefinition featureDef)
void	GVModelSet.loadSwitchGvFromFile(String gvFile, FeatureDefinition featDef, PhoneTranslator trickyPhones)
void	CartTreeSet.loadTreeSet(HMMData htsData, FeatureDefinition featureDef, PhoneTranslator trickyPhones) Loads all the CART trees
void	CartTreeSet.searchLf0InCartTree(HTSModel m, FeatureVector fv, FeatureDefinition featureDef, double uvthresh) Searches fv in Lf0Tree CART[] set of trees, per state, and fill the information in the HTSModel m.
void	CartTreeSet.searchMagInCartTree(HTSModel m, FeatureVector fv, FeatureDefinition featureDef) Searches fv in MagTree CART[] set of trees, per state, and fill the information in the HTSModel m.
void	CartTreeSet.searchMgcInCartTree(HTSModel m, FeatureVector fv, FeatureDefinition featureDef) Searches fv in mgcTree CART[] set of trees, per state, and fill the information in the HTSModel m.
void	CartTreeSet.searchStrInCartTree(HTSModel m, FeatureVector fv, FeatureDefinition featureDef) Searches fv in StrTree CART[] set of trees, per state, and fill the information in the HTSModel m.

Uses of FeatureDefinition in marytts.machinelearning

Methods in marytts.machinelearning that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	SoP.getFeatureDefinition()

Methods in marytts.machinelearning with parameters of type FeatureDefinition

Modifier and Type	Method and Description
double	SoP.solve(Target t, FeatureDefinition feaDef, boolean log) Solve the linear equation given the features (factors) in t and coeffs and factors in the SoP object * if interceptTterm = TRUE solution = coeffs[0] + coeffs[1]*factors[0] + coeffs[2]*factors[1] + ...
double	SoP.solve(Target t, FeatureDefinition feaDef, boolean log, boolean debug)

Constructors in marytts.machinelearning with parameters of type FeatureDefinition

Constructor and Description
SoP(FeatureDefinition featDef) Build a new empty sop with the given feature definition.
SoP(String line, FeatureDefinition feaDef)

Uses of FeatureDefinition in marytts.tools.dbselection

Fields in marytts.tools.dbselection declared as FeatureDefinition

Modifier and Type	Field and Description
protected static FeatureDefinition	FeatureMakerMaryServer.featDef
protected static FeatureDefinition	FeatureMaker.featDef
static FeatureDefinition	DatabaseSelector.featDef

Methods in marytts.tools.dbselection with parameters of type FeatureDefinition

Modifier and Type	Method and Description
static byte[]	CoverageUtils.toCoverageFeatures(String featureNames, FeatureDefinition def, FeatureVector[] featureVectors) Convert the given feature vectors to the coverage features format, containing all byte features in a single byte array.

Constructors in marytts.tools.dbselection with parameters of type FeatureDefinition

Constructor and Description
CoverageDefinition(FeatureDefinition featDef, CoverageFeatureProvider cfProvider, String configFile) Build a new coverage definition and read in the config file

Uses of FeatureDefinition in marytts.tools.voiceimport

Fields in marytts.tools.voiceimport declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	PhoneFeatureFileWriter.featureDefinition
protected FeatureDefinition	F0PolynomialTreeTrainer.featureDefinition
protected FeatureDefinition	CARTBuilder.WagonCallerThread.featureDefinition
protected FeatureDefinition	F0PolynomialInspector.inFeatureDefinition
protected FeatureDefinition	AcousticFeatureFileWriter.inFeatureDefinition
protected FeatureDefinition	HalfPhoneFeatureFileWriter.leftFeatureDef
protected FeatureDefinition	F0PolynomialFeatureFileWriter.outFeatureDefinition
protected FeatureDefinition	AcousticFeatureFileWriter.outFeatureDefinition
protected FeatureDefinition	HalfPhoneFeatureFileWriter.rightFeatureDef

Methods in marytts.tools.voiceimport with parameters of type FeatureDefinition

Modifier and Type	Method and Description
void	CARTBuilder.buildAndDumpDistanceTables(FeatureVector[] featureVectors, String filename, FeatureDefinition featDef) Build the distance tables for the units from which we have the feature vectors and dump them to a file with the given filename
void	FestivalCARTImporter.dumpCARTS(String destDir, FeatureDefinition featDef) Dump the CARTs in the cart map to destinationDir/CARTS.bin
void	CARTBuilder.dumpFeatureVectors(FeatureVector[] featureVectors, FeatureDefinition featDef, String filename) Dump the given feature vectors to a file with the given filename
CART	CARTBuilder.importCART(String filename, FeatureDefinition featDef) Read in the CARTs from festival/trees/ directory, and store them in a CARTMap
void	FestivalCARTImporter.importCARTS(String festvoxDirectory, String destDir, FeatureDefinition featDef) Read in the CARTs from festival/trees/ directory, and store them in a CARTMap
boolean	CARTBuilder.replaceLeaves(CART cart, FeatureDefinition featureDefinition) For each leaf in the CART, run Wagon on the feature vectors in this CART, and replace leaf by resulting CART

Constructors in marytts.tools.voiceimport with parameters of type FeatureDefinition

Constructor and Description
CARTBuilder.WagonCallerThread(String id, LeafNode leafToReplace, FeatureDefinition featureDefinition, FeatureVector[] featureVectors, String descFilename, String valueFilename, String distanceTableFilename, String cartFilename, int balance, int stop, String ESTDIR)

Uses of FeatureDefinition in marytts.tools.voiceimport.traintrees

Constructors in marytts.tools.voiceimport.traintrees with parameters of type FeatureDefinition

Constructor and Description
AgglomerativeClusterer(FeatureVector[] features, FeatureDefinition featureDefinition, List<String> featuresToUse, DistanceMeasure dist)
AgglomerativeClusterer(FeatureVector[] features, FeatureDefinition featureDefinition, List<String> featuresToUse, DistanceMeasure dist, float proportionTestData)
Wagon(String id, FeatureDefinition featureDefinition, FeatureVector[] featureVectors, DistanceMeasure aDistanceMeasure, File dir, int balance, int stop) Set up a new wagon process.

Uses of FeatureDefinition in marytts.tools.voiceimport.vocalizations

Fields in marytts.tools.voiceimport.vocalizations declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	VocalizationFeatureFileWriter.featureDefinition
protected FeatureDefinition	VocalizationF0PolynomialInspector.inFeatureDefinition
protected FeatureDefinition	VocalizationF0PolyFeatureFileWriter.inFeatureDefinition
protected FeatureDefinition	VocalizationF0PolyFeatureFileWriter.outFeatureDefinition

Uses of FeatureDefinition in marytts.unitselection

Methods in marytts.unitselection that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	UnitSelectionVoice.getF0CartsFeatDef()

Uses of FeatureDefinition in marytts.unitselection.analysis

Fields in marytts.unitselection.analysis declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	VoiceDataDumper.featureDefinition

Uses of FeatureDefinition in marytts.unitselection.data

Fields in marytts.unitselection.data declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	FeatureFileReader.featureDefinition
protected FeatureDefinition	HalfPhoneFeatureFileReader.leftWeights
protected FeatureDefinition	HalfPhoneFeatureFileReader.rightWeights

Methods in marytts.unitselection.data that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	FeatureFileReader.getFeatureDefinition()
FeatureDefinition	HalfPhoneFeatureFileReader.getLeftWeights()
FeatureDefinition	HalfPhoneFeatureFileReader.getRightWeights()

Methods in marytts.unitselection.data with parameters of type FeatureDefinition

Modifier and Type	Method and Description
FeatureVector[]	FeatureFileReader.featureVectorMapping(FeatureDefinition newFeatureDefinition) feature vector mapping according to new feature definition Note: The new feature definition should be a subset of original feature definition

Uses of FeatureDefinition in marytts.unitselection.select

Fields in marytts.unitselection.select declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	FFRTargetCostFunction.featureDefinition
protected FeatureDefinition	HalfPhoneFFRTargetCostFunction.leftWeights
protected FeatureDefinition	HalfPhoneFFRTargetCostFunction.rightWeights

Methods in marytts.unitselection.select that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	TargetCostFunction.getFeatureDefinition() Provide access to the Feature Definition used.
FeatureDefinition	FFRTargetCostFunction.getFeatureDefinition()
FeatureDefinition	DiphoneFFRTargetCostFunction.getFeatureDefinition() Provide access to the Feature Definition used.

Methods in marytts.unitselection.select with parameters of type FeatureDefinition

Modifier and Type	Method and Description
protected double	VocalizationFFRTargetCostFunction.cost(Target target, Unit unit, FeatureDefinition weights, WeightFunc[] weightFunctions) Compute the goodness-of-fit of a given unit for a given target
protected double	FFRTargetCostFunction.cost(Target target, Unit unit, FeatureDefinition weights, WeightFunc[] weightFunctions)
protected double	VocalizationFFRTargetCostFunction.featureCost(Target target, Unit unit, String featureName, FeatureDefinition weights, WeightFunc[] weightFunctions) Compute the goodness-of-fit between given unit and given target for a given feature
protected double	FFRTargetCostFunction.featureCost(Target target, Unit unit, String featureName, FeatureDefinition weights, WeightFunc[] weightFunctions)
void	JoinModelCost.setFeatureDefinition(FeatureDefinition def) Set the feature definition to use for interpreting target feature vectors.

Constructors in marytts.unitselection.select with parameters of type FeatureDefinition

Constructor and Description
VocalizationFFRTargetCostFunction(VocalizationFeatureFileReader ffr, FeatureDefinition fDef)

Uses of FeatureDefinition in marytts.util

Methods in marytts.util that return FeatureDefinition

Modifier and Type	Method and Description
static FeatureDefinition	FeatureUtils.readFeatureDefinition(InputStream featureStream)
static FeatureDefinition	FeatureUtils.readFeatureDefinition(String targetFeaturesData)

Uses of FeatureDefinition in marytts.vocalizations

Fields in marytts.vocalizations declared as FeatureDefinition

Modifier and Type	Field and Description
protected FeatureDefinition	VocalizationSelector.f0FeatureDefinition
protected FeatureDefinition	VocalizationSelector.featureDefinition

Methods in marytts.vocalizations that return FeatureDefinition

Modifier and Type	Method and Description
FeatureDefinition	VocalizationSelector.getFeatureDefinition() Get feature definition used to select suitable candidate

Uses of FeatureDefinition in weka.classifiers.trees.j48

Methods in weka.classifiers.trees.j48 with parameters of type FeatureDefinition

Modifier and Type	Method and Description
static CART	TreeConverter.c45toStringCART(weka.classifiers.trees.j48.C45PruneableClassifierTree c45Tree, FeatureDefinition aFeatDef, weka.core.Instances inst) This converts the WEKA-style ClassifierTree into a Mary CART tree.
static StringPredictionTree	TreeConverter.c45toStringPredictionTree(weka.classifiers.trees.j48.C45PruneableClassifierTree c45Tree, FeatureDefinition aFeatDef, weka.core.Instances inst) This converts the WEKA-style ClassifierTree into a Mary CART tree.