A B C D E F G H I J L M N O P Q R S T U W

A

addClassificationParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single classification parameter object

addClassificationParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) classification parameters vector

addFeatureExtractionParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single feature extraction parameter object

addFeatureExtractionParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) feature extraction parameters vector

addFeatureVector(double[], String, int, int, int) - Method in class marf.Storage.TrainingSet

Adds new feature vector to the mean and recomputes the mean

addFFT(double[]) - Method in class marf.gui.Spectrogram

Adds FFT spectrum to the data to dump

addFilename(String) - Method in class marf.Storage.TrainingSet.TrainingSample

A filename to the training set.

addInput(Neuron, double) - Method in class marf.Classification.NeuralNetwork.Neuron

Adds an input neuron and its associated weight

addLPC(double[], int, int) - Method in class marf.gui.Spectrogram

Adds LPC spectrum to the data to dump

addOutput(Neuron) - Method in class marf.Classification.NeuralNetwork.Neuron

Adds an output neuron

addPreprocessingParam(Object) - Method in class marf.Storage.ModuleParams

Adds (appends) a single preprocessing parameter object

addPreprocessingParams(Vector) - Method in class marf.Storage.ModuleParams

Adds (appends) preprocessing parameters vector

adFeatures - Variable in class marf.FeatureExtraction.FeatureExtraction

An array of features extracted (coefficiencies and/or amplitude values)

adSample - Variable in class marf.Storage.Sample

Sample data array (amplitudes)

autocorrelation(double[], int) - Static method in class marf.FeatureExtraction.LPC.LPC

Implements the least-square autocorrelation method

B

BANDPASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use bandpass filter

BandpassFilter - class marf.Preprocessing.FFTFilter.BandpassFilter.

Class BandpassFilter

BandpassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.BandpassFilter

BandpassFilter Constructor

C

Cepstral - class marf.FeatureExtraction.Cepstral.Cepstral.

Class Cepstral

CEPSTRAL - Static variable in class marf.MARF

Indicates to use cepstral analysis

Cepstral(Preprocessing) - Constructor for class marf.FeatureExtraction.Cepstral.Cepstral

Cepstral Constructor

CHEBYSHEV_DISTANCE - Static variable in class marf.MARF

Indicates to use Chebyshev distance for classification

ChebyshevDistance - class marf.Classification.Distance.ChebyshevDistance.

Class ChebyshevDistance

ChebyshevDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.ChebyshevDistance

ChebyshevDistance Constructor

Classification - class marf.Classification.Classification.

Class Classification

Classification(FeatureExtraction) - Constructor for class marf.Classification.Classification

Generic Classification Constructor

ClassificationException - exception marf.Classification.ClassificationException.

Class ClassificationException

ClassificationException(String) - Constructor for class marf.Classification.ClassificationException

Generic exception

classify() - Method in class marf.Classification.Classification

Generic classification routine.

classify() - Method in class marf.Classification.Markov.Markov

Not Implemented

classify() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Neural Network implementation of classification routine

classify() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

classify() - Method in class marf.Classification.Distance.Distance

Classify the feature vector based on on whatever distance() derivatives implement.

classify() - Method in class marf.Classification.RandomClassification.RandomClassification

Picks an ID at random

commit() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Applies changes made to neurons on every net's layer

commit() - Method in class marf.Classification.NeuralNetwork.Neuron

Applies weight changes

cropAudio(double, double) - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to crop arbitrary part of the audio sample.

cropAudio(double, double) - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of cropAudio() for testing.

cropAudio(double, double) - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of cropAudio()

cropAudio(double, double) - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of cropAudio()

D

data - Variable in class marf.gui.Spectrogram

The data vector

DEBUG - Static variable in class marf.MARF

Debug flag.

debug(String) - Static method in class marf.MARF

Outputs param to STDERR if DEBUG is enabled

DEFAULT_CHANNELS - Static variable in class marf.Storage.Loaders.WAVLoader

Default 1

DEFAULT_CHUNK_SIZE - Static variable in class marf.FeatureExtraction.FFT.FFT

Default number (1024) of doubles per chunk in a feature vector.

DEFAULT_CHUNK_SIZE - Static variable in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Default number (256) of doubles per chunk in a feature vector.

DEFAULT_EPOCH_NUMBER - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default number of epoch iterations of 64 if none supplied

DEFAULT_FREQUENCY - Static variable in class marf.Storage.Loaders.WAVLoader

Default 8000 Hz

DEFAULT_MIN_ERROR - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default minimum training error of 0.1 if none supplied

DEFAULT_OUTPUT_NEURON_BITS - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

How many binary Neurons in the output layer.

DEFAULT_SAMPLE_BIT_SIZE - Static variable in class marf.Storage.Loaders.WAVLoader

Default 16

DEFAULT_TRAINING_CONSTANT - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

Default training constant of 1 if none supplied

delta - Variable in class marf.Classification.NeuralNetwork.Neuron

Used in error calculation

Distance - class marf.Classification.Distance.Distance.

Class Distance

distance(double[], double[]) - Method in class marf.Classification.Distance.ChebyshevDistance

ChebyshevDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.Distance

Generic distance routine.

distance(double[], double[]) - Method in class marf.Classification.Distance.EuclideanDistance

EuclideanDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.MahalanobisDistance

Partial MahalanobisDistance implementation

distance(double[], double[]) - Method in class marf.Classification.Distance.MinkowskiDistance

MinkowskiDistance implementation

Distance(FeatureExtraction) - Constructor for class marf.Classification.Distance.Distance

Distance Constructor

DoFFT(double[], double[], double[], double[], int) - Static method in class marf.FeatureExtraction.FFT.FFT

FFT algorithm, translated from "Numerical Recipes in C++" Implements the Fast Fourier Transform, which performs a discrete Fourier transform in O(nlogn).

DoLPC(double[], double[], double[], int) - Static method in class marf.FeatureExtraction.LPC.LPC

Does LPC algorithm NOTE: input is assumed to be windowed, ie: input.length = N

Dummy - class marf.Preprocessing.Dummy.Dummy.

Class Dummy

DUMMY - Static variable in class marf.MARF

Indicates to use Dummy preprocessing module (just normalization)

Dummy(Sample) - Constructor for class marf.Preprocessing.Dummy.Dummy

Dummy Constructor

DUMP_CSV_TEXT - Static variable in class marf.Storage.TrainingSet

Indicates to dump training set data as CSV text file.

DUMP_GZIP_BINARY - Static variable in class marf.Storage.TrainingSet

Indicates to dump training set data as gzipped binary file.

dump() - Method in class marf.Preprocessing.Preprocessing

Not Implemented

dump() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of dump() for testing.

dump() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

dump() - Method in class marf.FeatureExtraction.FFT.FFT

Not Implemented

dump() - Method in class marf.FeatureExtraction.LPC.LPC

Not Implemented

dump() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

dump() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

dump() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

dump() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Not Implemented

dump() - Method in class marf.Classification.Classification

Generic implementation of dump() for TrainingSet

dump() - Method in class marf.Classification.Markov.Markov

Not Implemented

dump() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Dumps Neural Net to an XML file

dump() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

dump() - Method in class marf.Classification.RandomClassification.RandomClassification

Dumps "training set" of IDs

dump() - Method in interface marf.Storage.StorageManager

An object must know how dump itself to a file.

dump() - Method in class marf.Storage.TrainingSet

Dump the current training set to disk

dump() - Method in class marf.gui.Spectrogram

Dumps spectrogram

dump() - Method in class marf.gui.WaveGrapher

Dumps graph of wave in the CSV format

dump(BufferedWriter) - Method in class marf.Storage.TrainingSet.TrainingSample

Write one training sample to a text file.

dumpXML(String) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Dumps Neural Network as XML file

E

Endpoint - class marf.Preprocessing.Endpoint.Endpoint.

Class Endpoint

ENDPOINT - Static variable in class marf.MARF

Indicates to use endpointing

Endpoint(Sample) - Constructor for class marf.Preprocessing.Endpoint.Endpoint

Endpoint Constructor

EUCLIDEAN_DISTANCE - Static variable in class marf.MARF

Indicates to use Euclidean distance for classification

EuclideanDistance - class marf.Classification.Distance.EuclideanDistance.

Class EuclideanDistance

EuclideanDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.EuclideanDistance

EuclideanDistance Constructor

eval() - Method in class marf.Classification.NeuralNetwork.Neuron

Evaluates current neuron's value

existsFilename(String) - Method in class marf.Storage.TrainingSet.TrainingSample

Check existance of the file in the training set.

extractFeatures() - Method in class marf.FeatureExtraction.FeatureExtraction

Abstract feature extraction routine.

extractFeatures() - Method in class marf.FeatureExtraction.FFT.FFT

FFT Implementation of extractFeatures()

extractFeatures() - Method in class marf.FeatureExtraction.LPC.LPC

LPC Implementation of extractFeatures()

extractFeatures() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

extractFeatures() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

extractFeatures() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

extractFeatures() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Random Gaussian feature extracton.

F

F0 - class marf.FeatureExtraction.F0.F0.

Class F0

F0 - Static variable in class marf.MARF

Indicates to use F0

F0(Preprocessing) - Constructor for class marf.FeatureExtraction.F0.F0

F0 Constructor

FeatureExtraction - class marf.FeatureExtraction.FeatureExtraction.

Class FeatureExtraction

FeatureExtraction(Preprocessing) - Constructor for class marf.FeatureExtraction.FeatureExtraction

FeatureExtraction constructor

FeatureExtractionException - exception marf.FeatureExtraction.FeatureExtractionException.

Class FeatureExtractionException

FeatureExtractionException(String) - Constructor for class marf.FeatureExtraction.FeatureExtractionException

Generic exception

FFT - class marf.FeatureExtraction.FFT.FFT.

Class FFT

FFT - Static variable in class marf.MARF

Indicates to use FFT

FFT(Preprocessing) - Constructor for class marf.FeatureExtraction.FFT.FFT

FFT Constructor

FFTFilter - class marf.Preprocessing.FFTFilter.FFTFilter.

FFTFilter class

FFTFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.FFTFilter

FFTFilter Constructor

filter(double[], double[]) - Method in class marf.Preprocessing.FFTFilter.FFTFilter

Perform a filter by the following algorithm: sample -> window -> FFT -> buffer buffer * frequency response buffer -> IFFT -> window -> sample Window used is square root of Hamming window, because the sum at half-window overlap is a constant, which avoids amplitude distortion from noise.

freqResponse - Variable in class marf.Preprocessing.FFTFilter.FFTFilter

Frequency repsonse to be multiplied by the incoming value

G

generate(int, int[], int) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Generates virgin net at random.

getAudioFormat() - Method in class marf.Storage.Sample

getClassification() - Static method in class marf.MARF

Retrieves current Classification reference

getClassificationMethod() - Static method in class marf.MARF

Gets classification method to be used

getClassificationParams() - Method in class marf.Storage.ModuleParams

getConfig() - Static method in class marf.MARF

Returns a string representation of the current MARF configuration

getCurrentSubject() - Static method in class marf.MARF

Gets ID of a subject currently being trained on

getDumpMode() - Method in class marf.Storage.TrainingSet

Retrieves current dump mode

getDumpSpectrogram() - Static method in class marf.MARF

Whether spectrogram wanted or not

getDumpWaveGraph() - Static method in class marf.MARF

Whether wave graph wanted or not

getFeatureExtraction() - Static method in class marf.MARF

Retrieves current FeatureExtraction reference

getFeatureExtractionMethod() - Static method in class marf.MARF

Gets currently selected feature extraction method.

getFeatureExtractionMethod() - Method in class marf.Storage.TrainingSet

Returns preprocessing method used on this training set

getFeatureExtractionParams() - Method in class marf.Storage.ModuleParams

getFeaturesArray() - Method in class marf.FeatureExtraction.FeatureExtraction

Allows retrieval of a feature vector

getID() - Method in class marf.Storage.Result

Returns result's ID

getIntVersion() - Static method in class marf.MARF

Returns an integer representation of the MARF version

getMeanCount() - Method in class marf.Storage.TrainingSet.TrainingSample

Retrieves current mean count

getMeanVector() - Method in class marf.Storage.TrainingSet.TrainingSample

Retrieves the mean vector

getMessage() - Method in class marf.util.MARFException

getModuleParams() - Static method in class marf.MARF

Gets module-specific parameters an application programmer passed on to the module

getNextChunk(double[]) - Method in class marf.Storage.Sample

Gets the next chunk of audio data and places it into chunkArray.

getPreprocessing() - Static method in class marf.MARF

Retrieves current Preprocessing reference

getPreprocessingMethod() - Static method in class marf.MARF

Gets currently selected preprocessing method.

getPreprocessingMethod() - Method in class marf.Storage.TrainingSet

Returns preprocessing method used on this training set

getPreprocessingParams() - Method in class marf.Storage.ModuleParams

getRes() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Gets outputs of a neural network run

getResult() - Static method in class marf.MARF

Gets the entire Result object

getResult() - Method in class marf.Classification.Classification

Retrieves the classification result

getSample() - Static method in class marf.MARF

Retrieves current Sample reference

getSample() - Method in class marf.Preprocessing.Preprocessing

Returns enclosed sample.

getSample() - Method in class marf.Storage.SampleLoader

getSampleArray() - Method in class marf.Storage.Sample

Retrieves array containing audio data of the entire sample.

getSampleFile() - Static method in class marf.MARF

Obtains filename of a sample currently being processed

getSampleFormat() - Static method in class marf.MARF

Gets input sample file format

getSampleLoader() - Static method in class marf.MARF

Retrieves current SampleLoader reference

getSampleSize() - Method in class marf.Storage.Sample

Returns the length of the sample.

getSampleSize() - Method in class marf.Storage.SampleLoader

Retrieves the length of the sample (# of audio data in the audio stream).

getSecondClosestID() - Method in class marf.Storage.Result

Returns second closest ID

getSubjectID() - Method in class marf.Storage.TrainingSet.TrainingSample

Retrieves Subject ID of a particular training sample

getTrainingSamples() - Method in class marf.Storage.TrainingSet

Retrieves training samples

getTrainingSetFile() - Method in class marf.Storage.TrainingSet

Retrieves current training set file name

getVersion() - Static method in class marf.MARF

Returns a string representation of the MARF version

H

hamming(double[]) - Static method in class marf.FeatureExtraction.FeatureExtraction

Applies hamming window to an array of doubles

hamming(int, int) - Static method in class marf.FeatureExtraction.FeatureExtraction

Retrieves a single value of hamming window based on length and index within the widow

HIDDEN - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates middle (hidden) neuron

HIGH_FREQUENCY_BOOST_FFT_FILTER - Static variable in class marf.MARF

Indicates to use filter boosting high frequencies

HIGH_PASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use high pass FFT filter

HighFrequencyBoost - class marf.Preprocessing.FFTFilter.HighFrequencyBoost.

HighFrequencyBoost Class

HighFrequencyBoost(Sample) - Constructor for class marf.Preprocessing.FFTFilter.HighFrequencyBoost

HighFrequencyBoost Constructor

HighPassFilter - class marf.Preprocessing.FFTFilter.HighPassFilter.

HighPassFilter Class

HighPassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.HighPassFilter

HighPassFilter Constructor

I

iArrayIndex - Variable in class marf.Storage.Sample

Chunk pointer in the sample array

iFormat - Variable in class marf.Storage.Sample

Sample's format

incMeanCount() - Method in class marf.Storage.TrainingSet.TrainingSample

Increases mean count by one

indent(BufferedWriter, int) - Static method in class marf.Classification.NeuralNetwork.NeuralNetwork

Indents the output according to the requested tabulation.

initialize(String, boolean) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Parses XML and produces NNet.

INPUT - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates input neuron

InvalidSampleFormatException - exception marf.util.InvalidSampleFormatException.

Class InvalidSampleFormatException

InvalidSampleFormatException(int) - Constructor for class marf.util.InvalidSampleFormatException

Generic exception

InvalidSampleFormatException(String) - Constructor for class marf.util.InvalidSampleFormatException

J

JAXP_SCHEMA_LANGUAGE - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

JAXP 1.2 Schema

JAXP_SCHEMA_SOURCE - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

JAXP 1.2 Schem URL

L

loadSample(File) - Method in class marf.Storage.SampleLoader

SampleLoader interface.

loadSample(File) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

loadSample(File) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

loadSample(File) - Method in class marf.Storage.Loaders.WAVLoader

Loads WAV sample data from a file.

loadSample(String) - Method in class marf.Storage.SampleLoader

Same as loadSample(File) but takes filename as an argument.

LOW_PASS_FFT_FILTER - Static variable in class marf.MARF

Indicates to use low pass FFT filter

LowPassFilter - class marf.Preprocessing.FFTFilter.LowPassFilter.

LowPassFilter Class

LowPassFilter(Sample) - Constructor for class marf.Preprocessing.FFTFilter.LowPassFilter

LowPassFilter Constructor

LPC - class marf.FeatureExtraction.LPC.LPC.

Class LPC

LPC - Static variable in class marf.MARF

Indicates to use LPC

LPC(Preprocessing) - Constructor for class marf.FeatureExtraction.LPC.LPC

LPC Constructor

M

MAHALANOBIS_DISTANCE - Static variable in class marf.MARF

Indicates to use Mahalanobis distance for classification

MahalanobisDistance - class marf.Classification.Distance.MahalanobisDistance.

Class MahalanobisDistance

MahalanobisDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.MahalanobisDistance

MahalanobisDistance Constructor

MARF - class marf.MARF.

Class MARF

MARFException - exception marf.util.MARFException.

Class MARFException

MARFException(String) - Constructor for class marf.util.MARFException

Generic exception

MARFException(String, Exception) - Constructor for class marf.util.MARFException

This is used for debug purposes only with some unusual Exception's.

Markov - class marf.Classification.Markov.Markov.

Class Markov

MARKOV - Static variable in class marf.MARF

Indicates to use Hidden Markov Models for classification

Markov(FeatureExtraction) - Constructor for class marf.Classification.Markov.Markov

Markov Constructor

max - Variable in class marf.gui.Spectrogram

Current maximum

min - Variable in class marf.gui.Spectrogram

Current minimum

MINKOWSKI_DISTANCE - Static variable in class marf.MARF

Indicates to use Minkowski distance for classification

MinkowskiDistance - class marf.Classification.Distance.MinkowskiDistance.

Class MinkowskiDistance

MinkowskiDistance(FeatureExtraction) - Constructor for class marf.Classification.Distance.MinkowskiDistance

MinkowskiDistance Constructor

ModuleParams - class marf.Storage.ModuleParams.

Class ModuleParams

ModuleParams() - Constructor for class marf.Storage.ModuleParams

Default Constructor

MP3 - Static variable in class marf.MARF

Indicates MP3 incoming sample file format

MP3 - Static variable in class marf.Storage.Sample

MP3 sample format

MP3Loader - class marf.Storage.Loaders.MP3Loader.

Not Implemented

MP3Loader() - Constructor for class marf.Storage.Loaders.MP3Loader

MP3 Loader Constructor

N

name - Variable in class marf.Classification.NeuralNetwork.Neuron

Neuron's name

NEURAL_NETWORK - Static variable in class marf.MARF

Indicates to use Neural Network for classification

NeuralNetwork - class marf.Classification.NeuralNetwork.NeuralNetwork.

Class NeuralNetwork

NeuralNetwork(FeatureExtraction) - Constructor for class marf.Classification.NeuralNetwork.NeuralNetwork

NeuralNetwork Constructor

Neuron - class marf.Classification.NeuralNetwork.Neuron.

Class Neuron

Neuron(String, int) - Constructor for class marf.Classification.NeuralNetwork.Neuron

Neuron Constructor

NormalFFT(double[], double[]) - Static method in class marf.FeatureExtraction.FFT.FFT

Performs a normal FFT, taking a real input (supposedly an audio sample) and returns the frequency analysis in terms of "magnitude"

NormalFFT(double[], double[], double[]) - Static method in class marf.FeatureExtraction.FFT.FFT

Performs a normal FFT, taking a real input (supposedly an audio sample) and returns the frequency analysis in terms of "magnitude" and "phase angle"

normalize() - Method in class marf.Preprocessing.Preprocessing

Normalization of incoming samples by amplitude.

NotImplementedException - exception marf.util.NotImplementedException.

Class NotImplementedException

NotImplementedException(String) - Constructor for class marf.util.NotImplementedException

Generic exception

O

oAudioFormat - Variable in class marf.Storage.SampleLoader

Properties of a wave.

oAudioInputStream - Variable in class marf.Storage.SampleLoader

Stream representing wave sample.

oByteArrayOutputStream - Variable in class marf.Storage.SampleLoader

Output stream used for writing audio data.

oFeatureExtraction - Variable in class marf.Classification.Classification

Reference to the FeatureExtraction object

oPreprocessing - Variable in class marf.FeatureExtraction.FeatureExtraction

Internal reference to the Preprocessing module

oResult - Variable in class marf.Classification.Classification

Classification Result

oSample - Variable in class marf.Preprocessing.Preprocessing

Sample container

oSample - Variable in class marf.Storage.SampleLoader

Sample references of the sample to be loaded.

oTrainingSet - Variable in class marf.Classification.Classification

TrainingSet Container

OUTPUT - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates output neuron

outputEncoding - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

All output will use this encoding

P

preprocess() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to do general preprocessing and perhaps calling removeNoise() and removeSilence().

preprocess() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of preprocess() for testing.

preprocess() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

preprocess() - Method in class marf.Preprocessing.FFTFilter.FFTFilter

FFTFilter implementation of preprocess()

preprocess() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Overrides FFTFilter's preprocess with extra normalization after boost.

Preprocessing - class marf.Preprocessing.Preprocessing.

Class Preprocessing

Preprocessing(Sample) - Constructor for class marf.Preprocessing.Preprocessing

Preprocessing Constructor

PreprocessingException - exception marf.Preprocessing.PreprocessingException.

Class PreprocessingException

PreprocessingException(String) - Constructor for class marf.Preprocessing.PreprocessingException

Generic exception

printXML(BufferedWriter, int) - Method in class marf.Classification.NeuralNetwork.Neuron

Dumps XML of the current Neuron

Q

queryResultID() - Static method in class marf.MARF

Queries for the final classification result

R

RANDOM_CLASSIFICATION - Static variable in class marf.MARF

Indicates to use random classification

RANDOM_FEATURE_EXTRACTION - Static variable in class marf.MARF

Indicates to use random feature extraction

RandomClassification - class marf.Classification.RandomClassification.RandomClassification.

Class RandomClassification

RandomClassification(FeatureExtraction) - Constructor for class marf.Classification.RandomClassification.RandomClassification

RandomClassification Constructor

RandomFeatureExtraction - class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction.

Class RandomFeatureExtraction.

RandomFeatureExtraction(Preprocessing) - Constructor for class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

RandomFeatureExtraction Constructor

readAudioData(double[]) - Method in class marf.Storage.SampleLoader

Reads audio data from the sample's audio stream into paiAudioData.

readAudioData(double[]) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

readAudioData(double[]) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

readAudioData(double[]) - Method in class marf.Storage.Loaders.WAVLoader

Buffers out the contents of audioBuffer into audioData

recognize() - Static method in class marf.MARF

Recognition/Identification mode

removeNoise() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to remove noise from the sample.

removeNoise() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of removeNoise() for testing.

removeNoise() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

removeNoise() - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of removeNoise()

removeNoise() - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of removeNoise()

removeSilence() - Method in class marf.Preprocessing.Preprocessing

Derivatives implement this method to remove silence.

removeSilence() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of removeSilence() for testing.

removeSilence() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

removeSilence() - Method in class marf.Preprocessing.FFTFilter.BandpassFilter

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.HighFrequencyBoost

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.HighPassFilter

Stub implementation of removeSilence()

removeSilence() - Method in class marf.Preprocessing.FFTFilter.LowPassFilter

Stub implementation of removeSilence()

reset() - Method in class marf.Storage.SampleLoader

Resets the marker for the audio stream.

resetArrayMark() - Method in class marf.Storage.Sample

Resets the marker used for reading audio data from sample array

restore() - Method in class marf.Preprocessing.Preprocessing

Not Implemented

restore() - Method in class marf.Preprocessing.Dummy.Dummy

Dummy implementation of restore() for testing.

restore() - Method in class marf.Preprocessing.Endpoint.Endpoint

Not Implemented

restore() - Method in class marf.FeatureExtraction.FFT.FFT

Not Implemented

restore() - Method in class marf.FeatureExtraction.LPC.LPC

Not Implemented

restore() - Method in class marf.FeatureExtraction.F0.F0

Not Implemented

restore() - Method in class marf.FeatureExtraction.Cepstral.Cepstral

Not Implemented

restore() - Method in class marf.FeatureExtraction.Segmentation.Segmentation

Not Implemented

restore() - Method in class marf.FeatureExtraction.RandomFeatureExtraction.RandomFeatureExtraction

Not Implemented

restore() - Method in class marf.Classification.Classification

Generic implementation of restore() for TrainingSet

restore() - Method in class marf.Classification.Markov.Markov

Not Implemented

restore() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Retsores Neural Net from an XML file

restore() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

restore() - Method in class marf.Classification.RandomClassification.RandomClassification

Restores "training set" of IDs

restore() - Method in interface marf.Storage.StorageManager

An object must know how retore its non-transient data structures from a file.

restore() - Method in class marf.Storage.TrainingSet

Retrieve the current training set from disk

restore() - Method in class marf.gui.Spectrogram

Not implemented

restore() - Method in class marf.gui.WaveGrapher

Not implemented

restore(BufferedReader) - Method in class marf.Storage.TrainingSet.TrainingSample

Retrieve one training sample from a text file.

result - Variable in class marf.Classification.NeuralNetwork.Neuron

Current Neuron's result

Result - class marf.Storage.Result.

Class Result

Result() - Constructor for class marf.Storage.Result

Default Constructor Equivalent to Result(0)

Result(double[]) - Constructor for class marf.Storage.Result

ResultSet Constructor Equivalent to Result(0, padResultSet)

Result(int) - Constructor for class marf.Storage.Result

ID Constructor

Result(int, double[]) - Constructor for class marf.Storage.Result

ID ResultSet Constructor

Result(int, Vector) - Constructor for class marf.Storage.Result

ID Vector ResultSet Constructor

S

Sample - class marf.Storage.Sample.

Class Sample

Sample() - Constructor for class marf.Storage.Sample

Default constructor

Sample(double[]) - Constructor for class marf.Storage.Sample

Accepts pre-set sample for testing

Sample(int) - Constructor for class marf.Storage.Sample

Constructor with format indication

SampleLoader - class marf.Storage.SampleLoader.

Absract Class SampleLoader

SampleLoader() - Constructor for class marf.Storage.SampleLoader

Default constructor.

saveSample(File) - Method in class marf.Storage.SampleLoader

SampleLoader interface.

saveSample(File) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

saveSample(File) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

saveSample(File) - Method in class marf.Storage.Loaders.WAVLoader

Saves the wave into a file for playback

saveSample(String) - Method in class marf.Storage.SampleLoader

Same as saveSample(File) but takes filename as an argument.

Segmentation - class marf.FeatureExtraction.Segmentation.Segmentation.

Class Segmentation

SEGMENTATION - Static variable in class marf.MARF

Indicates to use segmentation

Segmentation(Preprocessing) - Constructor for class marf.FeatureExtraction.Segmentation.Segmentation

Segmentation Constructor

setAudioFormat(int) - Method in class marf.Storage.Sample

Sets current format of a sample

setClassificationMethod(int) - Static method in class marf.MARF

Sets classification method to be used

setClassificationParams(Vector) - Method in class marf.Storage.ModuleParams

Sets classification parameters vector

setCurrentSubject(int) - Static method in class marf.MARF

Sets ID of a subject currently being trained on

setDumpMode(int) - Method in class marf.Storage.TrainingSet

Sets the dump mode

setDumpSpectrogram(boolean) - Static method in class marf.MARF

Indicates whether spectrogram is wanted as an output of a FeatureExtraction module

setDumpWaveGraph(boolean) - Static method in class marf.MARF

Indicates whether wave graph is wanted as an output

setFeatureExtractionMethod(int) - Static method in class marf.MARF

Sets feature extraction method to be used

setFeatureExtractionMethod(int) - Method in class marf.Storage.TrainingSet

Sets feature extraction method used on this training set

setFeatureExtractionParams(Vector) - Method in class marf.Storage.ModuleParams

Sets feature extraction parameters vector

setFrequencyResponse(double[]) - Method in class marf.Preprocessing.FFTFilter.FFTFilter

Sets frequency response.

setID(int) - Method in class marf.Storage.Result

Sets ID, should only be called by a Classification module

setMeanVector(double[]) - Method in class marf.Storage.TrainingSet.TrainingSample

Sets new mean vector

setModuleParams(ModuleParams) - Static method in class marf.MARF

Sets module-specific parameters an application programmer wishes to pass on to the module

setPreprocessingMethod(int) - Static method in class marf.MARF

Sets preprocessing method to be used

setPreprocessingMethod(int) - Method in class marf.Storage.TrainingSet

Sets feature extraction method used on this training set

setPreprocessingParams(Vector) - Method in class marf.Storage.ModuleParams

Sets preprocessing parameters vector

setSample(Sample) - Method in class marf.Storage.SampleLoader

Sets internal sample reference from outside

setSampleArray(double[]) - Method in class marf.Storage.Sample

Sets the internal sample array (adSample) with the specified argument.

setSampleFile(String) - Static method in class marf.MARF

Sets input sample file name

setSampleFormat(int) - Static method in class marf.MARF

Sets input sample file format

setSamplesDir(String) - Static method in class marf.MARF

Sets directory with sample files to be read from

setSubjectID(int) - Method in class marf.Storage.TrainingSet.TrainingSample

Sets new Subject ID

setTrainingSetFile(String) - Method in class marf.Storage.TrainingSet

Sets current training set file name

size() - Method in class marf.Storage.TrainingSet

Gets the size of the feature vectors set

Spectrogram - class marf.gui.Spectrogram.

Class Spectrogram

Spectrogram() - Constructor for class marf.gui.Spectrogram

Constructor

Spectrogram(String) - Constructor for class marf.gui.Spectrogram

Constructor with a feature extraction method name

StatsCollector - class marf.Stats.StatsCollector.

Not Implemented

StatsCollector() - Constructor for class marf.Stats.StatsCollector

Stochastic - class marf.Classification.Stochastic.Stochastic.

Class Stochastic

STOCHASTIC - Static variable in class marf.MARF

Indicates to use stochastic models for classification

Stochastic(FeatureExtraction) - Constructor for class marf.Classification.Stochastic.Stochastic

Stochastic Constructor

StorageManager - interface marf.Storage.StorageManager.

Interface StorageManager

streamedRecognition() - Static method in class marf.MARF

Meant to provide implementation of the buffered sample processing for large samples.

strMessage - Variable in class marf.util.MARFException

Error message container

strMethod - Variable in class marf.gui.Spectrogram

To differentiate file names based on the feature extraction method name.

strTrainingSetFile - Variable in class marf.Storage.TrainingSet

TrainingSet file name

T

threshold - Variable in class marf.Classification.NeuralNetwork.Neuron

Activation threshhold

train() - Static method in class marf.MARF

Training mode

train() - Method in class marf.Classification.Classification

Generic training routine for building/updating mean vectors in the training set.

train() - Method in class marf.Classification.Markov.Markov

Not Implemented

train() - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Implementes training of Neural Net

train() - Method in class marf.Classification.Stochastic.Stochastic

Not Implemented

train() - Method in class marf.Classification.RandomClassification.RandomClassification

Simply stores incoming ID's

train(double[], int, double) - Method in class marf.Classification.NeuralNetwork.NeuralNetwork

Actual training of the net

train(double, double, double) - Method in class marf.Classification.NeuralNetwork.Neuron

Neuron training

TrainingSet - class marf.Storage.TrainingSet.

TrainingSet -- Encapsulates Speaker ID and speaker's clusters of "feature" sets

TrainingSet.TrainingSample - class marf.Storage.TrainingSet.TrainingSample.

TrainingSample contains one item in the training set.

TrainingSet.TrainingSample(TrainingSet) - Constructor for class marf.Storage.TrainingSet.TrainingSample

TrainingSet() - Constructor for class marf.Storage.TrainingSet

Construct a training set object.

type - Variable in class marf.Classification.NeuralNetwork.Neuron

Current neuron type

U

ULAW - Static variable in class marf.MARF

Indicates ULAW incoming sample file format

ULAW - Static variable in class marf.Storage.Sample

ULAW sample format

ULAWLoader - class marf.Storage.Loaders.ULAWLoader.

Not Implemented

ULAWLoader() - Constructor for class marf.Storage.Loaders.ULAWLoader

ULAWLoader Constructor

UNDEF - Static variable in class marf.Classification.NeuralNetwork.Neuron

Indicates undefined neuron type

UNK - Static variable in class marf.Storage.Sample

Unknown sample format

updateSample() - Method in class marf.Storage.SampleLoader

UpdateSample() is just used whenever the AudioInputStream is assigned to a new value (wave file).

W

W3C_XML_SCHEMA - Static variable in class marf.Classification.NeuralNetwork.NeuralNetwork

XML 2001 Schema

WAV - Static variable in class marf.MARF

Indicates WAV incoming sample file format

WAV - Static variable in class marf.Storage.Sample

WAVE sample format

WaveGrapher - class marf.gui.WaveGrapher.

Class WaveGrapher

WaveGrapher(double[], double, double, String, String) - Constructor for class marf.gui.WaveGrapher

Constructor

WAVLoader - class marf.Storage.Loaders.WAVLoader.

Class WAVLoader

WAVLoader() - Constructor for class marf.Storage.Loaders.WAVLoader

WAVLoader Constructor.

writeAudioData(double[], int) - Method in class marf.Storage.SampleLoader

Writes audio data into the sample's audio stream.

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.MP3Loader

Not Implemented

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.ULAWLoader

Not Implemented

writeAudioData(double[], int) - Method in class marf.Storage.Loaders.WAVLoader

Buffers the contents of audioData into audioBuffer

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