/**
* Copyright 2010 DFKI GmbH.
* All Rights Reserved. Use is subject to license terms.
*
* This file is part of MARY TTS.
*
* MARY TTS is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published by
* the Free Software Foundation, version 3 of the License.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
*/
package marytts.vocalizations;
import java.awt.Color;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import javax.sound.sampled.AudioFormat;
import javax.sound.sampled.AudioInputStream;
import javax.sound.sampled.AudioSystem;
import javax.sound.sampled.UnsupportedAudioFileException;
import javax.swing.JFrame;
import marytts.machinelearning.KMeansClusteringTrainerParams;
import marytts.machinelearning.PolynomialCluster;
import marytts.machinelearning.PolynomialKMeansClusteringTrainer;
import marytts.signalproc.display.FunctionGraph;
import marytts.util.data.BufferedDoubleDataSource;
import marytts.util.data.audio.AudioDoubleDataSource;
import marytts.util.data.audio.AudioPlayer;
import marytts.util.data.audio.DDSAudioInputStream;
import marytts.util.math.Polynomial;
public class KMeansClusterer {
private ArrayList<String> baseNames;
Polynomial[] f0Polynomials;
private int polynomialOrder = 3;
private int numberOfSamples = 0;
private int numberOfClusters;
private HashMap<Polynomial, String> mapPolynomialBaseNames;
public KMeansClusterer() {
baseNames = new ArrayList<String>();
mapPolynomialBaseNames = new HashMap<Polynomial, String>();
}
public void loadF0Polynomials(String fileName) throws IOException {
BufferedReader bfr = new BufferedReader(new FileReader(new File(fileName)));
String line;
ArrayList<String> lines = new ArrayList<String>();
while ((line = bfr.readLine()) != null) {
lines.add(line.trim());
}
double[][] f0PolynomialCoeffs;
String[] words = lines.get(0).trim().split("\\s+");
polynomialOrder = words.length - 1;
numberOfSamples = lines.size();
f0PolynomialCoeffs = new double[numberOfSamples][polynomialOrder];
f0Polynomials = new Polynomial[numberOfSamples];
for (int i = 0; i < lines.size(); i++) {
line = lines.get(i);
words = line.trim().split("\\s+");
baseNames.add(words[0].trim());
for (int j = 0; j < polynomialOrder; j++) {
f0PolynomialCoeffs[i][j] = (new Double(words[j + 1].trim())).doubleValue();
}
// System.out.println(f0PolynomialCoeffs[i][0]+" "+f0PolynomialCoeffs[i][1]+" "+f0PolynomialCoeffs[i][2]+" "+f0PolynomialCoeffs[i][3]);
// System.out.println(words[0]+" "+words[1]+" "+words[2]+" "+words[3]+" "+words[4]);
}
// testing
for (int i = 0; i < numberOfSamples; i++) {
f0Polynomials[i] = new Polynomial(f0PolynomialCoeffs[i]);
mapPolynomialBaseNames.put(f0Polynomials[i], baseNames.get(i));
System.out.print(baseNames.get(i) + " ");
for (int j = 0; j < polynomialOrder; j++) {
System.out.print(f0PolynomialCoeffs[i][j] + " ");
}
System.out.println();
double coeff[] = f0Polynomials[i].coeffs;
System.out.print(baseNames.get(i) + " ");
for (int j = 0; j < coeff.length; j++) {
System.out.print(coeff[j] + " ");
}
System.out.println();
}
}
public void trainer(int numClusters) throws UnsupportedAudioFileException, IOException {
this.numberOfClusters = numClusters;
KMeansClusteringTrainerParams params = new KMeansClusteringTrainerParams();
params.numClusters = numClusters;
params.maxIterations = 10000;
// Train:
PolynomialCluster[] clusters = PolynomialKMeansClusteringTrainer.train(f0Polynomials, params);
// Visualise:
FunctionGraph clusterGraph = new FunctionGraph(0, 1, new double[1]);
clusterGraph.setYMinMax(-550, 500);
clusterGraph.setPrimaryDataSeriesStyle(Color.BLUE, FunctionGraph.DRAW_DOTS, FunctionGraph.DOT_FULLCIRCLE);
JFrame jf = clusterGraph.showInJFrame("", false, true);
for (int i = 0; i < clusters.length; i++) {
double[] meanValues = clusters[i].getMeanPolynomial().generatePolynomialValues(100, 0, 1);
clusterGraph.updateData(0, 1. / meanValues.length, meanValues);
Polynomial[] members = clusters[i].getClusterMembers();
System.out.print("Cluster " + i + " : ");
for (int m = 0; m < members.length; m++) {
double[] pred = members[m].generatePolynomialValues(meanValues.length, 0, 1);
clusterGraph.addDataSeries(pred, Color.GRAY, FunctionGraph.DRAW_LINE, -1);
String baseName = mapPolynomialBaseNames.get(members[m]);
System.out.print(baseName + " ");
jf.repaint();
String waveFile = "/home/sathish/Work/phd/voices/f0desc-listener/vocalizations/wav/" + File.separator + baseName
+ ".wav";
AudioInputStream inputAudio = AudioSystem.getAudioInputStream(new File(waveFile));
// Enforce PCM_SIGNED encoding
if (!inputAudio.getFormat().getEncoding().equals(AudioFormat.Encoding.PCM_SIGNED)) {
inputAudio = AudioSystem.getAudioInputStream(AudioFormat.Encoding.PCM_SIGNED, inputAudio);
}
int audioSampleRate = (int) inputAudio.getFormat().getSampleRate();
AudioDoubleDataSource signal = new AudioDoubleDataSource(inputAudio);
double[] sentenceAudio = signal.getAllData();
AudioPlayer ap = new AudioPlayer(new DDSAudioInputStream(new BufferedDoubleDataSource(sentenceAudio),
new AudioFormat(AudioFormat.Encoding.PCM_SIGNED, audioSampleRate, // samples per second
16, // bits per sample
1, // mono
2, // nr. of bytes per frame
audioSampleRate, // nr. of frames per second
true))); // big-endian;))
ap.start();
try {
ap.join();
Thread.sleep(10);
} catch (InterruptedException ie) {
}
}
System.out.println();
jf.setTitle("Cluster " + (i + 1) + " of " + clusters.length + ": " + members.length + " members");
jf.repaint();
try {
Thread.sleep(5000);
} catch (InterruptedException ie) {
}
}
}
/**
* @param args
* args
* @throws IOException
* IOException
* @throws UnsupportedAudioFileException
* UnsupportedAudioFileException
*/
public static void main(String[] args) throws IOException, UnsupportedAudioFileException {
KMeansClusterer kmc = new KMeansClusterer();
// String fileName = "/home/sathish/phd/voices/en-GB-listener/vocal-polynomials/all.listener.polynomials.txt";
// String fileName = "/home/sathish/phd/voices/en-GB-listener/vocal-polynomials/SpiVocalizationF0PolyFeatureFile.txt";
String fileName = "/home/sathish/phd/voices/en-GB-listener/yeahPrudenceVocalizationF0PolyFeatureFile.txt";
kmc.loadF0Polynomials(fileName);
kmc.trainer(5);
System.exit(0);
}
}