public void testStretch2() {
double[] signal = FFTTest.getSampleSignal(16000);
int samplingRate = 8000;
double rateFactor = 0.5;
NaiveVocoder nv =
new NaiveVocoder(new BufferedDoubleDataSource(signal), samplingRate, rateFactor);
double[] result = nv.getAllData();
double meanSignalEnergy = MathUtils.mean(MathUtils.multiply(signal, signal));
double meanResultEnergy = MathUtils.mean(MathUtils.multiply(result, result));
double percentDifference =
Math.abs(meanSignalEnergy - meanResultEnergy) / meanSignalEnergy * 100;
assertTrue(
"Stretching changed signal energy by " + percentDifference + "%", percentDifference < 6);
}
@Override
public boolean compute() throws IOException, MaryConfigurationException {
logger.info("Duration tree trainer started.");
FeatureFileReader featureFile = FeatureFileReader.getFeatureFileReader(getProp(FEATUREFILE));
UnitFileReader unitFile = new UnitFileReader(getProp(UNITFILE));
FeatureVector[] allFeatureVectors = featureFile.getFeatureVectors();
int maxData = Integer.parseInt(getProp(MAXDATA));
if (maxData == 0) maxData = allFeatureVectors.length;
FeatureVector[] featureVectors = new FeatureVector[Math.min(maxData, allFeatureVectors.length)];
System.arraycopy(allFeatureVectors, 0, featureVectors, 0, featureVectors.length);
logger.debug(
"Total of "
+ allFeatureVectors.length
+ " feature vectors -- will use "
+ featureVectors.length);
AgglomerativeClusterer clusterer =
new AgglomerativeClusterer(
featureVectors,
featureFile.getFeatureDefinition(),
null,
new DurationDistanceMeasure(unitFile),
Float.parseFloat(getProp(PROPORTIONTESTDATA)));
DirectedGraphWriter writer = new DirectedGraphWriter();
DirectedGraph graph;
int iteration = 0;
do {
graph = clusterer.cluster();
iteration++;
if (graph != null) {
writer.saveGraph(graph, getProp(DURTREE) + ".level" + iteration);
}
} while (clusterer.canClusterMore());
if (graph == null) {
return false;
}
// Now replace each leaf with a FloatLeafNode containing mean and stddev
for (LeafNode leaf : graph.getLeafNodes()) {
FeatureVectorLeafNode fvLeaf = (FeatureVectorLeafNode) leaf;
FeatureVector[] fvs = fvLeaf.getFeatureVectors();
double[] dur = new double[fvs.length];
for (int i = 0; i < fvs.length; i++) {
dur[i] =
unitFile.getUnit(fvs[i].getUnitIndex()).duration / (float) unitFile.getSampleRate();
}
double mean = MathUtils.mean(dur);
double stddev = MathUtils.standardDeviation(dur, mean);
FloatLeafNode floatLeaf = new FloatLeafNode(new float[] {(float) stddev, (float) mean});
Node mother = fvLeaf.getMother();
assert mother != null;
if (mother.isDecisionNode()) {
((DecisionNode) mother).replaceDaughter(floatLeaf, fvLeaf.getNodeIndex());
} else {
assert mother.isDirectedGraphNode();
assert ((DirectedGraphNode) mother).getLeafNode() == fvLeaf;
((DirectedGraphNode) mother).setLeafNode(floatLeaf);
}
}
writer.saveGraph(graph, getProp(DURTREE));
return true;
}
